This resource provides a detailed tutorial on using Excel pivot tables for summarizing and analyzing large datasets. It begins by explaining the purpose and usefulness of pivot tables, contrasting them with static Excel tables and demonstrating their dynamic nature. The material then focuses heavily on data cleaning techniques that are essential before creating a pivot table, covering the removal of blank rows, duplicates, and unwanted formatting, as well as using formulas and features like Flash Fill to standardize text, dates, and separate combined data. Finally, the tutorial walks through creating and building a pivot table from scratch, explaining the pivot table field list, adding and manipulating fields, understanding aggregation methods (sum, count, average, etc.), grouping data, and customizing the report layout with subtotals, grand totals, and blank rows.
Mastering Excel Pivot Tables
Based on the information from the sources, here is a discussion about Pivot Tables in Excel:
What are Pivot Tables and Why are They Useful?
Effectively, pivot tables are an interactive way of quickly summarizing large amounts of data. In our data-driven world, many individuals collect data from various sources to support better business decisions. However, simply looking at large datasets in an Excel spreadsheet doesn’t clearly highlight key metrics, issues, successes, failures, or trends. Pivot tables provide a way to take this data and make sense of it.
For example, with a dataset of over 14,000 rows of sales data including region, country, item type, sales channel, order priority, order date, order ID, ship date, units sold, unit price, unit cost, total revenue, total cost, and total profit, it’s difficult to easily see things like the top 10 countries by total profit or the number of high-priority orders. Using filter drop-downs is possible but much less efficient than using a pivot table.
The key difference between a regular Excel table and a pivot table is that pivot tables are dynamic. This means you can quickly change the analysis being performed. By moving fields around, you can instantly view the data summarized in different ways, such as seeing the sum of total profit by country after initially looking at units sold. You can add other fields to break down the analysis further, like dropping ‘item type’ into columns to see sales summarized by country and item type. You can also apply filters, for instance, to show only the top five countries to make the data more manageable. Once data is in a pivot table, it can be pivoted in various ways, allowing the creation of more pivot tables and even pivot charts. This opens up opportunities for visual analysis, which is often easier for people to interpret. Ultimately, this can lead to creating interactive dashboards showing key metrics with filters.
In summary, a pivot table is a dynamic, interactive tool for summarizing large datasets. They are useful because they help analyze large datasets in a clear and effective way.
Difference Between Excel Tables and Pivot Tables
It’s important to understand the distinction between Excel Tables and Pivot Tables, as they are not the same. Excel tables are essentially static; you can sort or filter the data, but you cannot easily analyze it in many different ways. In contrast, pivot tables are much more dynamic. With a pivot table, you can move fields around and add different fields to view your data in numerous ways, making them ideal for data analysis.
The sources strongly recommend putting your data into an Excel table prior to creating a pivot table. While it might seem like an extra step, there are many advantages to using Excel tables that make working with pivot tables much easier. One of the most useful features of Excel tables is their auto-expand capabilities. If you add new data to the bottom of an Excel table, it automatically expands to include that data. This means that any pivot table or chart linked to that Excel table will automatically include the new data after a simple refresh. If your data is not in an Excel table, you would have to manually reselect the data range to include new rows.
When data is formatted as an Excel table, it automatically gets some formatting like shading and borders, plus filter and sort drop-downs in the headers. An additional ribbon called Table Design appears when you select a cell within the table. This contextual ribbon contains tools to format the table, apply options, and access table tools.
Preparing Data Before Creating a Pivot Table (Data Cleaning)
Before analyzing data with a pivot table, it is extremely important to clean the data. Data cleaning refers to processes in Excel used to tidy up datasets, make them consistent, format them correctly, and present the data in a way that a pivot table can easily analyze and produce accurate results. Skipping this step can lead to inaccurate analysis. This is particularly crucial if data is downloaded from a third party, external source, or database, as it may not import into Excel in the expected format. Issues like columns being out of place, strange formatting, blank rows, blank cells, or duplicate entries can occur.
Several techniques are discussed for cleaning data:
Removing Blank Rows: Blank rows make data harder to read and cause issues in pivot tables, appearing as a ‘blank’ entry. Manually deleting them is tedious for large datasets. Excel provides a quicker way:
Select the data range (e.g., using Ctrl+A while clicked in the data).
Go to the Home tab, in the Editing group, click Find & Select, and choose Go To Special.
Select ‘Blanks’ and click OK. This selects all blank cells/rows in the selection.
Go back to the Home tab, in the Cells group, click Delete, and select Delete Sheet Rows. Removing blank rows before creating a pivot table ensures accuracy and prevents the ‘blank’ entry from appearing.
Removing Duplicates: Duplicates can also cause problems for pivot tables. The desired removal depends on the type of duplicate; for instance, removing duplicate records where every column is identical, as opposed to repeated values in a single column like ‘Online’/’Offline’ in sales channel. Excel has a Remove Duplicates utility for this.
Click anywhere in the data.
Go to the Data tab, in the Data Tools group, click Remove Duplicates.
A dialog box appears allowing you to select which columns to consider when checking for duplicates.
Formatting Data: Applying the correct formatting is important.
Columns with text (like Region, Country, Item Type) can be formatted as Text using the Format Cells dialog box (Ctrl+1).
Dates might appear as numbers if date formatting isn’t applied. This is because Excel stores dates as numbers, counting days since January 1st, 1900. To display them correctly, select the column and apply Short Date or Long Date format from the Home tab’s Number group.
Numeric columns (like Unit Price, Total Revenue, Total Profit) should have appropriate number formatting. Currency and Accounting formats are common for monetary values. Accounting format often aligns currency symbols to the left and decimal places, which many find easier to read than Currency format where the symbol is next to the value. This can be applied via the Home tab or the Format Cells dialog box (Ctrl+1).
Tidying Up Text: Inconsistencies in text, such as different cases (uppercase, lowercase, proper case) or erroneous spaces (leading, trailing, or multiple spaces between words), can make analysis inaccurate.
Changing Case: Use Excel text formulas like UPPER(), LOWER(), or PROPER(). A recommended method is to use a “helper column” next to the column needing changes, write the formula (e.g., =PROPER(B4)) in the first cell, copy it down, then copy the results and use Paste Special > Paste Values over the original column to remove the formulas, and finally delete the helper column.
Removing Spaces: The TRIM() function removes leading, trailing, and excessive spaces within text. Even if spaces aren’t visible, applying TRIM() is a good practice. Similar to changing case, use a helper column, the TRIM() formula (e.g., =TRIM(B4)), copy/paste values, and delete the helper column.
Removing Line Breaks: The CLEAN() function removes non-printable characters, including line breaks. Again, use a helper column, the CLEAN() formula (e.g., =CLEAN(A4)), copy/paste values, and delete the helper column.
Splitting Data: Sometimes a single column contains multiple pieces of data that should be separate (e.g., Order Date and Order ID combined).
Text to Columns: This feature is useful when data is separated by a consistent delimiter (like a comma, tab, space, or other character).
Select the column(s) you want to split.
Go to the Data tab, in the Data Tools group, click Text to Columns.
In the wizard, choose ‘Delimited’ if your data has separators or ‘Fixed width’ if data is aligned in columns.
Specify the delimiter(s). The preview shows how the data will be split.
Choose the data format for each new column (optional, General often works) and importantly, the Destination cell where the split data should start appearing.
Click Finish.
Flash Fill: This feature, introduced in Excel 2013, automatically fills data based on a detected pattern. It can be used to split data (e.g., first name and last name from a full name) or combine data.
Type the desired output for the first item in a new column next to your data.
Press Ctrl+Enter to stay in the cell.
Go to the Data tab, in the Data Tools group, click Flash Fill (or use the shortcut Ctrl+E). Excel will attempt to apply the pattern to the rest of the column. You can also start typing the second item, and Flash Fill may show a grayed-out preview; hit Enter if it’s correct.
Using Formulas: Excel functions like CONCAT() (or CONCATENATE() in older versions) can combine data from multiple cells. These are useful if you need to add specific text or characters (like a hyphen and spaces) between the combined data. Formulas require referencing the cells and enclosing text within quote marks.
Replacing Data: You might need to replace specific text or values.
Find and Replace: This utility (Ctrl+H) can find specific text and replace it with something else throughout the selected range.
Substitute Formula: The SUBSTITUTE() function can replace specific text within a cell based on a formula (e.g., =SUBSTITUTE(B4,”UK”,”United Kingdom”)). Like other formulas, you’d use a helper column and Paste Special > Paste Values to apply the result.
Spell Check: Running a spell check is crucial because if something is misspelled, a pivot table will treat it as a completely separate item, leading to inaccurate analysis. The Spell Checker is on the Review tab in the Proofing group (F7 shortcut). It starts checking from the currently selected cell. You can choose to ignore, change, change all, or add words to the dictionary (useful for names or brands not in the standard dictionary).
Putting Data into an Excel Table
As mentioned, it is highly recommended to put your clean data into an Excel Table before creating a pivot table. You must be clicked somewhere within your data set to do this.
There are two main ways to format data as a table:
Go to the Home tab, in the Styles group, click the Format as Table drop-down and choose a table style.
Click anywhere in the data and press the keyboard shortcut Ctrl+T. This opens the Create Table dialog box.
Both methods will ask if your table has headers. Once applied, your data gets default formatting and the Table Design contextual ribbon appears. From the Table Design ribbon, you can customize the style, add a total row, toggle banded rows or columns, and turn the filter button on/off.
In the Properties group of the Table Design ribbon, you can see and rename the table. It’s good practice to give your table a meaningful name (like Sales_Data) instead of the default generic name (like Table1) because it makes referencing the data easier, especially in workbooks with multiple tables. Table names cannot contain spaces.
Creating a Pivot Table
Once your data is clean and in an Excel table, you are ready to create a pivot table.
Recommended Pivot Tables: Excel can analyze your data and suggest pivot table layouts.
Click anywhere in your data table.
Go to the Insert tab, in the Tables group, click Recommended PivotTables.
A window pops up showing different suggested pivot table summaries based on your data (e.g., sum of unit price by region, sum of profit by item type).
Select the one that best suits your needs and click OK. Excel creates a new worksheet with the pre-built pivot table. You can still modify this table afterward.
Creating a Blank Pivot Table from Scratch: This gives you full control over the layout.
Click anywhere in your data table.
Go to the Insert tab, in the Tables group, click PivotTable. Alternatively, from the Table Design ribbon, in the Tools group, click Summarize with PivotTable. Both methods open the Create PivotTable dialog box.
Choose the data: The dialog box should automatically detect and select your Excel table (e.g., Sales_Data). You can also choose to use an external data source from another file or database.
Choose where to place the report: The common and recommended practice is to place the pivot table on a New Worksheet to keep your raw data separate from your analysis. You can also choose an existing worksheet.
Click OK. Excel creates a new worksheet containing a blank pivot table report area and the PivotTable Fields pane on the right.
Understanding the Pivot Table Interface
When you click inside the blank pivot table report area, two additional contextual ribbons appear: PivotTable Analyze and PivotTable Design. These ribbons contain commands for managing, organizing, and changing the look of your pivot table. They disappear when you click outside the pivot table.
PivotTable Design Ribbon: Focuses on the appearance and layout.
PivotTable Styles: Similar to table styles, allows choosing a visual style. Styles are influenced by the workbook’s theme.
PivotTable Style Options: Toggles elements like row/column headers, banded rows/columns.
Layout: Controls subtotals (show/hide, position), grand totals (on/off for rows/columns), and report layout (Compact, Outline, Tabular forms). You can also insert or remove blank lines after each item.
PivotTable Name: It’s good practice to rename pivot tables from generic names (e.g., PivotTable1) to meaningful names.
Options: Accesses various pivot table settings, including layout and format options like auto-fitting column widths.
Group: Used for grouping selected items or ungrouping.
Insert Slicer / Insert Timeline: Visual filters for pivot tables (not covered in detail in this source).
Refresh: Updates the pivot table with any changes to the source data.
Show group: Toggle buttons to show/hide the Field List pane, plus/minus buttons, and headers. If the Field List disappears, check this button.
The PivotTable Fields pane (usually on the right) is crucial for building the pivot table. At the top, it lists all the column headings from your source data as fields. Below are four areas: Filters, Columns, Rows, and Values. These areas determine the layout and type of analysis.
Building and Modifying a Pivot Table
Building a pivot table involves dragging fields from the top section of the PivotTable Fields pane into one of the four areas.
Rows Area: Typically used for fields you want to appear as row labels (e.g., Region, Item Type).
Columns Area: Typically used for fields you want to appear as column labels (e.g., Sales Channel, Order Priority).
Values Area: This is where you put fields containing numerical data that you want to summarize (e.g., Total Profit, Units Sold). By default, Excel often performs a Sum on numeric fields dragged here, or a Count if the field contains text or dates.
Filters Area: Fields dragged here create report-level filters at the top of the pivot table, allowing you to filter the entire report by selections from that field (e.g., filtering by specific Countries or Order Dates).
You can easily change the layout by dragging fields between these areas. Dragging a field outside the pane removes it from the pivot table.
Aggregating Data: The default aggregation (Sum or Count) can be changed.
Right-click on any value in the column you want to change the aggregation for.
Select Value Field Settings.
In the Summarize values by list, choose a different calculation like Average, Max, Min, Product, Count Numbers, etc..
Click OK. You can also access Value Field Settings by clicking the drop-down arrow next to the field in the Values area.
You can combine different methods of aggregation by dragging the same field into the Values area multiple times. Each instance can then be summarized using a different calculation (e.g., one column showing Sum of Total Profit, another showing Average of Total Profit).
Renaming Fields/Headings: You can change the default headings in the pivot table report area (like ‘Row Labels’ or ‘Sum of Total Profit’) by double-clicking the cell and entering a new custom name. Note that renaming a heading in the pivot table report updates the name in the Values area of the fields pane, but the original field name above remains unchanged.
Number Formatting: To ensure formatting (like currency symbols and decimal places) stays with the numbers when the pivot table layout changes, apply it via the pivot table’s specific options, not just standard cell formatting from the Home tab.
Right-click on a number within the column you want to format.
Select Number Format. Alternatively, access this via Value Field Settings > Number Format.
Choose the desired format (e.g., Accounting, Currency) and settings.
Click OK. This applies the formatting to all numbers in that value field.
Handling Empty Cells: By default, pivot tables show blank cells where there is no data for a combination of criteria. This can affect charts or make the table harder to read. You can replace blanks with a value like 0:
Click inside the pivot table.
Go to the PivotTable Analyze ribbon, in the PivotTable group, click Options.
On the Layout & Format tab, under the Format group, check the box for For empty cells show: and enter the value you want to display (e.g., 0).
Click OK.
Grouping Data
Grouping allows you to combine items in your pivot table.
Automatic Grouping: Excel automatically groups dates when you drag a date field into rows or columns. It analyzes the data and creates fields for years, quarters, and months if applicable. These automatically created fields (like ‘Years’ and ‘Quarters’) appear in the PivotTable Fields pane and can be used independently. You can expand/collapse these groups using the +/- buttons in the pivot table.
Custom Grouping: You can create your own groups from non-date fields (e.g., grouping several Item Types into a ‘Food and Drink’ category).
Select the items you want to group by holding down Ctrl and clicking each item.
Go to the PivotTable Analyze ribbon, in the Group group, click Group Selection. Excel creates a new group (e.g., ‘Group1’) and a new field in the Rows/Columns area (e.g., ‘Item Type2’).
You can rename the group label in the pivot table (using F2 or double-clicking and changing the custom name in Value Field Settings) and rename the new group field in the fields pane (using Field Settings).
Ungrouping: To reverse automatic or custom grouping, select an item within the group and click Ungroup in the Group group on the PivotTable Analyze ribbon.
Inserting Blank Lines: To improve readability, especially with grouping, you can insert blank rows between groups. Go to the Design ribbon, in the Layout group, click Blank Rows, and select Insert Blank Line after Each Item. To remove them, choose Remove Blank Line after Each Grouped Item.
Layout Options
You can customize the overall appearance and structure of your pivot table report. These options are found on the PivotTable Design ribbon, in the Layout group.
Subtotals:You can choose not to show subtotals at all.
You can show them at the bottom of each group (often preferred) or at the top of each group (the default).
Grand Totals:You can turn grand totals off for both rows and columns.
You can turn them on for both rows and columns, only for rows, or only for columns. Turning them off is common when creating charts to avoid including totals.
Report Layout: This changes how the fields are displayed in the report area.
Compact Form: Optimizes for readability and uses space efficiently. It places subtotals at the top of groups and keeps related fields in the same column. This is the most compact view.
Outline Form: Moves the innermost row field to a new column, creating a hierarchical structure where each field is in its own column. Subtotals appear at the top by default, but you can change their position.
Tabular Form: Similar to Outline form, but adds grid lines within the pivot table, making it look more like a regular Excel table.
Repeat Item Labels: In Outline or Tabular forms, you can choose to repeat the labels for outer row fields on every line instead of only showing them once. This can make the table easier to read in some cases or is necessary for certain chart types like map charts. You can turn this off if desired.
These options allow you to tailor the pivot table’s appearance to best suit your analysis and presentation needs.
Cleaning Data for Excel Pivot Tables
Data cleaning is a crucial process to undertake before analyzing large datasets, particularly when planning to use tools like pivot tables in Excel. It involves tidying up data sets, making them consistent, formatting them correctly, and presenting the data in a way that allows for easy and accurate analysis. Skipping this step, especially when importing data from external sources or databases, can lead to inaccurate analysis because data doesn’t always import in the expected format, potentially including columns out of place, strange formatting, blank rows, or duplicate entries.
Here are some of the key data cleaning techniques discussed in the sources:
Removing Blank Rows Blank rows make data harder to read and can cause issues in pivot tables by being picked up as a “blank” entry. Manually deleting them row by row is tedious for large datasets. A quicker method involves selecting the data range, using “Go To Special” to select “Blanks,” and then using the “Delete Sheet Rows” command. Removing blank rows ensures the pivot table is accurate.
Removing Duplicate Entries Duplicate rows, particularly where every column’s information is exactly the same, can sometimes occur when importing data and can cause problems for pivot tables. Excel’s “Remove Duplicates” utility can easily find and remove these exact duplicates. You can specify which columns to check for duplicates, but typically, you check all columns to find completely duplicated rows.
Removing Unwanted Formatting Imported data may contain inconsistent formatting like background shading, bold text, or italics, which results in an inconsistent-looking worksheet. This formatting often isn’t desired. The “Clear Formats” option, found under the “Clear” button in the Home tab’s editing group, can quickly remove all applied formatting, including background shading, bold, italics, and number formatting, providing a clean slate. Other “Clear” options exist for different purposes, such as clearing only contents, comments/notes, or hyperlinks.
Applying Desired Formatting After clearing unwanted formatting, applying consistent and appropriate formatting is important to make your data easier to read. This is referred to as number formatting but can be applied to any column, not just those containing numbers. The “Number group” on the Home tab provides standard options like General, Number, Currency, Accounting, and Date. Dates in Excel are stored as numbers (days since January 1, 1900), so applying a Date format (like Short Date or Long Date) is necessary to display them correctly. For numeric data, you can control decimal places using dedicated buttons or the “Format Cells” dialog box (Ctrl + 1). For monetary values, Currency and Accounting formats add symbols; Accounting format is often preferred as it aligns currency symbols and decimal points, enhancing readability for lists of numbers.
Tidying Up Text Using Formulas Inconsistencies in text, such as case variations (uppercase, lowercase, proper case) or erroneous spaces (leading, trailing, multiple spaces between words), can negatively impact analysis. Excel provides text functions to standardize these:
UPPER(), LOWER(), and PROPER() functions are used to change the case of text.
TRIM() removes leading/trailing spaces and extra spaces between words.
CLEAN() removes non-printing characters, which might appear as small square boxes, and can also remove manual line breaks within cells. These functions are typically used in a “helper column” next to the original data. Multiple functions can be combined in a single formula in a helper column to perform several cleaning steps at once, saving time.
Using Paste Special to Convert Formulas to Values When cleaning data using formulas in a helper column, the formulas refer to the original data column. If the original column is simply deleted, the helper column will result in #REF! errors because the references are broken. To avoid this, the cleaned data in the helper column must be converted from formulas to static values. This is achieved by copying the helper column and then using the “Paste Special” > “Paste Values” option to paste only the resulting values over the original column (or a new location), discarding the underlying formulas. Once the values are pasted, the helper column can be safely deleted.
Splitting and Combining Data Sometimes data is combined in a single cell that needs to be separated (e.g., “Order Date Order ID”), or data in separate cells needs to be combined.
“Text to Columns” is a wizard that splits a single column of text into multiple columns based on a specified delimiter (like a comma, space, or other character) or a fixed width.
“Flash Fill” is a faster tool (available since Excel 2013) that can split or combine data by recognizing patterns based on one or two examples provided by the user. It can be accessed via a button on the Data tab or the Ctrl + E shortcut.
The CONCAT() function (or CONCATENATE() in older versions) joins text from multiple cells. Custom text or delimiters can be included in the joined result by enclosing them in quote marks within the function.
Finding and Replacing Data To standardize inconsistent text entries (e.g., replacing “Democratic Republic of the Congo” with “DRC” or “United States of America” with “USA”), you can use the “Find and Replace” dialog box (Ctrl + F, then select the Replace tab). You specify what to find and what to replace it with, choosing whether or not to match the case. The SUBSTITUTE() formula can also perform find and replace using a formula, requiring the “Paste Special” > “Paste Values” trick afterward.
Running a Spell Check Spelling errors can cause problems in pivot tables because the table will treat variations of the same word as completely separate items. Running a spell check (Review tab > Proofing group, or F7) helps ensure consistency in text entries. You can choose the dictionary language and add correctly spelled but unrecognized words to the dictionary.
Once data is cleaned, it is highly recommended to put it into an Excel Table before creating a pivot table. Excel Tables offer several advantages, including automatic formatting, built-in filter and sort buttons, and importantly, auto-expand capabilities. This means that if new data is added to the table, it is automatically included in the data source for any associated pivot tables or charts, which can then be updated by simply clicking the refresh button. Data can be converted into an Excel Table using the “Format as Table” option on the Home tab or the Ctrl + T keyboard shortcut. Tables can be given meaningful names for easier identification.
In summary, thorough data cleaning is essential for accurate and effective analysis using pivot tables, addressing issues like inconsistencies, errors, and formatting problems through various Excel tools and functions.
Excel Data Analysis with Pivot Tables
Based on the sources, data analysis is the process of summarizing large amounts of data to make sense of them. In a data-driven world where information is collected from various sources, simply looking at a large spreadsheet might not highlight key metrics, issues, successes, failures, or trends. Data analysis aims to take this data and present it in a way that allows for clearer understanding and better business decisions.
Excel provides powerful tools for data analysis, particularly Pivot Tables.
Key aspects of Data Analysis discussed in the sources:
The Role of Pivot Tables Pivot tables are described as an interactive and dynamic way to quickly summarize large amounts of data. Unlike static Excel tables where analysis is limited primarily to sorting and filtering, pivot tables allow you to pivot fields around and view data in all different ways. This dynamism makes it much more efficient to analyze data compared to manually using filters. Pivot tables help analyze large datasets in a clear and effective way. They facilitate asking questions about the data, such as finding top performers or seeing counts of high-priority orders. Pivot charts can be created from pivot table data to offer visual analysis options, as most people find it easier to analyze and interpret data visually. This can extend to creating interactive dashboards with filters for deeper analysis.
The Critical Need for Data Cleaning Before Analysis A central theme is that data cleaning is essential prior to analyzing data with a pivot table. Skipping this step, especially when importing data from external sources or databases, can lead to inaccurate analysis. Data doesn’t always import in the desired format, and inconsistencies or errors can cause problems for pivot tables. Cleaning ensures the data is tidied up, consistent, correctly formatted, and presented in a way that allows the pivot table to easily analyze it and produce accurate results. The sources highlight cleaning steps like removing blank rows, removing duplicate entries, clearing unwanted formatting, applying desired formatting, tidying text using formulas (case, spaces), splitting and combining data, finding and replacing data, and running a spell check. All these steps contribute to a “clean looking data set ready for analysis”.
Structuring Analysis with Pivot Table Fields To perform analysis with a pivot table, you use the Pivot Table Fields pane, which lists the column headings from your source data. These fields are dragged into four areas: Filters, Columns, Rows, and Values. These areas determine the layout of the pivot table and control the type of analysis being done. Placing fields in different areas changes how the data is summarized and viewed.
Aggregating Data for Analysis The Values area is typically where numeric fields are placed. By default, Excel usually performs a sum calculation for numeric values and a count for text or date fields dropped into this area. However, you can change how the data is summarized using the Value Field Settings. This allows you to choose from various aggregation methods, including Sum, Count, Average, Max, Min, Product, and more. You can even combine different aggregation methods (like sum and average) for the same data by dragging the field into the Values area multiple times and setting a different calculation for each instance. This ability to calculate averages, mins, or maxes “on the fly” expands the analysis beyond what was present in the raw source data.
Grouping Data for Deeper Analysis Grouping data is another way to analyze it. Excel automatically groups certain fields, like dates, into categories like years, quarters, and months. This allows you to see the data summarized at different levels (e.g., total profit by year, then by month within each year). You can also create your own custom groups for non-date fields to categorize data according to your analysis needs (e.g., grouping different item types into “food and drink” or “other”). Grouping allows for analyzing data in “multiple dimensions” by adding more fields to the Rows or Columns areas.
Handling Empty Cells and Layout How empty cells are displayed affects the accuracy of analysis, especially in pivot charts. Replacing blank cells with zeros in the Pivot Table Options ensures that items with no data are still represented, showing a zero value rather than being excluded from the analysis or charts. Additionally, the report layout options (compact, outline, tabular) and the choice to display or hide subtotals and grand totals affect the readability and presentation of the analyzed results.
In summary, data analysis in Excel, as presented in the sources, relies heavily on the dynamic capabilities of Pivot Tables, which allow for summarizing, slicing, dicing, and aggregating data in various ways. However, the foundation of accurate analysis is thorough data cleaning, ensuring the data is reliable and free from inconsistencies before being used in a pivot table. Using Excel Tables is also recommended as it makes managing and updating the data source for analysis more efficient.
Grouping Data in Excel Pivot Tables
Based on the sources, grouping data in Excel pivot tables is a way to summarize data by multiple fields and organize the display of that data. It allows you to analyze information at different levels or categorize data according to specific needs.
Here are key aspects of grouping data discussed in the sources:
Automatic Grouping Excel will automatically apply grouping when you summarize data by more than one field in areas like the Rows or Columns of a pivot table.
Date Grouping A common example of automatic grouping occurs when you drag a date field into an area like Rows. Excel looks at your source data and automatically groups the dates by categories such as years, quarters, and months. These levels appear as separate fields (e.g., “Years,” “Quarters,” “Order Date”) in the Pivot Table Fields pane. You can then use these fields independently to summarize data at different granularities, for instance, viewing total profit by year, and then expanding to see the breakdown by month within each year. If you don’t need a specific level, like quarters, you can simply remove that field from the Rows area. The “Group Field” option on the Pivot Table Analyze ribbon shows the date ranges and the levels (months, quarters, years) that Excel has pulled from the data.
Custom Grouping You can create your own custom groups for fields that are not dates. This allows you to categorize data based on your analytical requirements. For example, you could select several ‘item type’ categories like ‘baby food’, ‘beverages’, ‘cereal’, ‘fruits’, ‘meat’, ‘snacks’, and ‘vegetables’ and group them together under a new name like “Food and Drink”. The remaining items could be grouped under “Other”.
Creating Custom Groups To create a custom group, you select the specific items in the pivot table report that you want to include in the group. Then, you go to the Pivot Table Analyze ribbon and select the Group Selection button. Excel will create a new group (initially named generically, like “Group1”). You can rename this group directly in the pivot table report. Excel also creates a new field in the Pivot Table Fields pane corresponding to this custom group (e.g., “Item Type2” if you grouped based on ‘Item Type’). It is recommended to rename this new field as well (e.g., “Food and Drink”) for consistency. This can be done by clicking the drop-down arrow for the field in the Rows area and selecting “Field Settings,” or by right-clicking the field name in the Rows area and selecting “Field Settings”.
Expanding and Collapsing Groups When grouping is applied, items in the pivot table report often display with little plus and minus symbols next to them. These symbols allow you to collapse or expand the details within a group, letting you focus on summary levels or drill down into specifics. You can toggle the display of these buttons on or off from the Pivot Table Analyze ribbon in the Show group.
Multi-Dimensional Analysis Grouping contributes significantly to creating multi-dimensional pivot tables. By adding more fields and grouping them in the Rows or Columns areas, you can analyze your data by multiple factors simultaneously (e.g., analyzing profit by region, item type, and sales channel).
Ungrouping Data If you need to revert a group, you can select an item within the group in the pivot table and click the Ungroup button on the Pivot Table Analyze ribbon.
Grouping and Layout The report layout options can interact with grouping. For example, the Compact Form layout maintains the grouping structure. Adding blank rows using the “Blank Rows” option on the Design ribbon will insert a blank line after each grouped item, which can help emphasize groups and improve readability.
Excel Number Formatting Explained
Based on the sources and our conversation, number formatting is a crucial aspect of data cleaning and analysis in Excel, particularly to improve readability and consistency of your data. It involves ensuring that values in your cells are displayed in a way that accurately reflects their type and makes them easy to interpret.
Here’s a breakdown of the key points about number formatting discussed:
Purpose of Number Formatting:
To make your data a lot easier to read.
To ensure consistency in how numbers are displayed, such as the number of decimal places and the presence of currency symbols.
A currency symbol, for example, always makes monetary values a lot easier to read.
Applying Formatting in Standard Worksheets:
Formatting is applied using the Home tab in the Number group.
A drop-down menu provides common formatting options (e.g., General, Number, Currency, Accounting, Short Date, Long Date).
You can access more detailed formatting options by clicking “More Number Formats” at the bottom of the drop-down or by using the Ctrl+1 keyboard shortcut to open the “Format Cells” dialog box.
The appropriate format depends on the type of information in the column.
Examples discussed include:
Applying Text formatting to columns containing text.
Applying Date formatting to columns containing dates. Excel stores dates as numbers (days since January 1, 1900), and date formatting is needed to display them as calendar dates. If not formatted as a date, you might see the underlying numeric value. “Short date” and “long date” are common options. Custom date formats are also available via “More number formats” but are considered advanced.
Applying Number formatting to columns like “Units Sold,” where you might need to control the number of decimal places (e.g., reducing to zero using the Increase/Decrease Decimal buttons or “Format Cells”).
Applying Currency or Accounting formatting to monetary columns like “Unit Price,” “Total Revenue,” or “Total Profit” to add a currency symbol and control decimal places. The key difference is that Accounting format aligns the currency symbols and decimal points in a column, which is often considered easier to read, especially in long lists of numbers, whereas Currency format places the symbol right next to the value and doesn’t align decimals. The sources suggest Accounting format is frequently used.
Formatting and Data Cleaning Steps:
When initially cleaning data, steps like using “Clear Formats” can remove all formatting, including desirable number formatting. Therefore, you might need to reapply the correct formatting after this step.
Helper columns created for text cleaning formulas (like UPPER, TRIM, CLEAN, SUBSTITUTE) might inherit the formatting of surrounding columns, sometimes defaulting to “Text”. To see formula results correctly, these columns might need to be changed back to “General” format before applying the formula.
Identifying numbers stored as text is important. Indicators include the number being aligned to the left side of the cell and a little green triangle in the corner. You can convert these using the warning symbol option “Convert to Number” or by using the VALUE formula.
Number Formatting in Pivot Tables:
When you build a pivot table, the numbers in the values area are initially unformatted and inconsistent.
It is NOT recommended to apply number formatting directly to the cells in a pivot table using the Home ribbon. This is because pivot tables are dynamic; the fields and their locations can change when you rearrange or “pivot” the data. Formatting applied to a static cell will not move with the number it was applied to if the layout changes.
The correct method for applying number formatting in a pivot table is to apply it to the number itself, which ensures it moves with the data regardless of the layout.
This is done by right-clicking on a number within the pivot table and selecting “Number Format”.
Alternatively, you can access this through the Value Field Settings for the specific field in the Values area, and then clicking the “Number Format” button at the bottom.
Both methods open the familiar “Format Cells” dialog box, allowing you to choose formats like Accounting or Currency.
Custom number formatting is also available through this pivot table method.
If you configure your pivot table to show zero for empty cells, these zeros will also display with the number formatting applied to that values field (e.g., showing “$ -“).
In essence, applying consistent and appropriate number formatting is a vital step, first during general data cleaning and preparation, and then specifically within pivot tables using the recommended methods to maintain accuracy and readability as you analyze your data.
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This extensive text provides a detailed tutorial on using Excel and Power BI for data analysis, emphasizing how to convert raw data into actionable insights. It covers fundamental techniques like sorting, filtering, and using Flash Fill in Excel, then moves to more advanced tools such as Pivot Tables for summarizing data and Power Query for importing, cleaning, and transforming data. The document highlights how Power Query is particularly useful for handling data from external sources and combining multiple files, positioning it as a significant advancement in data manipulation capabilities. It then introduces Power Pivot and the concept of a data model to manage relationships between multiple tables and handle large datasets more efficiently, contrasting it with the limitations of relying solely on worksheet formulas like XLOOKUP. Finally, the text explores Power BI Desktop and Power BI Online for creating interactive visualizations and reports, demonstrating how to import data, build data models, write DAX formulas, and share insights, showcasing the power of these tools for analyzing large volumes of data and creating dynamic dashboards.
Excel and Power BI Data Analysis Tools
Based on the sources, Data Analysis is defined as the process of converting raw data into useful information. The purpose of this conversion is to gain insight and make decisions. The source mentions that there are various synonyms for data analysis, including data analytics, analytics, business intelligence, and data science.
The sources highlight that almost every tool used for data analysis requires a proper data set. A proper data set generally includes a field name at the top and empty cells all the way around.
Several tools are presented in the sources as being used for data analysis in Excel and Power BI:
Sort and Filter: These are fundamental tools available in Excel tables, Pivot Tables, Power Query, Power Pivot, and Power BI Desktop. Sorting organizes records in a table, for example, from smallest to largest (a to z) or largest to smallest (z to a). You can sort by one column or multiple columns. Filtering shows only certain records based on one or more conditions. Filters can use various logical tests like AND, OR, or BETWEEN. A particularly helpful use of filtering in the Excel worksheet is to extract specific records. Filtering can also be data type specific, offering different options for dates, text, and numbers. When filtering, the records that match the criteria are shown, and the rest are hidden.
Flash Fill: This is a one-time, simple data cleaning tool in Excel. It can be used if there’s a consistent pattern in the data. You provide an example by typing the desired output next to the original data, and then Flash Fill attempts to apply the pattern to the rest of the column. It’s not recommended for tasks that need to be repeated or refreshed with new data; for those, formulas or Power Query are suggested.
Pivot Table: This is an amazing tool to build reports and charts. It’s particularly useful for summarizing data, such as survey results, showing counts and percentages. Standard pivot tables are suitable for small data sets within Excel and simple calculations like count and percent of total. They allow you to drag fields to areas like Rows and Values to create unique lists and calculations. Pivot tables can connect to data from various sources, including tables or ranges in the worksheet, external data sources, data models in Power Pivot, and data models in Power BI online. A key point is that with standard pivot tables, you have to repeatedly add number formatting to fields.
Power Query: Described as the greatest Excel tool invented since the pivot table. It excels at importing data from outside of Excel (like text files, other Excel files, databases, websites), cleaning data (e.g., splitting columns, extracting information), transforming data (e.g., removing columns, calculating new columns, combining tables), and loading data to the Excel worksheet, the pivot table cache, or the Power Pivot data model. Power Query is also present in Power BI Desktop, functioning the same way. Power Query memorizes the steps applied during importing, cleaning, and transforming, allowing for easy refreshing of data. These steps form the foundation of a Power Query query. Power Query has a functional language called M code, which is used for data mashup.
XLOOKUP function: A worksheet formula that can be used in data analysis, particularly when you need to look up values from one table and bring them into another column in your main table. It’s presented as a modern replacement for older lookup functions like VLOOKUP. XLOOKUP is appropriate when the data is already in the Excel worksheet, the data set is not excessively large (e.g., 43,000 rows is considered not a lot), and the solution can be created using standard pivot tables and Excel charts.
Power Pivot: An Excel feature that creates data model pivot tables. It allows for creating relationships between related tables, which helps avoid using many lookup formulas like XLOOKUP. Power Pivot enables the use of more than one table in a pivot table report. It is also capable of importing large amounts of data into a behind-the-scenes columnar database that compresses the data and can hold millions of rows. Power Pivot allows for the creation of reusable, formattable formulas called DAX measures, which are used in data model pivot tables. In Power Pivot, DAX measures are built in the measure grid below the fact table.
DAX Formulas: Data Analysis Expressions, a function-based formula language used in Power Pivot and Power BI Desktop. There are two types: DAX measures (reusable formulas dragged into data model pivot tables) and DAX calculated columns (formulas that add a new column to a table). Dax measures calculate based on the conditions or criteria (filter context) in the pivot table. This filter context makes calculations efficient, especially with large data sets. In Power Pivot, the assignment operator for DAX measures is a colon followed by an equal sign. In Power BI Desktop, it’s just an equal sign.
Data Model: Created in Power Pivot or Power BI Desktop, it involves multiple tables with relationships defined between them. Dimension or lookup tables, which contain unique lists (the “one” side of a relationship) and attributes, are related to fact tables, which contain repeating values (the “many” side of a relationship). Creating relationships in the data model replaces the need for lookup formulas like XLOOKUP and allows dragging and dropping fields from any related table into reports. The data model is stored in a behind-the-scenes columnar database.
Power BI Desktop: A free Microsoft tool designed for creating data models, visualizations, and reports. It contains the same Power Query and Power Pivot tools found in Excel. Power BI has a wider variety of visuals and reporting tools compared to Excel, and its visuals are interactive. Data models created in Excel Power Pivot can be imported into Power BI Desktop.
Power BI Online: Requires a license and allows users to upload Power BI Desktop files or Excel files with Power Pivot data models. This makes reports, visuals, dashboards, and data models shareable and universally available to assigned groups, serving as a single source of truth for data. Dashboards in Power BI Online are specific locations where you can pin important information (tables, charts, visuals, etc.) from various reports and workbooks for easy presentation and sharing. Dashboards should present information needed for good decisions.
The sources provide examples illustrating these tools:
Example 1 shows using Sort, Filter, and Flash Fill.
Example 4 (from video 3) shows summarizing survey results with a Pivot Table.
Example 5 demonstrates using Power Query to import, transform, and refresh data from a website CSV file.
Example 6 shows using Power Query to combine multiple files into one table, calculate a new column, and load it to the Pivot Table cache.
Example 7 illustrates solving a data modeling problem (needing data from multiple tables) using worksheet formulas like XLOOKUP to add helper columns before creating standard Pivot Table reports and charts. This approach is suitable for smaller data sets.
Example 8 shows solving the same data modeling problem as Example 7 but using Power Query to import data from an external Excel file and load it directly to the Power Pivot data model. This approach is better for larger data sets and allows creating relationships between tables and reusable DAX measures. It also introduces concepts like the one-to-many relationship and hiding fields in the data model.
Example 9 uses Power BI Desktop for the same data source as Example 8, demonstrating importing data with Power Query, loading it to the data model in Power BI Desktop, and creating interactive visuals and dashboards. This approach is preferred for interactive and shareable visuals.
Example 10 shows importing 7 million rows of data from an SQL database into Power BI Desktop using Power Query. It discusses the efficiency of the columnar database for handling big data and creating calculated columns and measures using DAX formulas (including the concept of iterator functions like SUMX) to calculate values like revenue and cost. It also covers creating a date table using DAX and marking it as a date table.
In essence, data analysis, as presented in the sources, is about transforming data for insight and decision-making using a range of tools in Excel and Power BI, from basic sorting and filtering to advanced data modeling with Power Query, Power Pivot, and Power BI Desktop, often involving calculated formulas using XLOOKUP or DAX. The choice of tool often depends on the size of the data, the source of the data, the complexity of transformations needed, and the desired output (e.g., simple report vs. interactive dashboard).
Mastering Power Query: Data Transformation in Excel and Power BI
Based on the sources, Power Query is highlighted as a fundamental and highly valuable tool in the process of Data Analysis, which involves converting raw data into useful information to gain insight and make decisions. It is described as the greatest Excel tool invented since the pivot table.
The primary reason for Power Query’s significance is that while tools like the Pivot Table were amazing for building reports and charts, there was a missing piece for importing data into Excel and fixing or cleaning bad data. Power Query fills this gap.
Power Query is not exclusive to Excel; it is also available in Power BI Desktop and functions the same way in both applications.
Key Capabilities of Power Query:
Importing Data: Power Query excels at bringing data into your analysis environment from various sources outside of Excel. These sources include:
Text files (like CSV, TXT)
Other Excel files
Databases (like SQL databases)
Websites
Folders (to combine multiple files)
Many other data sources
Cleaning Data: It provides tools to fix issues or extract specific parts of your data. Examples include:
Splitting columns (e.g., splitting first and last name)
Extracting information (e.g., extracting a date from a date time field)
Handling delimiters (e.g., tab delimiters in text files)
Transforming Data: Power Query allows you to reshape and modify data before loading it. Examples include:
Removing unwanted columns
Calculating new columns (e.g., multiplying Units by Price to get Sales)
Combining multiple tables into one table
Changing data types
Filtering data (e.g., filtering files by extension in a folder import)
Transforming text (e.g., changing text case to lowercase for filtering)
Removing relational columns automatically added during database import
The Power Query Editor:
Transformations are performed in the Power Query Editor, which is a separate window on top of the Excel or Power BI Desktop window. The Editor provides a preview of the data.
Applied Steps: One of the most important features is the recording of Applied Steps. Power Query memorizes every step applied during importing, cleaning, and transforming. These steps are rerun automatically when the data is refreshed. You can view the data preview at each step of the process.
M Code: Behind the user interface and applied steps is a functional language called M code, which Microsoft calls the data mashup language. While Power Query writes this code automatically when you use the user interface, you can view it in the formula bar or the Advanced Editor, and even write your own M code. M code is case-sensitive, which is different from the Excel worksheet.
Loading Data:
After cleaning and transforming data in the Power Query Editor, the results need to be loaded. The loading destination depends on whether you are using Excel or Power BI Desktop and the purpose of the analysis.
In Excel:
The default is to load the data as an Excel Table on a new worksheet.
Using Close & Load To, you can control the destination:
Load as a Table to a specified worksheet location.
Load to the Pivot Table Cache (for creating Pivot Tables directly from the query output without first putting it on a worksheet).
Load to the Power Pivot Data Model (used when working with multiple tables and relationships).
Only Create a Connection: This option stores the query definition in the Power Query Editor but does not load the data anywhere visible in the worksheet. This is the crucial option when importing data for the Data Model, especially when combining it with the Add this data to the Data Model option. It prevents duplicating the data source by putting it in a worksheet table and the data model.
In Power BI Desktop:
The Power Query Editor has a Close & Apply button. This closes the editor, applies the steps, and loads the data only to the columnar database in the Data Model. There is no option to load directly to a worksheet as in Excel, as the primary destination is always the data model for creating visuals and reports.
Benefits and Use Cases:
Automation and Refreshing: Because Power Query memorizes the steps, when the source data updates (e.g., a new monthly file is added to a folder, or a website CSV changes), you can simply click Refresh, and Power Query will re-import, re-clean, re-transform, and reload the data automatically. This eliminates repetitive manual tasks.
Handling Different Data Structures: Power Query is adept at handling various delimiters (comma, tab) and structures (single tables, multiple files in a folder).
Data Modeling: Power Query is essential for importing data from external sources into the Power Pivot or Power BI Data Model. This allows for building relationships between tables and avoiding the need for numerous lookup formulas like XLOOKUP in the worksheet, especially when dealing with data from multiple tables.
Big Data: Power Query is used to import large amounts of data (e.g., 7 million rows from an SQL database) into the compressed columnar database used by Power Pivot and Power BI Desktop.
Examples from Sources:
Example 5: Power Query is used to import, transform, and load data from a website CSV file to an Excel worksheet table that can then be easily refreshed.
Example 6: Power Query imports and combines data from multiple text files in a folder into a single table, adds a calculated ‘Sales’ column, and loads it directly to the Pivot Table cache, ready for reporting and charting.
Example 8: Power Query imports data from tables within an external Excel file and loads them directly to the Power Pivot Data Model using the “Only Create Connection” and “Add to the Data Model” options, preparing the data for creating relationships and data model pivot tables.
Example 10: Power Query connects to an online SQL database with 7 million rows, imports selected tables using credentials, checks and changes data types, removes unnecessary columns in the Power Query Editor, and loads the data to the Power BI Desktop Data Model.
In summary, Power Query is a robust, user-friendly, and essential tool for modern data analysis in both Excel and Power BI Desktop, providing powerful capabilities for connecting to, cleaning, and transforming data from a wide range of sources, automating repetitive data preparation tasks, and enabling advanced data modeling.
The Art of Excel Pivot Tables
Based on the sources, Pivot Tables are a cornerstone tool in data analysis, designed primarily for building reports and charts. They are considered one of the most significant tools invented in Excel, with Power Query being highlighted as the greatest since the pivot table.
Here’s a discussion of Pivot Tables based on the information provided:
Core Purpose and Functionality Pivot Tables allow you to convert raw data into useful information by summarizing and organizing records in a table. They provide an interactive way to analyze data by dragging fields into different areas (like Rows, Columns, and Values) in the Pivot Table Fields task pane. They use the same sorting and filtering conventions as Excel tables.
Standard Pivot Tables (Working with One Table) This type of pivot table is used when you have your data in a single table, such as an Excel worksheet table or a “flat table” created by adding lookup columns using functions like XLOOKUP. They perform calculations using built-in options like “Summarize Values By” (e.g., Count, Sum) and “Show Values As” (e.g., Percent of Column Total, Difference From Previous).
They are appropriate for data already in Excel, when there isn’t a lot of data (e.g., 43,000 rows is considered manageable, but 100,000-500,000 rows might slow down).
A limitation is that if you use the same number field in multiple reports, you have to reapply number formatting each time.
Standard pivot tables can automatically group dates into months and years.
Data sources can be a table or range directly in the worksheet, or data loaded into the Pivot Table Cache from Power Query. You can access data directly from the Pivot Table Cache using the “from external data source” option.
Data Model Pivot Tables (Working with Multiple Tables) Introduced with tools like Power Pivot and Power BI Desktop, Data Model Pivot Tables work with multiple tables loaded into a behind-the-scenes columnar database called the Data Model.
Relationships: Instead of using lookup formulas like XLOOKUP in the worksheet, relationships (often one-to-many) are created between related tables in the Data Model (e.g., linking a fact table with sales data to dimension tables like products, sales reps, or dates). This allows you to drag and drop fields from any related table into the pivot table report.
DAX Measures: Calculations are performed using reusable DAX measures that you create. A significant advantage is that you can include number formatting in the DAX measure, and this formatting will apply automatically whenever the measure is used in a pivot table.
Filter Context: DAX measures calculate efficiently using a concept called Filter Context, where the measure automatically filters the data based on the conditions in the pivot table (rows, columns, filters) before performing the calculation.
Handling Big Data: The Data Model, using a columnar database, can handle importing and analyzing large amounts of data (millions of rows), which is much better than handling such volumes directly in an Excel worksheet.
Data Loading: Data is typically loaded into the Data Model using Power Query, often selecting the “Only Create a Connection” and “Add this data to the Data Model” options to avoid duplicating data in the worksheet.
Date Tables: Unlike standard pivot tables, Data Model pivot tables do not automatically group dates. A dedicated date dimension table with a unique list of dates and attributes (like month, year) is required and linked via a relationship. The date table must be marked as a date table in the Data Model to function correctly.
Implicit vs. Explicit Measures: It is recommended to use explicit (user-created) DAX measures rather than implicit measures, which are automatically created when you drag a raw number field into a Data Model pivot table. Implicit measures are hidden, read-only, cannot be formatted or reused, and do not transfer when connecting live to data models in Power BI Desktop.
You can hide unnecessary fields in the Data Model so they don’t appear in the pivot table field list, making it less cluttered.
Integration with Power Query Power Query is essential for getting data from external sources and cleaning/transforming it before it is used in a pivot table. Power Query output can be loaded directly to the Pivot Table Cache for standard pivot tables or to the Data Model for data model pivot tables. This eliminates repetitive manual data preparation steps, as refreshing the query automatically updates the pivot table report.
Integration with Power Pivot and Power BI Desktop Power Pivot in Excel and Power BI Desktop share the core Data Model technology, enabling the creation of Data Model Pivot Tables. Power BI Desktop has a visual called a “Matrix” which is similar to an Excel pivot table and is used for cross-tab reports from the Data Model. You can also connect Excel pivot tables directly to data models stored online in Power BI Service.
In summary, Pivot Tables are powerful tools for data summarization and reporting, evolving from the standard type working with single tables to the more advanced Data Model type capable of handling multiple tables and large datasets using DAX formulas and relationships, often populated and managed with the help of Power Query and the Data Model environment.
Understanding the Data Model for Power Tools
Based on the sources and our previous discussion about Pivot Tables, the Data Model is a fundamental component used in conjunction with Data Model Pivot Tables and tools like Power Pivot and Power BI Desktop.
Here’s a discussion of the Data Model:
What it is: The Data Model is a behind-the-scenes columnar database that stores and compresses data. It is the underlying structure used by Power Pivot in Excel and Power BI Desktop.
Purpose and Benefits:
Handles Large Datasets: A key advantage of the Data Model is its ability to import and analyze large amounts of data (millions of rows) much more effectively than an Excel worksheet. The columnar database design helps compress the data, making it possible to work with volumes that would overwhelm Excel’s row limit or performance.
Works with Multiple Tables: The Data Model allows you to bring data from multiple tables together for analysis in a single pivot table report.
Relationships: Instead of using lookup formulas like XLOOKUP to combine data in the worksheet, you create relationships (typically one-to-many) between related tables directly in the Data Model. This linking of tables (like a fact table with sales data and dimension tables with product or sales rep details) is crucial for working with data spread across different sources. These relationships replace the need for adding helper columns with lookup formulas in your source data.
DAX Calculations: Calculations are performed using reusable formulas called DAX measures. These measures are built in the Data Model and can be easily dragged into a pivot table. DAX measures calculate efficiently using Filter Context, meaning the formula automatically considers the filters and conditions applied in the pivot table or visual (like rows, columns, or slicers) before performing the calculation.
Reusable Formatting: A significant advantage of DAX measures is that number formatting can be applied directly to the measure itself, so it only needs to be set once and will apply automatically whenever the measure is used in any report. This contrasts with standard pivot tables where number formatting must be reapplied each time the same field is used in a different report.
Organized Reporting: You can hide fields in the Data Model that you don’t intend to use in your pivot table reports (like foreign keys or raw number columns that will be used in measures), making the pivot table field list less cluttered.
How Data is Loaded: Data is typically loaded into the Data Model using Power Query. When loading Power Query output, you often select the “Only Create a Connection” option and then “Add this data to the Data Model”. This prevents the data from being loaded into the Excel worksheet and the Data Model, avoiding duplication and potential performance issues. Data can come from various sources, including Excel files containing tables or external databases.
Working with Dates: Unlike standard pivot tables that can auto-group dates, Data Model pivot tables require a dedicated date dimension table. This table contains a unique list of dates and related attributes like month name, year, etc.. This date table needs to be linked to the fact table using a relationship and marked as a date table in the Data Model tools to function correctly and prevent issues like inefficient date grouping or the creation of hidden date tables.
Implicit vs. Explicit Measures: When using a Data Model, it is strongly recommended to create your own DAX measures (explicit measures) rather than relying on the hidden implicit measures automatically created when dragging raw number fields into a pivot table. Implicit measures have limitations: they are hidden, read-only, cannot be formatted or renamed easily, and do not transfer when connecting live to data models in Power BI Service. Explicit measures offer control, reusability, and formatting.
Interface:
In Excel’s Power Pivot window (which opens when you manage the data model), there’s a Diagram View where you visualize tables and create relationships by dragging fields. There’s also a Data View to preview the data in each table and a Measure Grid at the bottom of the fact table to write DAX measures.
In Power BI Desktop, the corresponding views are Model View (similar to Diagram View) and Data View. Measures are typically created by right-clicking the table in the fields list or using buttons in the table/measure tools.
Integration: Data Models built with Power Pivot in Excel can be imported into Power BI Desktop. Both Excel Data Models and Power BI Desktop Data Models can be uploaded to Power BI Online (Power BI Service), making them available as a single source of truth for connecting to from other Excel or Power BI Desktop files.
In essence, the Data Model is the powerful engine behind advanced data analysis in Excel and Power BI, enabling efficient handling of large, multi-table datasets through relationships and flexible calculations via DAX.
Introduction to Power BI
Based on the sources and our conversation history, let’s discuss Power BI.
Power BI Desktop is a free Microsoft download that serves as a tool for data analysis, creating reports, and designing interactive visuals. It shares many core functionalities with Excel’s Power Pivot and Power Query. Power BI is specifically designed to offer more varied visuals and reporting tools and better shareability compared to Excel.
Here are some key aspects of Power BI:
Core Components and Workflow: Power BI Desktop integrates several tools:
Power Query: This is the tool used to import data from external sources (like databases, web files, other Excel files) and then clean and transform it. The Power Query Editor looks and functions very similarly to the one in Excel. The cleaned data is then loaded into the Data Model.
Data Model: Like Power Pivot in Excel, Power BI Desktop utilizes a behind-the-scenes columnar database called the Data Model to store and compress data. This model is crucial for handling large amounts of data, potentially millions of rows, much more effectively than a standard Excel worksheet. Within the Data Model, you create relationships between related tables (like fact and dimension tables) to link them for analysis, avoiding the need for lookup formulas in the source data. The Data Model in Power BI Desktop looks almost exactly the same as in Power Pivot. Power BI Desktop has a Model View (similar to Power Pivot’s Diagram View) for visualizing tables and creating relationships, and a Data View (similar to Power Pivot’s Data View) for previewing table data.
DAX Formulas: Calculations within the Data Model are performed using Data Analysis Expressions (DAX). You create reusable DAX measures to perform calculations like Sum or Average. A key advantage of DAX measures is that number formatting can be applied directly to the measure, and this formatting will be automatically applied whenever the measure is used in a report or visual. DAX measures calculate efficiently using Filter Context, meaning they automatically consider the filters applied by the visual (like rows, columns, slicers) before performing the calculation. While Power Pivot focuses on measures, Power BI Desktop also allows creating DAX calculated columns and entire DAX tables. It is strongly recommended to use explicit (user-created) measures rather than implicit measures (automatically created by dragging raw number fields), as implicit measures have limitations such as being hidden, read-only, and not transferring to Power BI Service when connecting live. Fields that are not needed for reporting (like foreign keys or raw number columns used in measures) can be hidden in the Data Model to keep the fields list cleaner in the reporting interface. In Power BI Desktop, hidden fields are indicated by an eyeball icon with a line through it.
Visualizations and Reporting: Reports are built in the Report View, which is comparable to an Excel worksheet where you might place pivot tables and charts. Power BI offers a wide array of visualizations. Examples include line charts, clustered column charts, a Matrix visual (similar to an Excel pivot table for cross-tab reports), slicers, cards, and maps. A defining feature is the interactivity of these visuals; clicking on one visual can filter or highlight data in other visuals on the page. You can control how visuals interact (filter, highlight, or none). Tooltips can be customized to show multiple measures when hovering over data points.
Power BI Online (Service): This is the cloud-based component that requires a license and enables sharing and collaboration.
You can publish Power BI Desktop files (containing the report and data model) or Excel files with Power Pivot data models to Power BI Online.
Uploaded data models appear as datasets. These datasets can serve as a single source of truth for multiple users and reports, allowing others to connect live to the data model from their own Excel or Power BI Desktop files without needing to share the original file.
Reports published from Power BI Desktop can be viewed and interacted with in Power BI Online.
Dashboards are a specific feature in Power BI Online, allowing you to pin visualizations from different reports and workbooks into a single view for easy access and sharing. Dashboards provide a high-level summary of key metrics.
Sharing is managed through workspaces, where groups of users with organizational emails can be granted access to reports, dashboards, and datasets.
Relationship with Excel Tools: Power BI Desktop and Power Pivot share the same Data Model engine. Many features learned in Power Query and Power Pivot in Excel are directly transferable to Power BI Desktop. While Excel (especially with Power Pivot) is capable of building data models and reports, Power BI Desktop is generally preferred for its superior visualization capabilities, interactivity, and the ease of sharing and collaborating via Power BI Online. Data models built in Power Pivot can be imported into Power BI Desktop.
Excel & Power BI Data Analysis Complete Class in One Video – 365 MECS 04
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The source provides an extensive transcript from a YouTube video offering a comprehensive Excel course designed for quick preparation and revision, particularly for job interviews. The tutorial begins with fundamental Excel concepts like rows, columns, and cells, before moving into essential functionalities such as data entry techniques, including the use of formatting and keyboard shortcuts. A significant portion of the content covers various data types and number formatting, followed by detailed explanations of advanced features like conditional formatting and data filtering. Finally, the video introduces a variety of critical Excel formulas, including RANK, IF, SUMIF, VLOOKUP, and XLOOKUP, alongside a promotional section about the Certified Management Accountant (CMA) certification from Zel Education.
Essential Excel Features and Formulas for Quick Reference
The Excel course content focuses on providing a quicket revision of essential features and formulas, often useful for interview preparation. The instruction emphasizes hand-picked features and formulas that are considered highly important.
The course covers content across several key categories, including basic terminology, data entry and formatting, fundamental formulas, and advanced features:
1. Excel Basics and Interface
The course begins by defining the core components of the Excel interface, noting that while often not asked in interviews, this knowledge is fundamental for using formulas.
Sheets and Zoom: Demonstrates how to add new sheets using the plus sign and how to zoom in and out of the worksheet.
Rows, Columns, and Cells: Defines columns (labeled A, B, C, etc.) and rows (labeled 1, 2, 3, etc.). A cell is the box formed by the intersection of row and column lines (e.g., C13), and understanding this relationship is crucial because formulas rely on it. The Name Box displays the name of the currently selected cell.
Data vs. Formatting: Explains the distinction between raw Data (information) and Formatting (decoration or presentation).
2. Formatting, Data Entry, and Shortcuts
A significant portion of the course involves using shortcuts and formatting tools to improve data presentation and efficiency.
Formatting Options: Formatting features are primarily found in the Home tab and include the Font, Alignment, and Number groups. Professional data presentation requires using appropriate fonts (like Aptos, Arial, or Calibri) and professional colors (such as blue, black, burgundy, dark green, or grey).
Alignment: Demonstrates using Merge & Center to center headings across multiple columns.
Shortcuts: The instructor heavily emphasizes using shortcut keys, noting that the Alt key activates the on-screen keys, allowing users to follow the path (e.g., Alt + H for Home tab) to execute commands. Specific shortcuts covered include:
Merge & Center: Alt + H + M + C.
Select All Data: Ctrl + A.
All Borders: Alt + H + B + A.
Thick Border: Alt + H + B + T.
Fill Handle: Used to quickly generate series (like serial numbers).
Data Entry Form Hack: Provides a hack to quickly enter data using a form interface via the shortcut Alt + D + O.
Format Painter: Allows copying the formatting from one cell or range to another quickly.
3. Number Formats and Data Types
The content details how different types of data are handled in Excel, which is important for understanding calculations and presentation.
Data Types: Discusses common formats, including Numbers (whole and decimal), Text, Percentage, Currency, and Accounting formats.
Observation Tip: Text typically aligns to the left of the cell, while numbers align to the right.
Date and Time: Covers Short Date (e.g., 16/9/2025) and Long Date (e.g., 16 September 2025). The course extensively explains Custom Date Formatting, where date components are represented by D (Day), M (Month), and Y (Year). The number of times the letter is repeated dictates the format (e.g., four D’s for the full day name).
Decimal Management: Shows how to use the Increase/Decrease Decimal options.
Fixing Errors: Explains that the “######” error indicates that the cell width is too small to display the number, which can be fixed by double-tapping between column headers.
Date Shortcut: Provides the shortcut Control + Semicolon to insert the current date.
4. Data Arrangement and Visualization Features
The course introduces powerful features for analyzing and manipulating data sets.
Conditional Formatting and Filtering
The video contrasts Conditional Formatting and Filtering, noting they share similar options.
Conditional Formatting: Applying formatting (colors, fonts, etc.) based on defined rules or conditions (e.g., coloring a cell green if the value is greater than 50%). Rules demonstrated include Greater Than, Less Than, Between, Equals To, Text That Contains, Date Occurring, and identifying Duplicate Values.
Filtering: Allows users to display only a subset of the data (e.g., only data from Gujarat) by hiding non-matching entries. The shortcut for applying or removing filters is Ctrl + Shift + L.
Sorting and Series
Sorting (Arrangement): Arranging data based on Text (A to Z), Numbers (Smallest to Largest), or Dates (Oldest to Newest). It also covers Sort by Color.
Fill Series: A method to quickly generate long sequential lists (numbers or dates) by selecting the initial value, navigating to Fill > Series (Shortcut: Alt + H + F + I + S), specifying the column, and setting a stop value (e.g., 10,000).
Find and Replace
The Find function (Shortcut: Ctrl + F) allows searching for specific text within the current sheet or the entire workbook.
The Replace function is used to automatically substitute found text with new text across the selected area or workbook.
Advanced Features
Flash Fill: Available after the 2019 version, Flash Fill recognizes patterns based on a single example provided by the user (e.g., combining names) and applies that pattern to the entire column. The shortcut is Ctrl + E.
Table Creation: Converting a data range into a Table (Shortcut: Ctrl + T) provides dynamic features, including the automatic application of formatting and formulas to new entries, and enabling the use of Slicers for easy interactive filtering. Tables can be converted back to a normal range if needed.
Pivot Table and Pivot Chart: The course shows how to create both a Pivot Table and a Pivot Chart simultaneously using the shortcut Alt + D + P. This allows users to summarize data, show values as ranks or percentages, and insert analytical tools like Slicers and Timelines.
Data Validation (Dropdowns): Demonstrated as a method to create dropdown lists within cells, either based on an existing list or by manually entering values separated by commas.
5. Essential Formulas
The course covers several mandatory formulas, grouped by category:
CategoryFormulaDescription/Key RequirementBasic MathSUMBasic addition. Shortcut is Alt + Equals.CalculationPercentageCalculated using division; requires absolute cell reference (F4) to fix the denominator (total) when applied across multiple rows.StatisticalRANKCalculates the position of a number within a set of numbers; requires fixing the reference range using F4.ConditionalSUBTOTALUsed instead of SUM when working with filtered data, as it provides accurate totals only for the visible, filtered data. (Uses function number 9 for SUM).ConditionalSUMIFCalculates the sum of values based on a single specified criterion (e.g., total sales for one specific customer).LogicalIFApplies a conditional test; returns one value if the condition is True and another if False. Output text must be in double inverted commas.TextPROPERConverts text to sentence case (proper capitalization).Text/DateTEXTUsed primarily with dates to return the day (e.g., “Tuesday”) or month name based on format codes.DateDAYSCalculates the difference in days between two dates.DateEDATECalculates a future date by adding a specified number of months to a start date.LookupVLOOKUPRetrieves information from master data; cannot be used if the lookup value is duplicated. Requires column index number.LookupXLOOKUPAn alternative to VLOOKUP (available post-2019) that requires a lookup array and a return array, simplifying the process.
Excel Data Entry Fundamentals and Formatting
Data Entry basics in Excel involve a combination of accurately inputting information (Data) and subsequently improving its presentation (Formatting).
A data entry operator’s task is to transcribe available information (such as bills) into Excel and then apply necessary formatting.
Here is a detailed discussion of the fundamental aspects of Data Entry according to the course content:
1. Fundamental Terminology and Distinction
To perform data entry effectively, it is necessary to understand the basic elements of the Excel interface:
Rows and Columns: Data is entered into cells defined by rows (labeled 1, 2, 3, etc.) and columns (labeled A, B, C, etc.).
Cell: A cell is the box formed by the intersection of row and column lines. Understanding the row and column structure is crucial because it forms the basis of the cell name (e.g., C13) and is the backbone for formulas. The Name Box displays the name of the currently selected cell.
Data vs. Formatting:Data refers to the raw information itself.
Formatting is the process of decorating or presenting the data (e.g., applying colors, fonts, borders, or alignment). Proper representation of data always requires formatting. Formatting options are generally found in the Home tab, specifically in the Font, Alignment, and Number groups.
2. Setting Up the Data Entry Table
The physical act of data entry begins with structuring the worksheet:
Headings: Data entry requires setting up appropriate headings (e.g., Serial Number, Party Name, Amount).
Merging Headings: To center a main heading (like “XYZ Limited”) across multiple columns, the Merge & Center feature is used. Using the shortcut key for this process is recommended.
Merge & Center Shortcut:Alt + H + M + C. This shortcut is derived by pressing Alt (the activation key), followed by H (for the Home tab), M (for Merge), and C (for Center).
Data Input and Series Generation: After setting up headings, entries are written sequentially. For sequential numbers (like serial numbers), the Fill Handle can be used. By selecting the first two numbers (e.g., 1 and 2) and dragging the fill handle, the rest of the numbers in the series can be automatically generated.
3. Applying Borders and Enhancing Presentation
Once the data is entered, formatting is applied for professional presentation:
Selecting Data: The shortcut Ctrl + A (Control + All) is used to select the complete dataset.
Applying Borders:All Borders: To apply borders to every cell within the selected data, the shortcut is Alt + H + B + A.
Thick Border: To apply a darker, thicker border around the outside of the data range, the shortcut is Alt + H + B + T.
Color and Font:Filling Color: The “bucket” tool is used to fill entire cells with color. When choosing colors, use darker shades for higher elements and complementary lighter shades below (e.g., dark blue contrasts well with light grey).
Font Color: The ‘A’ symbol is used to change the font color.
Professional Fonts: It is recommended to use professional, simple fonts such as Aptos, Arial, or Calibri.
Professional Colors: Recommended professional colors include blue, black, burgundy, dark green, and grey.
Bold/Italic: The Bold option can be used to make text thicker, often used for headings.
4. Advanced Data Entry Method (The Form Hack)
The course highlights a rapid data entry method using a built-in form interface:
Form Shortcut: To enter data using a form, select the data range and press Alt + D + O.
This method allows continuous entry without the need to apply macros or manual setup. New entries are generated by navigating to “New” and pressing Enter after inputting the information.
5. Data Type Observation
While entering data, a basic observation can distinguish between text and numbers:
Text vs. Numbers: Text generally aligns to the left side of the cell, whereas numbers align to the right side.
Essential Excel Formulas and Functions Reference
The course content provides a quick revision of essential formulas and functions, emphasizing those that are most important and often asked about in interviews. Formulas are considered the backbone of Excel.
The formulas and functions discussed fall into several categories, including basic mathematics, statistical calculations, conditional logic, text manipulation, date calculations, and lookup functions.
1. Basic Calculation and Statistical Formulas
These formulas handle fundamental mathematical and ranking operations:
FormulaDescriptionKey RequirementSUMCalculates basic addition.A shortcut is available: Alt + Equals (=), which automatically takes the complete range above the current cell.PercentageCalculated using division, as there is no dedicated percentage function.Requires taking the student’s total marks (numerator) divided by the grand total (denominator, e.g., 400). If the denominator cell is used, it must be fixed using F4 so that the reference does not change when the formula is copied down.RANKDetermines the position of a number within a set of numbers.Requires two inputs: the number to be checked (e.g., a student’s percentage) and the complete reference range of all numbers (e.g., all student percentages). The reference range must be fixed using F4. Users must also choose between descending or ascending order.SUBTOTALCalculates totals (like SUM) but is specifically designed for use with filtered data.Unlike the standard SUM formula, SUBTOTAL provides accurate totals only for the currently visible, filtered data. When using SUBTOTAL, you input the function number (e.g., 9 for SUM) followed by the reference range. This is necessary because the normal SUM formula will show the total of the entire dataset, even if a filter is applied.SUMIFCalculates the sum of values based on a ** single specified criterion**.Requires providing a range (where to look for the criterion), the criteria itself (what to look for, e.g., a specific party name like “Swift Nova”), and the sum range (the column containing the values to be summed). All ranges should typically be fixed using F4.2. Logical and Conditional Formulas
The IF function is considered “universal” and mandatory for any complex work involving dashboards or sheets.
FormulaDescriptionKey RequirementsIFApplies a conditional test and returns one value if the condition is True, and another if False.Logical Test: The condition to be checked (e.g., is the percentage greater than 50%?). Value if True/False: The outputs if the condition is met or not met. Any text output (like “Pass” or “Fail”) must be enclosed in double inverted commas.3. Text and Date Formulas
These formulas assist in reformatting text and performing time-based calculations:
FormulaDescriptionKey RequirementsPROPERConverts text into sentence case (proper capitalization).Requires selecting the text cell. This is useful for cleaning up data where names or phrases might be entered in all small or all capital letters.TEXTPrimarily used with dates to extract specific components like the full day or month name.Requires the value (the date cell) and the format (the code defining what to extract, enclosed in double inverted commas). For example, typing “DDDD” will return the full day name (e.g., “Tuesday”).DAYSCalculates the difference in the number of days between two specified dates.The syntax requires providing the end date first, followed by the start date.EDATECalculates a future due date by adding a specified number of months to a starting date.Requires the start date and the number of months to add.4. Lookup Formulas
Lookup formulas are crucial for retrieving information from a master dataset into a report or summary.
FormulaDescriptionKey RequirementsVLOOKUPRetrieves information from a table based on a lookup value.Crucially, the lookup value (the item being searched for, e.g., “Bharat Innovation”) cannot be duplicated in the master data. Requires specifying the lookup value, the complete table array (the data range, often excluding headers), and the column index number (the number of the column containing the desired answer). For an exact match, the final argument should be set to FALSE.XLOOKUPAn alternative to VLOOKUP and HLOOKUP, available in Excel versions after 2019.It is considered much easier to use. It requires the lookup value, the lookup array (just the column where the lookup value is found), and the return array (just the column where the desired answer is located). Similar to VLOOKUP, the lookup value should not be duplicated.5. Features Related to Formulas
In addition to formulas, the course touches on features that automate pattern recognition and data manipulation:
Flash Fill (Control + E): This feature, available after the 2019 version, works based on pattern recognition. If the source data and the desired output follow a similar pattern (e.g., combining first and last names), the user provides one example answer, and Flash Fill automatically generates the rest of the output for the entire column.
Dynamic Tables: Converting data to a Table (Shortcut: Ctrl + T) makes formulas dynamic, meaning they automatically extend and apply to new entries added to the table.
Excel Conditional Formatting and Rules
Conditional Formatting is a vital feature in Excel that allows you to apply formatting (decoration) to cells based on specified conditions or rules. The name itselfConditional Formatting is a vital feature in Excel that allows you to apply formatting (decoration) to cells based on specified conditions or rules. The name itself explains its function: you are applying formatting using a condition.
Conditional Formatting and Filtering share similar options, although they serve different purposes. The rules for Conditional Formatting are primarily found under the Home tab.
Purpose and Mechanism
Conditional Formatting means applying formatting—such as colors, fonts, borders, alignment, or number format—with a condition.
For example, you might set a rule: “If the cell’s amount is greater than 100, color it green; otherwise, color it red”. The formula acts like an “If” condition, where if a criterion is met, the decoration is applied.
Key Rules and Conditions
The course content demonstrates several essential rules found within the Conditional Formatting feature:
Greater Than / Less Than: You can highlight values that are above or below a specified number.
Example: Highlighting quantities greater than 10 with red color.
Example: Highlighting quantities less than 7 with green color.
Between: This rule highlights values that fall within a defined range (e.g., between 10 and 15).
Equals To: This highlights cells containing a specific, exact value (e.g., 20).
When using Equals To, you can apply a Custom Format, allowing you to choose specific fill colors (e.g., blue) and font colors (e.g., white and bold) that are not available in the preset options.
Text That Contains: This highlights cells where the text includes a specific string.
Example: If you select a column and set the rule to highlight cells containing “प्रदेश,” it will highlight “Uttar Pradesh,” “Madhya Pradesh,” and “Himachal Pradesh” because they all contain the specified text.
Date Occurring: This allows you to highlight dates based on their relationship to the current date, such as Yesterday, Tomorrow, or Today.
Duplicate Values: This feature quickly identifies and highlights any values that are repeated within the selected range.
Top/Bottom Rules: You can highlight the Top 10 items or Top 10 Percentage of values in the selection.
Data Bars, Color Scales, and Icon Sets: Beyond highlighting text or numbers, Conditional Formatting offers graphical visualization options like Data Bars, Color Scales, and Icon Sets.
Managing Conditional Formatting Rules
Rules can be cleared or managed in two ways:
Clear Rules from Selected Cells: Removes formatting only from the specific area you have selected.
Clear Rules from Entire Sheet: Removes all Conditional Formatting rules applied across the entire worksheet.
Manage Rules: Used to view or edit existing rules, such as correcting an incorrect range selection.
Distinction from Filtering
While Conditional Formatting options are very similar to those found in Filter dropdowns (e.g., Greater Than, Text That Contains, Date Occurring), their core difference lies in how they display the data:
FeatureConditional FormattingFilteringData DisplayAll data remains visible (e.g., 10,000 entries).Only the matching subset of data is displayed (e.g., 2,000 entries).HighlightingThe results that meet the condition are highlighted with color.The results that do not meet the condition are hidden (data is not deleted).Conditional Formatting is preferred when you want the complete dataset to remain visible, but certain data points need to be visually highlighted.
Excel Data Validation: Creating Dropdown Lists
Data Validation is a feature in Excel primarily used to create dropdown menus within cells. It offers a way to restrict or guide the type of data that can be entered into a cell or range, thereby ensuring consistency and ease of data entry.
The course content demonstrates two primary methods for setting up dropdowns using Data Validation:
1. Creating Dropdowns from an Existing List (Source List)
If you already have a set of unique values prepared in a range (such as unique party names or categories), you can use this range as the source for your dropdown list.
Process:Select the cell(s) where you want the dropdown to appear.
Navigate to the Data tab.
Go to Data Validation.
In the Data Validation window, under the “Allow” setting, choose List.
In the “Source” field, select the range of cells containing the unique values (the pre-existing list).
Click Enter or OK.
Result: The selected cells will now have a dropdown arrow, allowing users to select any value from the source list. This can be dragged down to apply the validation to more cells.
2. Creating Dropdowns by Manually Entering Values
If the list of possible entries is small or static, you can manually type the options directly into the Data Validation source box.
Process:Select the cell(s).
Go to Data > Data Validation.
Under the “Allow” setting, choose List.
In the “Source” field, manually enter the desired values, ensuring they are separated by commas.
Example: To create a dropdown for typical survey responses, you would enter Yes, No, I don’t know.
Click OK.
Result: The dropdown will contain only the options you typed.
Other Data Validation Applications
The Data Validation feature is capable of more than just creating dropdowns. It can be used to set restrictions on data entry.
The options available within Data Validation (such as Number, Decimal, etc.) are similar to those found in Conditional Formatting.
While the course primarily uses Data Validation to teach the creation of dropdowns, it is noted that this feature can also be used for other types of data restriction.
Excel Mastery in 90 Minutes | Complete Excel Course in One Video
This text provides a comprehensive tutorial on Microsoft Excel, covering various aspects from the user interface and basic functionalities to advanced features. It extensively explains data manipulation techniques, including sorting, filtering, and cleaning. The tutorial also explores formula construction, emphasizing the use of functions like SUM, COUNT, AVERAGE, VLOOKUP, and newer functions such as XLOOKUP. Finally, it demonstrates data analysis using pivot tables and charts, along with data import and formatting methods. The instruction incorporates numerous exercises to reinforce learning.
Excel Skills Study Guide
Short Answer Quiz
What is the keyboard shortcut to undo the last action in Excel, and how can you use it multiple times?
The keyboard shortcut to undo is Ctrl + Z. Pressing it multiple times will undo a series of actions, going back step-by-step through the changes you made.
What keyboard shortcuts do you use to cut, copy, and paste? Briefly explain the difference between cutting and copying.
Ctrl + X is the shortcut to cut, Ctrl + C to copy, and Ctrl + V to paste. Cutting removes the content from the original location, while copying duplicates the content, leaving the original intact.
How can you open a file in Excel using a keyboard shortcut, and where will it take you?
The keyboard shortcut Ctrl + O will open the “Open” page in the backstage view of Excel. You can then navigate to recent files or browse to others on your computer.
Explain the purpose of the search bar in Excel, and what is the keyboard shortcut to quickly jump to it?
The search bar in Excel allows you to find commands, files, or help articles. The shortcut Alt + Q moves your cursor directly into the search bar.
What is contextual help in Excel, and how can you access it?
Contextual help is specific help information related to the area of Excel you are currently working in. You can usually access it by clicking a question mark icon in dialog boxes or settings.
What are the three ways to rename a worksheet tab, and what is the keyboard shortcut to close a workbook?
You can rename a worksheet by right-clicking the tab and selecting “Rename”, or by double-clicking the tab. Additionally, you can use the contextual menu by right-clicking the tab to select the “Rename” option. The keyboard shortcut to close a workbook is Ctrl + W.
Describe how the Ctrl + arrow keys can be used to navigate within a worksheet. Give three examples.
Ctrl + Down Arrow jumps to the last row containing data in a column, Ctrl + Right Arrow jumps to the last column containing data in a row, and Ctrl + Left Arrow will jump to column A.
Briefly describe what the order of operations (BODMAS/PEMDAS) is and why it matters when constructing formulas in excel.
The order of operations (BODMAS/PEMDAS) is a set of rules defining the order in which mathematical calculations are performed: Brackets, Orders, Division/Multiplication, Addition/Subtraction. It is crucial because it dictates how Excel evaluates formulas, affecting the final result.
Explain the difference between the COUNT, COUNTA, and COUNTBLANK functions.
COUNT counts only cells containing numbers. COUNTA counts cells that are not empty, whether they contain numbers or text. COUNTBLANK counts only cells that are blank in a specified range.
What is the difference between absolute and relative cell referencing? Give an example of when you might want to use each.
Relative referencing adjusts cell references when copying a formula (e.g., A1 becomes B1 when moved to the right), while absolute referencing keeps the cell reference constant (e.g., $A$1 remains $A$1 when copied). You’d use relative when calculations should adjust based on location and absolute when referring to a static input like a tax rate.
Essay Questions
Discuss the importance of keyboard shortcuts in improving efficiency when working with Excel. Provide specific examples of shortcuts that you find particularly useful, and explain why they are beneficial.
Explain the process of creating custom templates in Excel and how they can streamline workflows. Why is saving templates to the default personal folder beneficial?
Explain the significance of the “big five” functions in Excel: SUM, COUNT, AVERAGE, MIN, and MAX. Provide examples of scenarios where each function would be used, and describe how they contribute to data analysis.
Describe various ways to troubleshoot errors when creating formulas in excel and explain the significance of error checking and error handling in developing robust spreadsheets.
Discuss the differences between the following formulas: SUMIF, SUMIFS, COUNTIF, COUNTIFS, AVERAGEIF, and AVERAGEIFS. Explain what the distinction is between singular and plural formulas and provide a specific example of when you might use each.
Glossary of Key Terms
Absolute Referencing: A method of cell referencing in Excel where the cell reference remains constant when the formula is copied to other cells. It is denoted by adding dollar signs ($) before the column letter and row number (e.g., $A$1).
Auto Fill: A feature in Excel that automatically fills in data or formulas based on a pattern. This can involve dragging the fill handle to copy formulas down or across.
Backstage Area: A view accessed by clicking the “File” tab in Excel that allows you to manage files, access settings, and more.
BODMAS/PEMDAS: An acronym that represents the order of operations in mathematics: Brackets, Orders (or Parentheses, Exponents), Division, Multiplication, Addition, and Subtraction. It is essential for accurate formula calculation in Excel.
Contextual Help: Help information that is directly related to the area or tool being used. It provides specific and relevant guidance.
Control Key (Ctrl): A modifier key used in combination with other keys to execute commands and shortcuts.
COUNTA Function: A function that counts the number of cells in a range that are not empty, including cells containing numbers, text, dates or other characters.
COUNTBLANK Function: A function that counts the number of empty cells in a specified range.
COUNTIF Function: A function that counts the number of cells within a range that meet a specified criteria.
COUNTIFS Function: A function that counts the number of cells within a range that meet multiple specified criteria.
COUNT Function: A function that counts the number of cells in a range that contain only numbers.
Custom Formatting: A way to define how numbers, text, dates, or other data appears in cells that is not available in the built-in format options. It allows precise control over data display.
Cut: A command that removes selected content from the original location, allowing it to be pasted elsewhere.
Data Validation: A feature that allows you to restrict the data that can be entered in a cell. This is often used to create drop-down lists.
Date Functions: A group of functions in Excel that are designed to manipulate and calculate dates.
DATEDIF Function: A function that is used to calculate the difference between two dates in years, months, or days.
Delimiter: A character or symbol used to separate data fields or values.
Dynamic Functions: Functions in Excel that are able to automatically update or change results based on changes in the worksheet data.
EDATE Function: A function that returns the date that is the indicated number of months before or after a specified date.
EOMONTH Function: A function that returns the last day of the month, before or after a specified date, often used to manage loan payment schedules.
Error Handling: The process of writing formulas or using features that will handle or prevent error codes from showing in a cell.
Error Message: A text message that appears in a cell indicating a problem with a formula or a value entered.
FILTER Function: A dynamic function used to filter data in Excel based on specified criteria, returning records that match.
Fill Handle: The small square at the bottom-right of a selected cell that allows for quick copying or data entry.
Flash Fill: A feature in Excel that recognizes a pattern in your data and automatically fills in the rest. It can help clean and format data quickly.
Formula Bar: A bar located above the worksheet where you can enter or edit formulas and data.
Formula Auditing: A set of tools in Excel that helps you trace formula precedents and dependents to understand how calculations are performed.
Hard Coding: Directly entering a value into a formula instead of referencing a cell containing the value. This is generally discouraged because it makes spreadsheets harder to maintain.
IFERROR Function: A function that returns a specified value if a formula results in any error.
IFNA Function: A function that returns a specified value if a formula results in an #N/A error.
IF Function: A logical function that performs a test and returns one value if the result of the test is true, and another value if the result is false.
IFS Function: A logical function that tests for multiple conditions and returns a value corresponding to the first true condition, making long nested IF statements less complex.
Intellisense: Excel’s automatic suggestion tool, which shows a list of formulas, function names and arguments as you begin typing.
Keyboard Shortcut: A combination of keys used to perform a command or action quickly.
Left Function: A function that extracts a specified number of characters from the beginning of a text string.
Logical Function: A function that tests a condition and returns a true or false result, often used to make decisions based on specified criteria.
Marching Ants: The animated outline that appears around a cell or range when you cut or copy content; It visually indicates selected data that is being manipulated.
MAX Function: A function that returns the largest value in a range.
MIN Function: A function that returns the smallest value in a range.
Nested IF Statement: An IF statement that is embedded within another IF statement, allowing for multiple conditions to be tested sequentially.
NETWORKDAYS.INTL Function: A date function that calculates the number of workdays between two dates, using international weekend days.
NETWORKDAYS Function: A date function that calculates the number of workdays between two dates, excluding weekends.
Offset Function: A lookup function that returns a reference to a range that is a specified number of rows and columns from a starting point.
Operators: Symbols used in formulas to perform mathematical or logical operations (e.g., +, -, *, /, =, >, <).
Order of Operations: The rules of mathmatics which dictate the sequence in which calculations are performed in a formula; commonly remembered using acronyms like BODMAS or PEMDAS.
Paste: A command that inserts cut or copied content into a specified location.
Personal Templates: Templates saved in a default folder, making them readily accessible under the “Personal” section when creating a new workbook in Excel.
Quick Access Toolbar: A customizable toolbar at the top of the Excel window for quick access to frequently used commands.
Relative Referencing: A method of cell referencing in Excel where the cell reference changes when the formula is copied to other cells based on the relative position. (e.g., A1 becomes B1 when copied to the right)
SORT Function: A dynamic function that sorts data based on specified columns and sort order.
SORTBY Function: A dynamic function that allows sorting of data based on one or multiple columns.
SUMIF Function: A function that sums values within a range that meet a specified criterion.
SUMIFS Function: A function that sums values within a range that meet multiple specified criteria.
SUM Function: A function that adds up the values in a range of cells.
Template File: A special type of Excel file (.xltx) that serves as a starting point for new workbooks. It preserves formatting and structure when opened, rather than modifying an existing file.
Text Functions: A group of functions in excel that can be used to manipulate or work with text data.
Text to Columns: A tool in Excel that separates text in a single column into multiple columns based on a delimiter.
TODAY Function: A date function that returns the current date, updating every time the workbook is opened or calculated.
UNIQUE Function: A dynamic function that returns a list of unique values from a specified range, removing duplicates.
WEEKDAY Function: A function that returns a numerical value corresponding to the day of the week for a given date.
WORKDAY.INTL Function: A function that returns the date a specified number of workdays after or before a date, using international weekend days.
WORKDAY Function: A function that returns the date a specified number of workdays after or before a date, excluding weekends and optionally specified holidays.
Mastering Microsoft Excel
Okay, here is a detailed briefing document summarizing the provided text, including key themes, ideas, facts, and relevant quotes:
Briefing Document: Excel Keyboard Shortcuts, Templates, Data Entry, Formulas, and More
Document Overview: This document summarizes key concepts and techniques for using Microsoft Excel, as presented in the provided source. It covers a range of topics, including efficient keyboard shortcuts, using templates, managing worksheets, entering and editing data, using formulas, handling errors, and applying formatting.
Main Themes and Important Ideas:
Efficiency through Keyboard Shortcuts:The text emphasizes the importance of using keyboard shortcuts to work more efficiently in Excel.
Formatting: Ctrl + B (bold), Ctrl + I (italic), Ctrl + U (underline) are used for quick text formatting.
Undoing Actions: Ctrl + Z is a crucial shortcut to undo the last action, and it can be used repeatedly to revert to previous states.
Moving and Copying Data: Ctrl + X (cut), Ctrl + C (copy), and Ctrl + V (paste) allow for quick data manipulation. The cut action temporarily stores the cut information on a clipboard, visualized by “marching ants” around a cell’s border.
Opening Files: Ctrl + O opens the backstage area directly to the open page.
Search: Alt + Q jumps the cursor to the search area.
Closing Files: Ctrl + W closes the current file.
Navigating Large Worksheets: Ctrl + Arrow keys allow users to quickly jump to the edges of a data range.
> *”a very important keyboard shortcut which you’re going to use all the time is ctrl z that’s going to undo your last action”*
Leveraging Excel Templates:
Excel templates are organized into categories for easy searching and use and include pre-built designs for common tasks, like budgets and invoices.
Templates can be searched by keywords (e.g., “invoice,” “budget”) through an online search bar.
Users can customize templates and save them for reuse in a “personal” templates section of Excel for quicker access, with the file type .xltx. This location is accessed via the “File -> New -> Personal” navigation.
Templates can be saved to a default custom office templates folder or a user-defined folder. Saving to the default folder allows you to select the template from the personal section.
“all of the templates in excel are organized into different categories to make them easier for you to find”
Worksheet Management:
Users can rename worksheets by right-clicking on the tab and selecting “Rename” or by double-clicking on the tab.
Worksheets can be inserted using the “Insert” option in the right-click menu or by clicking the plus (+) icon.
Worksheets can be reordered using a simple drag and drop.
Each worksheet contains approximately 17 billion cells.
Data Entry and Editing:
Data can be entered directly into a cell or via the formula bar.
Pressing “Enter” moves the cursor to the cell below, while pressing “Ctrl + Enter” keeps the cursor in the same cell. Pressing “Tab” moves the cursor to the right cell.
Data can be copied and pasted from other Microsoft applications, and formatting can be adjusted in Excel.
When using the formula bar, a tick is equivalent to enter, and a cross is the cancel.
Excel supports various data types, including text, numbers, decimals, percentages, and formulas.
“anytime you click on a cell that contains numbers or text you’re going to see the contents of that cell also reflected in the formula bar”
Basic Formulas and Operators:
Formulas begin with an equals sign (=).
Basic mathematical operators include +, -, *, and /.
Order of operations is determined by the BODMAS/PEMDAS rule. Brackets are calculated first, followed by orders (square roots, etc.), division, multiplication, addition, and subtraction.
The sum function adds up numbers within a cell range using this syntax: =SUM(cell1:cell2)
Green triangles in cells indicate warnings or potential errors.
“if you’ve got an open bracket you must always remember to close off as many brackets as you’ve opened”
Essential Excel Functions:
SUM: Adds up all the numbers in a selected range.
COUNT: Counts cells containing numbers; COUNTA counts non-empty cells. COUNTBLANK counts blank cells in a given range.
MIN and MAX: Returns the lowest and highest values within a selected range, respectively.
Error Handling:
#NAME? Error: Indicates a problem with the formula name or a named range. The formula can be investigated with the trace precedence function, the trace dependence function, the show formulas function, the error checking tool, or the evaluate formula tool.
#REF! Error: Occurs when a cell reference in a formula no longer exists. This can happen when cells are deleted.
#DIV/0! Error: Results from dividing a number by zero.
Excel’s formula auditing tools help troubleshoot and identify formula issues.
Excel’s evaluate formula tool helps step through a calculation to identify issues.
Relative vs. Absolute Referencing:
By default, Excel uses relative referencing, where cell references adjust when a formula is copied to different locations.
Absolute referencing, achieved by adding dollar signs ($) before the column and/or row (e.g., $A$1), keeps cell references constant when a formula is copied. Pressing F4 will lock cell references in a formula.
Flash Fill
Excel can be used to quickly fill in cells with a desired pattern or structure of data from a source. This can be done by typing the first data cell manually, and pressing control + e.
Cell Styles:
Cell styles are used to apply formatting to different cells, such as input, calculations and headings.
These can be customized.
Colors are determined by the theme being used.
Logical StatementsLogical statements use operators to determine whether a condition is true or false.
Examples of operators include: =, >, <, >=, <=, <>.
Logical statements can be combined with if statements to return specified output for true and false outcomes.
IF StatementsThe IF function allows users to attribute meaning to the true/false results of a logical test (e.g., IF(logical_test, value_if_true, value_if_false)).
IF statements can be nested to perform multiple logical tests.
IF statements can be used in conjunction with other functions to perform complex calculations.
The AND formula tests if multiple conditions are all true, and the OR statement tests if any conditions are true.
Nested IFs and IFs StatementsIFs statements can be used in place of a series of nested IF statements. The syntax is: IFs(logical_test1, value_if_true1, logical_test2, value_if_true2, …)
If using a nested IF or IFs function, you can close off all the brackets at the end of the formula, and Excel will fix it for you if you do not have the correct amount.
COUNTIF, SUMIF, and AVERAGEIF:COUNTIF counts cells that meet a single specified criterion (COUNTIF(range, criteria)).
SUMIF sums values in a range that meet a single specified criterion (SUMIF(range, criteria, sum_range)).
AVERAGEIF calculates the average of values that meet a single specified criterion (AVERAGEIF(range, criteria, average_range)).
COUNTIFS, SUMIFS, and AVERAGEIFS:
These functions are similar to their singular counterparts, but allow for multiple criteria to be set for a range.
Error Handling with IFNA and IFERROR:
IFNA replaces #N/A errors with a user-defined value (e.g., IFNA(value, value_if_na)).
IFERROR replaces any type of error with a user-defined value (e.g., IFERROR(value, value_if_error)).
Dynamic Arrays
Dynamic array functions automatically spill their results into adjacent cells.
OFFSET: Returns a reference to a range that is offset from a starting point (e.g., OFFSET(reference, rows, cols, [height], [width])).
SORT: Sorts a range of cells in ascending or descending order, based on a column index and sort order. This is useful for sorting a range, but can’t be used to sort non-contiguous columns.
SORTBY: Sorts a range of cells based on one or more columns, allowing for complex multi-column sorting (SORTBY(array, by_array1, sort_order1, [by_array2], [sort_order2]…))
UNIQUE: Extracts a unique list of values from a selected range.
FILTER: Filters a range of data based on specified criteria (FILTER(array, include, [if_empty])).
Dynamic array functions can be nested for more complex data manipulation.
Date and Time Functions
Date formats can be customized via the “Format Cells” option. These codes include d for day, m for month, and y for year.
DAY: Extracts the day number from a date.
MONTH: Extracts the month number from a date.
YEAR: Extracts the year from a date.
WEEKDAY: Returns the weekday number (e.g., 1-7) from a date.
DATE: Combines a year, month, and day into a date value (DATE(year, month, day)).
TIME: Combines a hour, minute, and second into a time value (TIME(hour, minute, second)).
TODAY: Returns the current date.
NOW: Returns the current date and time.
WORKDAY: Calculates a finish date, excluding weekends and holidays (WORKDAY(start_date, days, [holidays])).
WORKDAY.INTL: Calculates a finish date, excluding user defined weekends and holidays.
NETWORKDAYS: Calculates the number of workdays between two dates (NETWORKDAYS(start_date, end_date, [holidays])).
NETWORKDAYS.INTL: Calculates the number of workdays between two dates excluding user defined weekends and holidays.
DATEDIF: Calculates the difference between two dates in years, months, or days but does not appear in Excel’s function library and must be typed directly (DATEDIF(start_date,end_date,unit))
EOMONTH : Returns the last day of a month (EOMONTH(start_date, months)), this is useful for payment schedules
EDATE returns a date a specified number of months before or after a given date (EDATE(start_date,months))
Text Functions
Text to Columns: A tool for splitting data within a cell into multiple columns using a delimiter.
LEFT: Extracts a specified number of characters from the left side of a text string (LEFT(text, num_chars)).
RIGHT: Extracts a specified number of characters from the right side of a text string (RIGHT(text, num_chars)).
FIND: Locates the starting position of one text string within another text string (FIND(find_text, within_text, [start_num])).
LEN : Returns the length of the provided string
These can be combined for more complex data manipulation.
Conclusion:
This document provides a comprehensive overview of essential Excel skills. By mastering keyboard shortcuts, understanding Excel’s formula structure, and effectively applying different functions, users can enhance their productivity and perform advanced data analysis.
Let me know if you have any further questions.
Essential Excel Skills
Excel FAQ
What are some essential keyboard shortcuts for formatting text and manipulating cells in Excel?
Some crucial keyboard shortcuts include:
Ctrl + B for bold formatting, Ctrl + I for italics, and Ctrl + U for underline.
Ctrl + Z to undo the last action.
Ctrl + X to cut, Ctrl + C to copy, and Ctrl + V to paste cell content.
Ctrl + O to open a file.
Alt + Q to jump to the search area.
How can I quickly find and use templates in Excel?
Excel offers numerous templates categorized for easy searching. You can access these by going to File > New. In the Office section, you can browse suggested categories like budgets or search directly for templates such as invoices. Templates are reusable, and saving them in the default “Custom Office Templates” folder allows them to be accessed under the “Personal” section in the File > New area.
How can I navigate and manage multiple worksheets within an Excel workbook?
You can rename worksheets by right-clicking on the sheet tab and selecting “Rename” or by double-clicking the tab. Insert new worksheets by right-clicking on a tab and choosing “Insert” or by clicking the “+” icon next to the sheet tabs. Reorder worksheets by clicking and dragging the sheet tabs. To quickly navigate to the top, bottom, left-most or right-most cells of a worksheet use Ctrl + Up Arrow, Ctrl + Down Arrow, Ctrl + Left Arrow, and Ctrl + Right Arrow, respectively.
What are the different ways to enter and edit data in Excel cells?
You can enter data into a cell by selecting it and starting to type. The contents also appear in the formula bar. After typing, press Enter to move to the cell below or Ctrl + Enter to stay in the same cell. Use the Tab key to move to the next cell to the right. Data can be directly entered into cells or through the formula bar using a tick mark to accept and an “x” to cancel an entry. Excel supports a variety of data including text, numbers, percentages, and formulas. You can copy and paste data between Excel sheets, other Microsoft applications, and within workbooks, using the clipboard group in the Home tab.
How do formulas and operators work in Excel?
Formulas in Excel start with an equals sign (=). Basic operators include + (addition), – (subtraction), * (multiplication), and / (division). Excel follows the order of operations (BODMAS/PEMDAS), meaning brackets are calculated first, followed by orders, then division and multiplication, and lastly addition and subtraction. Functions like SUM are used to calculate sums of cells.
How do I use the SUM and COUNT functions in Excel and what are the error indicators?
The SUM function adds a range of numbers together. The syntax is =SUM(range). The COUNT function counts numeric values within a range. The syntax is =COUNT(range). The COUNTA function counts all non-blank cells in a range. The syntax is =COUNTA(range) And, the COUNTBLANK function counts all blank cells. The syntax is =COUNTBLANK(range). When errors occur in formulas, Excel provides indicators such as green triangles in cell corners. These often indicate a warning and can be addressed through the Error Checking tool under the Formulas tab. These warnings typically mean that a formula omits some data adjacent to the cells it references.
What is the difference between relative and absolute referencing in Excel formulas, and how does “Flash Fill” work?
Relative referencing adjusts cell references in formulas when copied. Absolute referencing, uses the $ sign before the column and row numbers (e.g., $A$1), and keeps the reference constant when copied. Flash fill (Ctrl + E) automatically fills data based on a detected pattern in the initial entry.
How do IF, AND, OR and IFERROR logical functions work in Excel?
IF statements evaluate a condition and return one value if true and another if false. You can nest IF statements to evaluate multiple conditions, or use the IFS function in newer versions of Excel. Logical operators like >, <, >=, and <= are used in logical statements. AND requires all conditions to be true, and OR requires at least one condition to be true. IFERROR provides a way to return a specific value if an error occurs in a formula.
Microsoft Excel Interface Guide
The Excel interface is comprised of several key elements that facilitate user interaction and data manipulation [1-3].
Title Bar: Located at the top of the screen, the title bar displays the name of the current document, which defaults to “Book 1,” “Book 2,” etc. until the file is saved with a custom name [1].
It also includes the Quick Access Toolbar on the left, which is a customizable area for frequently used commands [1, 4].
A search bar is located in the middle of the title bar, which allows you to look for anything within Excel [1, 5].
On the right side, account information, minimize, restore, and close buttons are available [1]. The close button in the top right corner will close the entire Excel application and all open workbooks [2].
Ribbons and Tabs: Below the title bar are tabs (e.g., Home, Insert, Draw, Page Layout, Formulas, Data, Review, View, Help) that organize commands into logical groups. Each tab has its own ribbon, which contains the commands for that specific category [2].
The commands are further organized into groups within each ribbon [6].
Commands can be accessed by clicking the icons on the ribbon or by using keyboard shortcuts, when available [7, 8].
A screen tip pops up when hovering over a command and gives the name, a short description, and any keyboard shortcut [7, 8].
Right-clicking on a command will display a contextual menu with related menu items [7].
Some groups will have a small diagonal arrow that when clicked, will open a dialog box or a pane with more options [9].
Start Screen: When Excel is launched for the first time, the start screen appears. This screen provides options to create a new blank workbook, select a template, or open existing files. The start screen will not be displayed when opening Excel after the initial launch unless it is closed and reopened [10, 11].
The start screen has three icons on the left: home, new, and open [10].
The ‘home’ page allows for creating a new blank workbook or selecting a template [10].
The ‘new’ icon has similar options to the ‘home’ page, with the ability to access a template library that is categorized [12].
The ‘open’ section is used to access previously created workbooks or folders [12].
The ‘account’ section allows for changing your account information and background themes [13].
The ‘options’ section allows for customizing your copy of excel, language, ribbons, and add-ins [11, 13].
Name Box and Formula Bar: Located below the ribbons, the name box displays the cell reference of the currently selected cell [3, 6].
The formula bar, next to the name box, shows the content of the selected cell and is used for creating or editing formulas [3].
Worksheet: The main area of the workbook where data is entered and manipulated [3].
Worksheets are organized into a grid of columns, labeled with letters, and rows, labeled with numbers, that form cells [3, 14].
Each cell is identified by a cell reference such as “A1”, “B2”, “C3” etc. which is where the column and row intersect [3, 14].
A workbook can contain multiple worksheets [3, 14]. Worksheets can be renamed, added, reordered, moved, copied, deleted, and colored [15, 16].
Each worksheet has over 1 million rows and 16,000 columns for data entry [15].
Horizontal and vertical scroll bars are included to navigate the worksheet [6].
Status Bar: Located at the bottom of the Excel window, the status bar displays various information and options [6].
It contains quick ways to switch worksheet views and a zoom slider [6].
The status bar can be customized to show useful pieces of information [6].
Backstage Area: Accessed by clicking the “File” tab, the backstage area is used for file management and settings. It contains options for opening, saving, printing, and sharing files, as well as account information, feedback, and options [17].
The “Info” page, within the backstage area, allows for protection of the workbook, inspecting the workbook, recovering unsaved workbooks, and controlling browser view options [17]. It also displays document properties [17].
Clicking the close button on this page will close the current workbook only, while leaving Excel open [4].
To go back to the worksheet from the backstage area, click the back arrow or press the escape key on your keyboard [4].
Customizing the Excel Quick Access Toolbar
The Quick Access Toolbar (QAT) is a customizable toolbar that provides quick access to frequently used commands [1, 2]. It is located in the top left corner of the Excel interface, but can be moved to below the ribbon [3].
Key aspects of the Quick Access Toolbar include:
Customization: Users can add and remove commands to tailor the toolbar to their needs [3].
Commands can be added by right-clicking on any command on the ribbon and selecting “Add to Quick Access Toolbar” [4].
Commands can also be added through the Excel options menu [4].
The Excel options menu allows users to view and select all of the commands available in Excel when customizing the toolbar [5].
Users can reorganize the commands on the QAT by using the arrows in the options menu [5].
Commands can be removed from the QAT by right-clicking on a command on the toolbar and selecting “Remove from Quick Access Toolbar” [6].
Position: The QAT can be displayed above or below the ribbon [3].
To change the position of the QAT, users can click the “Customize Quick Access Toolbar” drop-down arrow and select “Show Below the Ribbon” or “Show Above the Ribbon” [3].
Default Commands: By default, the QAT includes common commands such as save, undo, and redo [3].
Labels: The QAT can display labels for the items on the toolbar [4].
To display labels, users can select the “Display labels for the items on our quick access toolbar” checkbox in the Excel options menu [4].
Separators: Separators can be added to the QAT to group commands [5].
Separators are small, faint lines that add structure to the QAT [5].
Visibility: The QAT can be toggled on or off [4].
To hide the QAT, users can deselect “Show Quick Access Toolbar” in the Excel options menu [4].
The Quick Access Toolbar is a useful tool to enhance efficiency by providing a place to put frequently used commands that are easily accessible, so users do not have to hunt through different ribbons to find them [3].
Mastering Excel Keyboard Shortcuts
Keyboard shortcuts in Excel are key combinations that allow users to perform actions and execute commands quickly, without using the mouse [1]. They are an important tool for improving efficiency when working in Excel [1].
General Functionality:
Ctrl + N creates a new blank workbook [1-3].
Ctrl + O opens an existing workbook [4].
Ctrl + S saves the current workbook [1].
Ctrl + W closes the current workbook [2, 5].
Ctrl + Z undoes the last action [1, 4].
Ctrl + Y redoes the last action.
Ctrl + F1 minimizes or expands the ribbon [6, 7].
Esc will exit out of the backstage area [3].
Navigation:
Arrow keys navigate horizontally and vertically in a spreadsheet [8].
Ctrl + Arrow Key jumps to the last row or column of a data set or the edge of a continuous data range [7, 9].
Ctrl + Shift + Arrow Key selects all the data in a row or column [7, 10].
Editing:
Ctrl + X cuts selected content [4].
Ctrl + C copies selected content [4].
Ctrl + V pastes content [4].
Ctrl + B applies bold formatting [4].
Ctrl + I applies italic formatting [4].
Ctrl + U applies underline formatting [4].
Ctrl + Shift + Plus adds new columns or rows [11].
Ctrl + Minus deletes selected columns or rows [11, 12].
Selection:
Ctrl + A selects all data in a table or all cells in a worksheet [7, 13].
Shift + Arrow keys allows for selecting data [13].
Other:
Alt + = creates a sum formula [14].
Ctrl + ; inputs the current date [15].
Ctrl + Shift + ; inputs the current time [15].
Ctrl + Shift + Plus inserts a new column or row [11].
F1 opens the Excel help menu [16, 17].
F4 cycles through relative and absolute cell references [18].
F7 spell checks a worksheet [19, 20].
Alt + Q moves the cursor to the search area in the title bar [21].
Alt key displays shortcut keys assigned to all tabs, the search area and items on the quick access toolbar [16].
Ctrl + F3 opens the name manager dialog box [22].
Ctrl + G opens the go to dialog box [12, 19].
Ctrl + E uses the flash fill function [23].
Ctrl + T creates a table [24, 25].
Ribbon Access:
Pressing the Alt key activates the shortcut keys for the tabs on the ribbon, as well as the Quick Access Toolbar and the search bar. [16]
After pressing Alt, pressing the assigned letter of a tab will open that tab. From there, pressing the letters assigned to a particular command will execute that command using only the keyboard [16].
Screen Tips:When you hover the mouse over a command on a ribbon, a screen tip pops up giving the name, a short description, and the keyboard shortcut for the command, if one exists [2, 26].
It is not necessary to remember all of the available keyboard shortcuts, and most users will use a small set of shortcuts regularly [1]. You can find a comprehensive list of all keyboard shortcuts available in Excel in the help file [16].
Understanding Excel Cell References
Cell references are used to identify specific cells within a worksheet [1]. They are essential for creating formulas and performing calculations in Excel [1].
Each cell is identified by a combination of its column letter and row number. For example, the cell in the first column and first row is referred to as cell A1. Similarly, the cell in the second column and second row is B2, and so on [1].
When a cell is selected, its cell reference is displayed in the name box, located to the left of the formula bar [1].
Cell references are used in formulas to specify which cells are being used in a calculation. For example, the formula =A1+B1 would add the values in cells A1 and B1 [1].
There are three types of cell references:
Relative references: These references change when a formula is copied to another cell [2]. For example, if the formula =A1+B1 is in cell C1, and the formula is copied to cell C2, it will become =A2+B2. The cell references change relative to their new position [2].
Absolute references: These references do not change when a formula is copied. They are created by adding dollar signs ($) before both the column letter and row number, such as $A$1. When the formula $A$1+$B$1 is copied, it will remain $A$1+$B$1 in the new cell [2]. You can cycle through relative, absolute, and mixed cell references by using the F4 key [2].
Mixed references: These references have either the column or row as an absolute reference and the other as a relative reference. For example, $A1 will keep the column fixed as A, but the row will change relative to the position of the cell, as it is copied. A$1 will keep the row fixed at 1, but will change column to relative to its position [2].
When using named ranges, the cell references are absolute by default [2]. This means that when the named range is used in a formula, the reference will always refer to the exact same cells, no matter where the formula is copied.
Cell references can also be used to refer to cells on other worksheets. In this case, the sheet name is included in the reference, such as Sheet2!A1. It is also possible to refer to cells in other workbooks, by including the name of the workbook, such as [Workbook2.xlsx]Sheet1!A1.
Understanding cell references is crucial for creating effective formulas and analyzing data in Excel [1].
Mastering Data Manipulation in Excel
Data manipulation in Excel involves a variety of techniques to organize, clean, and transform data to make it suitable for analysis [1]. This includes tasks such as sorting and filtering, using formulas and functions, and cleaning up inconsistencies [1-53].
Key aspects of data manipulation in Excel include:
Sorting and Filtering:Sorting organizes data in a logical order, either in ascending or descending order, by cell values, cell color, font color, or conditional formatting icons [29-31]. Sorting can be performed on a single column or multiple columns [29]. Custom lists can be created to sort data in a specific order [32]. The SORT and SORTBY functions can be used to sort data and output the results to a different range [33].
Filtering extracts specific data that meets certain criteria [29]. Excel has a basic filter option using drop-down arrows, but also an advanced filter option that allows for more complex filtering criteria, such as extracting unique lists of values [35, 36]. The UNIQUE function can also extract a list of unique values [36, 37]. The FILTER function will filter a range based on specified criteria [38].
Data Cleaning:Removing blank rows and cells: Blank rows and cells can be removed using the “Go To Special” dialog box [43].
Correcting inconsistent casing: Text functions such as UPPER, LOWER, and PROPER can be used to standardize the capitalization of text strings [44].
Removing erroneous spaces: The TRIM function can be used to remove extra spaces at the beginning, end, or in between words in a text string [44].
Splitting data: The Text to Columns tool can be used to split data in a column into multiple columns [45, 46]. The FLASH FILL tool can quickly split data based on patterns, without using complex formulas [47, 48].
Combining data: The CONCAT function or the & operator can combine text strings from different cells into one [49, 50].
Removing Duplicates: The “Remove Duplicates” tool will identify and remove any duplicate rows based on selected columns [53].
Formulas and Functions:
Excel formulas and functions are used to perform calculations and manipulate data based on various criteria [5, 13].
Logical functions such as IF, AND, OR, IFERROR, and IFS are used to make decisions based on criteria [13, 18-20].
Lookup functions such as VLOOKUP, HLOOKUP, INDEX, MATCH, XLOOKUP, and XMATCH are used to retrieve data from tables based on specified values [13, 21-27].
Date and time functions such as WORKDAY, WORKDAY.INTL, NETWORKDAYS, NETWORKDAYS.INTL, DATEDIF, YEAR, MONTH, DAY, and WEEKDAY are used to manipulate date and time values [13, 38-40].
Text functions, such as LEFT, RIGHT, MID, FIND, LEN, and CONCAT, are used to manipulate text strings [44, 49, 50].
Tables:
Excel tables are a structured way to organize data, making it easier to sort, filter, and analyze [50-53]. Tables can be created by selecting data and using Ctrl + T or by going to the “Format as Table” option on the home tab. Tables auto-expand to include any new rows or columns that are added to them, and can be given meaningful names.
Cell Styles: Cell styles allow users to format cells to provide visual cues as to the purpose of the cell, for example to indicate input cells or cells containing formulas [14, 15].
Data Validation: Data validation tools can be used to control what type of data can be entered into cells, which can help to ensure that the data is consistent and error-free [15-17].
By using these techniques, you can manipulate your data so it is consistent, accurate, and ready for analysis.
Excel 2021/365 Beginners & Intermediate Training: 10-Hour Excel Tutorial Class
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This instructional guide provides a comprehensive walkthrough on creating interactive dashboards in Microsoft Excel. It begins by explaining how to transform raw data into a table format and then proceeds to demonstrate the creation of multiple pivot tables from this data. The guide then illustrates how to generate various pivot charts from these tables, including stacked column and line charts, and how to integrate them onto a single dashboard sheet. A key feature covered is making the dashboard dynamic through the addition and connection of slicers and timelines, allowing users to filter data interactively. Finally, the source details how to refresh the dashboard with new data, customize its appearance, and share the completed dashboard with others.
Interactive Excel Dashboards: Building and Sharing Data Insights
Building interactive dashboards in Microsoft Excel allows you to showcase the most important information to your organization, and it is described as being very easy to set up. You don’t need to know any VBA or install any add-ins, only the base version of Microsoft Excel. Once created, the dashboard will automatically update to reflect the latest data as new information comes in. It is also easy to share with others in your organization.
Here’s a detailed discussion on building Excel interactive dashboards based on the sources:
Core Components and Setup
Purpose: Dashboards can be used to answer various business questions, such as those related to profit or unit sales for a company.
Data Preparation: The first step is to ensure your data is in a table format. You can do this by clicking anywhere in your data, then going to the “Insert” tab on the top ribbon and selecting “Table,” or by pressing the shortcut key Control + T. When prompted, ensure your table has headers. This tabular format works very well for creating pivot tables.
Pivot Tables: To build the dashboard, you will create several pivot tables. These pivot tables serve as the foundation for your charts.
To insert a pivot table, click into your data table, go to the “Insert” tab, and select “PivotTable”.
It is recommended to place the pivot table on a new worksheet.
For a dashboard with three different charts, you will likely need three different pivot tables. You can create copies of an existing pivot table sheet by holding the Control key, clicking on the sheet, and dragging it over.
Pivot Charts: Once your pivot tables are set up, you will insert pivot charts to visually represent the data.
To insert a chart, click into your pivot table, go to the “PivotTable Analyze” tab on the top ribbon, and select “PivotChart”.
Chart Types:
For profit by country and cookie, a stacked column chart works well, which helps visualize largest items at the bottom and smallest at the top.
For unit sales over time, a line chart is recommended.
For profit by month, a line chart is also effective for representing data over time.
Formatting Charts:
Add a chart title by going to “Design” -> “Add Chart Elements” -> “Chart Title” -> “Above Chart”.
Remove field buttons on the chart to clean it up. You can do this by right-clicking on a field button and selecting “Hide All Field Buttons on Chart”.
Remove legends if they are unnecessary, such as a “Total” legend.
Currency/Number Formatting: Format values in pivot tables to currency or remove decimal places as needed.
Sorting Data: For better readability, you can sort data in pivot tables (e.g., from most profitable to least profitable for markets and cookie types).
Assembling the Dashboard
Moving Charts: After formatting, copy each pivot chart (Control + C) and paste it (Control + V) onto your main dashboard sheet.
Positioning: You can position charts on the dashboard by selecting them and pressing the Alt key while dragging to snap them into different positions, which helps with organization.
Alignment: Use alignment tools under the “Shape Format” tab to align charts (e.g., align to top, align to left) to ensure everything looks organized.
Dimensions: You can also specify the exact height and width of charts under the “Format” tab to ensure consistency.
Making the Dashboard Interactive
To make the dashboard dynamic and interactive, you can insert slicers and timelines.
Timelines:
Select one of the pivot charts, go to “PivotChart Analyze,” and select “Insert Timeline”.
Choose the “Date” field for the timeline.
Slicers:
Select a pivot table, go to “PivotChart Analyze,” and select “Insert Slicer”.
Choose fields like “Country” and “Product” to quickly filter data.
Clean Up Slicers: Right-click on a slicer, go to “Slicer Settings,” and turn off the “Display Header” to remove unnecessary text like “country” or “product”.
Resize Slicers: Resize slicers to fit the items, and ensure they have the same width for a consistent look.
Connecting Slicers/Timelines: Crucially, connect your slicers and timelines to all relevant pivot tables.
Right-click on a slicer (or timeline), go to “Report Connections,” and check the boxes for all the pivot tables you want that slicer to control. This ensures that when you interact with a slicer, all related views on your dashboard update.
To select multiple items with a slicer, click on the first item and then drag your mouse down.
Updating and Refining
Refreshing Data: When new data comes in, you can update your dashboard easily.
Paste the new data into the original data table. Because it’s formatted as an Excel table, the new data is automatically incorporated.
Go back to your dashboard, click into one of the pivot charts, go to “PivotChart Analyze,” and select “Refresh” -> “Refresh All“. This will update your dashboard to account for the latest data.
Visual Refinements:
Go to the “View” tab and turn off gridlines and headings to make the sheet look more like a proper dashboard.
Hide separate sheets for pivot tables and data by selecting them, right-clicking, and choosing “Hide”. This ensures that when shared, people only see the dashboard.
Change the color scheme/themes by going to the “Page Layout” tab and selecting from different themes. You can also browse for or save custom themes.
Sharing the Dashboard
To share the dashboard, click on the share icon in the top right-hand corner.
You can decide if people can edit or only view the sheet.
You can select specific people to share it with or copy a link to share.
Excel Dashboards: Dynamic Data Analysis and Visualization
Building dashboards in Microsoft Excel is presented as a very easy way to conduct data analysis and showcase important information to an organization. This approach allows for quick insights into business questions, such as those related to profit or unit sales.
Here’s a discussion of data analysis as described in the sources:
Purpose of Analysis: The primary goal of building these dashboards is to answer various business questions. For example, the “Kevin Cookie Company” aims to understand its profit and unit sales.
Data Preparation: A crucial first step for data analysis is to ensure your raw data is in a table format within Excel. This is achieved by selecting any cell in your data and pressing Control + T or by going to the “Insert” tab and choosing “Table”. Ensuring the table has headers is important. This tabular format is ideal for creating pivot tables.
Core Analytical Tools – Pivot Tables: The foundation of the dashboard and its analytical capabilities are pivot tables.
To create a pivot table, you click within your data table, go to the “Insert” tab, and select “PivotTable”.
It is recommended to place each pivot table on a new worksheet.
For a dashboard with multiple charts, you will likely need multiple pivot tables, which can be easily duplicated by copying existing pivot table sheets.
Visualizing Data – Pivot Charts: Once pivot tables are set up, pivot charts are inserted to visually represent the analyzed data.
To insert a chart, select a pivot table, go to “PivotTable Analyze,” and choose “PivotChart”.
Common chart types for specific analyses mentioned include:
Stacked column charts for analyzing profit by country and cookie, which help visualize larger items at the bottom and smaller ones at the top for easier consumption.
Line charts are recommended for analyzing unit sales over time and profit by month, as they are effective for representing data trends.
Charts can be formatted by adding titles, removing unnecessary field buttons to clean up the visual, and sometimes legends.
Refining and Organizing Analysis:
Formatting Values: Values in pivot tables can be formatted to currency or have decimal places removed for clarity.
Sorting Data: For better readability and insight, data within pivot tables can be sorted, for example, from most profitable to least profitable.
Dashboard Assembly: After creation and formatting, charts are copied and pasted onto a central dashboard sheet. They can be positioned and aligned using tools like the Alt key for snapping to cells, or “Shape Format” alignment tools for precise organization. Exact dimensions of charts can also be set for consistency.
Interactive Analysis – Slicers and Timelines: To make the dashboard dynamic and facilitate deeper data analysis, slicers and timelines are inserted.
Timelines are used for filtering data based on date fields.
Slicers allow for quick filtering by categorical fields like “Country” and “Product”.
To enhance interactivity, slicers and timelines must be connected to all relevant pivot tables. This ensures that when a filter is applied (e.g., selecting a specific country or product, or a time range), all charts on the dashboard update simultaneously to reflect the filtered data. This makes it very easy to look at data how you want to view it.
Updating Analysis with New Data: The dashboard is designed to automatically update to reflect the latest data. New data can be pasted directly into the original Excel table, and then the dashboard can be refreshed by selecting “Refresh All” under “PivotChart Analyze”.
Presenting the Analysis: For a clean, professional look, gridlines and headings can be turned off on the dashboard sheet. The separate sheets containing pivot tables and raw data can also be hidden, so only the dashboard is visible when shared. Color schemes and themes can be customized to match organizational branding.
Sharing Insights: The completed dashboard can be easily shared with others in an organization, with options to allow editing or only viewing.
Excel Dashboard Charting: A Comprehensive Guide
Charting data is a crucial aspect of building interactive dashboards in Microsoft Excel, allowing you to visually represent key information and gain insights.
Here’s a detailed discussion on charting data for dashboards:
Foundation for Charts: Pivot Tables
Before creating charts, your raw data must be in a table format. This tabular format is highly effective for generating pivot tables, which serve as the data source for your charts.
Dashboards typically require multiple pivot tables to support different charts and views. These can be created on separate worksheets and then copied to provide the necessary foundations.
Data within pivot tables should be formatted (e.g., currency, no decimals) and sorted (e.g., most profitable to least profitable) for better readability before charting.
Inserting Pivot Charts
Once your pivot table is prepared, you can insert a chart by clicking into the pivot table, navigating to the “PivotTable Analyze” tab, and selecting “PivotChart”.
This opens the “insert chart dialog” where you select the desired chart type.
Recommended Chart Types for Specific Analyses
Stacked Column Charts: These are well-suited for visualizing data like “profit by country and cookie”. They help in consuming data by arranging the largest items at the bottom and the smallest at the top.
Line Charts: These are highly effective for representing data trends over time. They are recommended for analyses such as “unit sales over time” and “profit by month”.
Formatting Charts for Dashboard Presentation
Add Chart Titles: To ensure clarity, add a descriptive title to each chart (e.g., “Profit by market and cookie type”, “units sold each month”, “profit by month”). This can be done via the “Design” tab under “Add Chart Elements”.
Remove Field Buttons: To clean up the chart and remove clutter, right-click on any field button on the chart and select “Hide All Field Buttons on Chart”. This makes the dashboard appear more professional.
Remove Legends: Unnecessary legends, such as a “Total” legend, can also be removed to simplify the visual.
Sizing and Positioning:
After formatting, charts are copied (Control + C) and pasted (Control + V) onto your main dashboard sheet.
The Alt key can be used while dragging a chart to snap it into different positions, aiding in organization.
For precise arrangement, use alignment tools under the “Shape Format” tab (e.g., “align to top,” “align to left”).
You can also specify the exact height and width of charts under the “Format” tab to ensure visual consistency across the dashboard.
Making Charts Interactive with Slicers and Timelines
To transform a static dashboard into an interactive one, insert slicers and a timeline.
Timelines are used for filtering data based on dates.
Slicers allow for quick filtering by categorical fields like “Country” and “Product”.
Crucially, connect your slicers and timelines to all relevant pivot tables on your dashboard. This ensures that when a filter is applied (e.g., selecting a specific country or date range), all charts on the dashboard update simultaneously, providing dynamic insights. This makes it very easy to look at data how you want to view it.
Updating Charts with New Data
Dashboards are designed to automatically reflect the latest data. When new data becomes available, simply paste it into the original Excel data table. Since the data is in a table format, it automatically incorporates the new information.
To update the charts, click into one of the pivot charts on your dashboard, go to the “PivotChart Analyze” tab, and select “Refresh All”. Your dashboard and all its charts will then reflect the most current data.
Excel Slicers: Dynamic Dashboard Data Filtering
Interactive slicers are a key component in creating dynamic and interactive dashboards in Microsoft Excel. They allow users to quickly filter data and gain insights into various business questions, such as profit or unit sales.
Here’s a discussion of interactive slicers:
Purpose and Functionality: Slicers provide a user-friendly way to filter data based on specific fields. For instance, they can be used to quickly view data for a specific country or product type. This makes it “very easy to look at my data how I want to view it”.
Integration with Pivot Tables and Charts:
Slicers are inserted from the “PivotChart Analyze” tab, which indicates their direct connection to the underlying pivot tables and charts.
To ensure the entire dashboard updates dynamically, slicers must be connected to all relevant pivot tables. If a slicer is not connected, other views on the dashboard will not update when a filter is applied. This connection is established by right-clicking on the slicer and selecting “Report Connections,” then checking all the pivot tables you want it to control.
Types of Slicers:
Categorical Slicers: These are used for filtering by categorical fields like “Country” or “Product”.
Timelines: Specifically designed for filtering data based on date fields. A timeline slicer is inserted similarly to a regular slicer, by selecting a date field within the “timeline prompt”.
Inserting Slicers:
Select one of the pivot charts on your dashboard.
Go to the “PivotChart Analyze” tab in the Excel ribbon.
Select “Insert Slicers” (or “Insert Timeline” for date-based filtering).
In the dialog box, choose the fields you wish to filter by, such as “Country” and “Product”.
Click “OK” to insert the slicers onto your dashboard.
Formatting Slicers for Dashboard Presentation:
Removing Headers: For a cleaner look, headers like “Country” or “Product” can be removed if they are self-evident. This is done by right-clicking on the slicer, selecting “Slicer Settings,” and unchecking “Display header”.
Resizing and Positioning: Slicers can be resized to fit their content and positioned on the dashboard for optimal organization. For consistency, their exact width can be set.
Enhancing Interactivity: Once connected to all pivot tables, selecting an item on a slicer (e.g., “India” for country, or “Chocolate Chip” for product) will simultaneously update all linked charts on the dashboard to reflect the filtered data. Users can also select multiple items by clicking and dragging their mouse.
In essence, interactive slicers, combined with timelines, transform a static dashboard into a powerful tool for dynamic data exploration, allowing users to customize their view of the data in real-time.
Sharing Excel Dashboards: A Guide to Dissemination
Sharing a Microsoft Excel dashboard is the final, crucial step in disseminating the insights gained from your data analysis to other members of your organization. Once you have built your interactive dashboard, complete with pivot tables, various charts, and dynamic slicers, it’s designed to be easily shared so that others can benefit from its analytical capabilities.
Here’s a discussion of dashboard sharing based on the sources:
Purpose of Sharing: The primary goal of sharing the dashboard is to allow “other people in your organization” to “get insights from your dashboard”. This ensures that the important information showcased on the dashboard can be used effectively for business understanding and decision-making.
Ease of Sharing: The process of sharing is described as “very easy”. You don’t need any special add-ins or VBA knowledge to set up or share these dashboards.
Preparation for Sharing: Before sharing, it’s recommended to refine the dashboard’s appearance for a more professional look. This involves:
Turning off gridlines and headings on the dashboard sheet itself to make it look less like a typical Excel spreadsheet and more like a dedicated dashboard.
Hiding the underlying sheets that contain the raw data and the individual pivot tables. By selecting these sheets, right-clicking, and choosing “hide,” you ensure that when the dashboard is shared, “people will only see the dashboard that you pulled together”. This streamlines the user experience and focuses attention solely on the interactive visualizations.
Customizing the color scheme/theme to match your organization’s branding or personal preference, which can be done via the “Page Layout” tab under “themes”.
Methods and Options for Sharing:
You can initiate the sharing process by clicking on the “share icon” located in the “top right-hand corner” of Excel.
This action opens a “share dialog” which provides flexibility in how you share and with whom.
Permission Levels: You have the ability to “decide whether people can edit the sheet or if it’s only view only”. This is important for controlling data integrity and ensuring that the shared version is consumed as intended.
Recipient Selection: Within the share dialog, you can “select people you want to share it with”.
Sharing via Link: Alternatively, for broader distribution, you can “simply copy a link and then share it out”.
In summary, Excel’s interactive dashboards are designed for easy and controlled sharing, enabling organizations to quickly disseminate data insights and empower collaborative data exploration.
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This document is a tutorial on Microsoft Excel, covering fundamental and advanced features. It explains basic Excel operations like formatting, saving files, and creating custom lists, then moves on to formulas, functions (including the “Big Six”), and order of operations. The tutorial also explores advanced concepts such as absolute and relative referencing, named ranges, Excel Tables, and data manipulation techniques including sorting, filtering, and using Power Query to combine data from multiple files. Finally, it shows how to handle errors and use conditional formatting to enhance spreadsheets.
Excel Study Guide
Quiz
What is the advantage of saving an Excel template to the custom templates folder? Saving to the custom templates folder allows you to easily access your template from File > New under the personal tab, which makes it convenient to create new files based on that template.
What does ‘hardcoding’ mean in the context of Excel formulas and why should it be avoided? Hardcoding refers to directly typing numbers into a formula instead of using cell references and it should be avoided because if the original numbers change, hardcoded formulas won’t update automatically.
What is the difference between functions and formulas in Excel? Functions are built-in operations in Excel, while a formula is an expression that performs a calculation. Formulas can include one or more functions and other operations.
What is the BODMAS/PEMDAS rule and why is it important when using Excel formulas? BODMAS (Brackets, Orders, Division, Multiplication, Addition, Subtraction) or PEMDAS (Parentheses, Exponents, Multiplication, Division, Addition, Subtraction) is a rule outlining the order of operations in a calculation, and it is crucial because Excel uses this rule when evaluating formulas.
What does the SUM function do, and how can cell ranges be used within it? The SUM function adds up a range of numbers and instead of adding individual numbers, cell ranges, like C6:C25, can be used to easily add all the values in those cells to produce a total.
How do the COUNT and COUNTA functions differ? The COUNT function only counts cells containing numeric data, while COUNTA counts cells that contain any type of data—numbers or text.
Briefly explain what the MIN and MAX functions do. The MIN function returns the smallest numeric value in a given range of cells, whereas the MAX function returns the largest value.
Why is it useful to use cell styles in Excel? Cell styles help improve the readability of spreadsheets and create consistency, particularly when sharing with colleagues, by allowing you to highlight cells for calculations, inputs, titles, and other uses.
How does data validation with a drop-down list help ensure data accuracy? Data validation with a drop-down list allows users to select from a pre-defined list, which prevents spelling errors and other input mistakes, thus ensuring consistency.
What is a nested IF statement? A nested IF statement is one or more IF statements used inside another IF statement, which allows you to perform more complex conditional tests and actions.
Answer Key
Saving to the custom templates folder allows you to easily access your template from File > New under the personal tab, which makes it convenient to create new files based on that template.
Hardcoding refers to directly typing numbers into a formula instead of using cell references and it should be avoided because if the original numbers change, hardcoded formulas won’t update automatically.
Functions are built-in operations in Excel, while a formula is an expression that performs a calculation. Formulas can include one or more functions and other operations.
BODMAS (Brackets, Orders, Division, Multiplication, Addition, Subtraction) or PEMDAS (Parentheses, Exponents, Multiplication, Division, Addition, Subtraction) is a rule outlining the order of operations in a calculation, and it is crucial because Excel uses this rule when evaluating formulas.
The SUM function adds up a range of numbers and instead of adding individual numbers, cell ranges, like C6:C25, can be used to easily add all the values in those cells to produce a total.
The COUNT function only counts cells containing numeric data, while COUNTA counts cells that contain any type of data—numbers or text.
The MIN function returns the smallest numeric value in a given range of cells, whereas the MAX function returns the largest value.
Cell styles help improve the readability of spreadsheets and create consistency, particularly when sharing with colleagues, by allowing you to highlight cells for calculations, inputs, titles, and other uses.
Data validation with a drop-down list allows users to select from a pre-defined list, which prevents spelling errors and other input mistakes, thus ensuring consistency.
A nested IF statement is one or more IF statements used inside another IF statement, which allows you to perform more complex conditional tests and actions.
Essay Questions
Discuss the importance of data validation in Excel and provide specific examples of how it can be used to ensure accuracy and consistency in a spreadsheet.
Compare and contrast the use of nested IF statements with the IFS function in Excel. Discuss situations where one may be more beneficial than the other.
Explain how you can use logical functions like AND, OR, and NOT, in combination with other Excel formulas, and describe their impact on data analysis.
Discuss the differences between the COUNTIF, SUMIF, AVERAGEIF and the COUNTIFS, SUMIFS, AVERAGEIFS functions, and provide examples of scenarios where you might choose one over the other.
Explore the use of dynamic array functions in Excel and discuss how functions like UNIQUE, SORT, and FILTER can improve the analysis and presentation of data, compared to older approaches.
Glossary of Key Terms
Cell Reference: A reference to a cell or a range of cells on a worksheet that can be used in a formula.
Hardcoding: Directly typing numbers or text into a formula instead of using cell references.
Function: A built-in operation in Excel that performs a specific task, such as SUM, AVERAGE, or COUNT.
Formula: An expression in Excel that calculates a value, often using functions, cell references, and operators.
BODMAS/PEMDAS: The order of operations: Brackets, Orders, Division, Multiplication, Addition, Subtraction or Parentheses, Exponents, Multiplication, Division, Addition, Subtraction.
Cell Range: A group of two or more cells on a worksheet, usually specified by the first and last cell (e.g., A1:A10).
Cell Style: A predefined set of formatting attributes that can be applied to cells, for example a particular font size, border, and background color.
Data Validation: A feature that allows you to control the type of data that can be entered into a cell using lists, numbers, and other options.
Dynamic Array: A formula that returns results that spill into multiple cells, automatically updating as data changes (e.g., UNIQUE, SORT).
Nested IF Statement: One or more IF statements used within another IF statement to allow for complex conditional logic.
Logical Functions: Functions that perform tests and return a TRUE or FALSE result, (e.g., AND, OR, NOT).
Conditional IFs: Functions that perform calculations only if specific conditions are met, (e.g., COUNTIFS, SUMIFS, AVERAGEIFS).
Error Handling: Using functions to manage and correct errors in formulas (e.g., IFERROR, IFNA).
Array: A collection of data (values, text, etc.) that can be used in formulas.
Mean: The average value of a set of numbers.
Median: The middle value in a set of numbers when they are ordered.
Mode: The value that appears most frequently in a set of numbers.
Rounding: Adjusting the value of a number to a specified number of decimal places or nearest whole number.
Custom Formatting: Formatting that allows users to control how a value is displayed (e.g., currency, dates).
Variable: In formulas, a named entity that acts as a placeholder for value, range or text string.
Lambda: An Excel feature that allows users to create their own custom, reusable functions.
Advanced Excel Techniques
Okay, here’s a detailed briefing document summarizing the main themes and important ideas from the provided Excel training transcript:
Briefing Document: Advanced Excel Techniques
Overview:
This document summarizes key concepts and techniques from an extensive Excel training resource, focusing on advanced formulas, data manipulation, and automation. The training covers topics ranging from fundamental formula principles to sophisticated functions, custom formatting, and data analysis tools.
Key Themes and Concepts:
Mastering Formulas:
Formula Fundamentals:
The training emphasizes the crucial distinction between functions (pre-built tools) and formulas (expressions using functions and operators).
It highlights the importance of using cell references (e.g., A1) instead of hardcoding numbers to ensure dynamic updates when data changes.
Order of Operations (BODMAS/PIDMAS): The importance of understanding the order of operations (Brackets, Orders/Indices, Division, Multiplication, Addition, Subtraction) is explained using examples, highlighting how Excel follows this rule.
Common Functions:
The training introduces six core functions: SUM, COUNT, COUNTA, AVERAGE, MIN, and MAX.
It emphasizes COUNT only works with numeric values while COUNTA counts text and numbers, showcasing their differences.
Logical Functions:
IF Statements: The core functionality of IF statements is explained, allowing for meaningful outputs based on logical tests, for example returning “yes” or “no” based on data.
AND, OR: The training details how these function enable evaluating multiple logical tests using AND (both conditions must be true) or OR (at least one condition must be true).
Nested IF Statements: It demonstrates how IF statements can be nested to handle multiple conditions and output appropriate results.
IFS Function: It shows how the IFS function can be used as a more streamlined and modern alternative to nested IF statements, simplifying complex logical checks.
Conditional Aggregations:
The training explores COUNTIFS, SUMIFS, and AVERAGEIFS, which are powerful tools for performing calculations based on multiple criteria.
Error Handling
IFNA and IFERROR: The training illustrates using these functions to deal with errors in formulas and output blank cells if an error occurs.
Data Manipulation and Control:
Data Validation: The training demonstrates using data validation drop-down lists to control input and prevent data entry errors.
Quote: “…the method that I would use to to ensure that people are inputting the correct names every single time is to use a data validation drop-down list…”
Cell Styles: The use of cell styles to improve spreadsheet readability is explained.
Quote: ” …cell styles to improve the readability of your spreadsheets…particularly if you’re going to be sharing your spreadsheets with colleagues or other people…”
Filter Function: The function is explored as a method for filtering data and outputting results in the spreadsheet.
Quote: “The Filter function allows us to filter data sets in our worksheet and output results.”
It demonstrates the use of AND, OR, and equals operators within a filter, providing versatile filtering options.
Advanced Data Analysis and Extraction:
UNIQUE Function: The training emphasizes that this function is used to extract a unique list of items from a column. The lesson goes into more detail about it’s two key operations, distinct and unique and clarifies that distinct is the default of the function. It also highlights the functions ability to select rows or columns.
SORT and SORTBY Functions: It demonstrates how to sort a data set or a single column using these functions.
LARGE and SMALL Functions: These functions are shown to extract the largest or smallest values from a dataset based on given parameters.
RANK.EQ and RANK.AVG Functions: The use of these functions are detailed and are shown to be effective when ranking data.
MODE.MULT and MODE.SNGL Functions The lesson explains the use of these functions, clarifying the difference between them and when it is best to use either.
SUBTOTAL and AGGREGATE Functions The use of these functions and their importance are explored. The key difference between them is explained, focusing on AGGREGATE and it’s ability to ignore errors.
Statistical Functions and Rounding
The training touches on the fundamentals of statistical analysis, focusing on AVERAGE, MEDIAN and MODE.
Rounding Functions: It covers ROUND, ROUNDUP, and ROUNDDOWN functions for general rounding, along with MROUND for rounding to multiples and CEILING and FLOOR for always rounding up or down.
Custom Formatting * The course touches on the power of custom formatting, highlighting it’s use in manipulating the look of numbers and text in the worksheet.
LET and LAMBDA Functions:
LET: The training highlights the LET function’s ability to declare variables within a formula, improving readability and efficiency. It provides an example using a complex file name extraction calculation.
Quote: “The LET function can simplify complex calculations in your worksheets by assigning names to calculation results or ranges.”
LAMBDA: It demonstrates how LAMBDA can create reusable custom functions with named parameters, that you can use as you would any other Excel formula.
Quote: “Lambda allows us to create our own functions that we can reuse throughout the workbook.”
Pivot Tables with Multiple Data Sources * The training highlights how to create pivot tables using data from multiple files, highlighting its use in analyzing larger data sets.
Key Quotes:
“Formulas are the backbone of excel.”
“The number one rule of creating formulas is to always make sure that wherever possible… you use the cell reference as opposed to hardcoding the number.”
Important Ideas/Facts:
Excel provides a vast array of built-in functions categorized in the ‘Formulas’ tab.
Dynamic array functions (like UNIQUE, SORT, FILTER) output results that automatically adjust based on the source data, impacting multiple cells.
Custom formatting allows for extremely granular control over the display of numbers and text.
LET and LAMBDA functions provide tools to enhance formula readability, efficiency, and reusability.
Conclusion:
This training material offers a comprehensive look at advanced Excel techniques. It covers core and more complex formulas, data control and error handling, and enhanced analysis tools, showcasing a holistic approach to improving Excel skills. This training aims to empower users to effectively manage, analyze, and automate their data using Excel.
Mastering Microsoft Excel
Excel FAQ
1. Why is it advantageous to save a template file in the custom templates folder? Saving a template file in the custom templates folder makes it easily accessible when creating a new file. Instead of navigating through different folders, you can go to File > New and find your template under the Personal tab, allowing for quick creation of new files based on that template. This is different from saving a template in a personal folder.
2. How do you create a custom list in Excel, and why is it useful? To create a custom list, go to File > Options > Advanced and scroll down to the Edit Custom Lists button. You can import a list from selected cells within your worksheet. Custom lists are useful for auto-filling cells with predefined sequences, like names of students or months of the year, by simply typing the first entry and dragging the autofill handle, saving you from typing the entire list each time.
3. What is the difference between a formula and a function in Excel? Formulas are calculations or expressions that perform operations in Excel. Functions are pre-built operations that are used within a formula to perform specific tasks, like SUM, AVERAGE, or IF. Functions are tools you use to build a formula.
4. What is the BODMAS/PEMDAS rule and why is it important in Excel? BODMAS (Brackets, Orders, Division, Multiplication, Addition, Subtraction) or PEMDAS (Parentheses, Exponents, Multiplication, Division, Addition, Subtraction) represents the order of operations that Excel follows when evaluating a formula. This rule ensures that calculations are performed in the correct sequence, giving you the accurate result you expect by prioritizing brackets (parentheses) first, followed by exponents, then division and multiplication (from left to right), and finally, addition and subtraction (from left to right).
5. What is the difference between COUNT and COUNTA functions in Excel? The COUNT function only counts cells that contain numerical data, while the COUNTA function counts all cells that are not empty, whether they contain numbers, text, dates, or other values. Thus, you would use COUNTA to count a range of text and number entries and COUNT only when a range contains purely numerical values.
6. How can cell styles improve the readability and usability of Excel spreadsheets, and how can these be applied? Cell styles enable you to apply a set of formatting options (font, color, number format, etc.) to cells with one click, enhancing readability and ensuring consistency. Cell styles can be applied to create headings, input cells, calculation cells and more. By creating distinct styles, users can easily understand the purpose of each cell (e.g., input cells have a particular color, while calculated cells are locked) and easily make changes in a consistent manner. Additionally, using styles allows you to automatically copy cell styles when adding new rows or columns.
7. How can Data Validation be used to prevent data entry errors? Data Validation allows you to restrict the type of data that can be entered into a cell, preventing errors and ensuring consistency. You can create drop-down lists to ensure people select from a predefined list of values (such as employee names) and you can also add restrictions on number or date format. This reduces spelling errors, data inconsistencies, and the chance that a formula will not run properly as it is relying on incorrect data.
8. How do IF, AND, OR, and nested IF statements work in Excel, and what are some practical uses?
IF statements: Evaluate a logical test and return one value if true and another if false. They are used to apply logic to a cell’s content.
AND function: Tests multiple conditions and returns TRUE only if all conditions are true.
OR function: Tests multiple conditions and returns TRUE if at least one condition is true.
Nested IF statements: Embed IF statements inside other IF statements, allowing for more complex, multi-layered logical evaluations, where multiple criteria require varying outcomes. These functions are crucial for performing conditional calculations and actions based on data in your spreadsheets, allowing for complex decision-making within formulas.
Microsoft Excel 365: A Comprehensive Guide
Microsoft Excel 365 is an updated version of Excel that is part of the Microsoft 365 subscription service [1]. It is an evergreen version, which means users always have the latest version with the newest features, without needing to purchase a new version [1].
Key aspects of Excel include:
Online Access: Excel 365 can be accessed via an online portal using any browser with an internet connection, allowing users to work on files from any location [1].
Interface:The Excel interface includes a start page that appears when the application is first opened, where users can create a new blank workbook, use a template, or access recent or pinned documents [2].
The main interface contains a title bar, tabs and ribbons, a quick access toolbar, a name box, a formula bar, and the worksheet area [2].
Commands are organized into logical groups within the ribbons [2].
The worksheet itself is a grid of columns (labeled with letters) and rows (labeled with numbers), which creates cells where data is entered [2, 3].
The bottom of the interface contains tabs for different worksheets, scroll bars, a status bar, view options, and a zoom slider [3].
Workbooks and Worksheets:A worksheet is the grid structure within Excel, and a workbook is the file that contains one or more worksheets [2].
Data Entry and Editing:Data can be entered directly into cells [3].
Contextual menus appear when right-clicking on a cell, with options specific to the type of data selected [3].
The autofill handle can be used to copy data or formulas down a column [4].
Formulas:Formulas are used to perform calculations [5].
Formulas must begin with an equals sign (=) [5].
Cell references are used in formulas rather than hardcoding numbers directly [5].
The order of operations, often remembered by the acronym BODMAS (or PEMDAS), dictates how calculations are performed in formulas, with operations in parentheses/brackets performed first [5, 6].
Common mathematical operators include addition (+), subtraction (-), multiplication (*), and division (/) [6].
Functions are pre-built formulas that can be used in calculations, and can be found in the formulas tab [5].
The sum function is commonly used to add a range of numbers [6].
Relative and Absolute Referencing:Relative referencing means that cell references in a formula will automatically adjust when the formula is copied to another cell [4].
Absolute referencing locks a cell reference to a specific cell, preventing it from changing when the formula is copied, and is indicated by using a dollar sign ($) before the column letter and row number (e.g. $A$1) [4].
Basic Functions:SUM: Adds up a range of numbers [7].
COUNT: Counts the number of cells in a range that contain numerical data [7].
COUNTA: Counts the number of non-blank cells in a range (including text and numbers) [7].
AVERAGE: Calculates the average of a range of numbers [7].
MIN: Returns the smallest value in a range of numbers [7].
MAX: Returns the largest value in a range of numbers [7].
Excel Tables:Tables are a way to format data in Excel that add structure to the data and allow for more efficient analysis [8].
Tables have a table design contextual ribbon that provides options for formatting [8].
When using formulas on data in a table, table references are used, which include the table name and column name, rather than cell references [9].
Tables can be named [9].
Total rows can be added to tables to quickly calculate totals for columns [10].
Rows and Columns:The width of columns or the height of rows can be autofitted [10].
Columns and rows can be inserted, deleted, and hidden [10].
Cell Formatting
Cell formatting can be changed using options on the home ribbon [8].
You can use the format painter to copy formatting [8].
Cell Styles can be used to apply specific formatting consistently and identify different types of cells (input, calculation, etc.) [11].
Gridlines can be removed to create a cleaner looking spreadsheet [8].
You can use merge and center to combine cells and center the text or the “center across selection” to center the text in a range of cells, but maintain the individual cells [12].
ThemesExcel themes affect the overall look and feel of a spreadsheet, controlling the colors, fonts, and effects used [12].
You can choose from predefined themes or customize your own theme [12].
Data Input and ValidationData Validation can be used to create drop-down lists, limit the type of data entered, and create custom error messages to prevent errors [13].
Worksheet protection can be used to prevent changes to formulas and other parts of the worksheet [13].
NavigationHyperlinks can be used to link to other worksheets, websites, or locations within the current worksheet [14].
A summary sheet provides instructions, keys, or legends to assist users in navigating and understanding a workbook [14].
Forms can be used to simplify the data entry process and can be added to the quick access toolbar [15].
Dynamic Array Functions:These functions allow for a single formula to generate multiple results [16].
SEQUENCE: Generates a list of sequential numbers [16].
RANDARRAY: Generates a list of random numbers [16].
UNIQUE: Extracts a list of unique values from a range of cells [16].
SORT: Sorts a range of cells [16].
SORTBY: Sorts a range of cells based on another range of cells [16].
FILTER: Filters a range of cells [16].
XLOOKUP: Performs lookups across columns, can be used as an alternative to INDEX and MATCH [16].
XMATCH: Returns the position of an item in a range of cells [16].
Power QueryPower Query is a tool that is used to import and transform data from multiple sources [17].
It uses an applied steps area to record all data transformations [17].
Mastering Excel Formulas
Excel formulas are a key component of the application, allowing users to perform calculations, analyze data, and manipulate information [1].
Key aspects of formulas include:
Initiation: Formulas always begin with an equals sign (=) [1]. This tells Excel that the content of the cell is a calculation, not just text or numbers.
Cell References: When creating formulas, cell references are used rather than directly typing in or “hardcoding” the numbers [1]. For example, instead of typing “=6+3”, a user would type “=A1+A2” if the numbers 6 and 3 were in cells A1 and A2 [1]. Using cell references allows a formula to update automatically if the values in those cells change [1].
Order of Operations: Calculations in formulas follow a specific order, often remembered by the acronym BODMAS or PEMDAS, which dictates the order in which mathematical operations are performed [1]:
Brackets (or Parentheses)
Orders (or Exponents)
Division
Multiplication
Addition
Subtraction
If the order of operations is not correct, the formula will give an incorrect result, but this can be corrected by using brackets [1].
Mathematical Operators:
Addition is represented by the plus sign (+) [1].
Subtraction is represented by the dash (-) [1].
Multiplication is represented by the asterisk (*) [1].
Division is represented by the forward slash (/) [1].
Functions: Functions are pre-built formulas that can be used to perform specific tasks [1].
They can be found in the formulas tab of the ribbon [1].
Functions are organized into categories such as financial, logical, text, date and time, lookup and reference, math and trig, and more [1].
The insert function button, or the keyboard shortcut Shift + F3, can be used to search for and insert a function [1].
A function’s arguments are the values or cell ranges that the function uses to perform its calculation [1].
A function typically requires an open bracket after the function name, then the arguments separated by commas, and then a closing bracket [1].
Excel’s Intellisense feature provides a list of functions that match what a user is typing, with a brief explanation of each [1].
Common Functions
SUM adds up a range of numbers [1, 2].
COUNT counts the number of cells in a range that contain numerical data [2].
COUNTA counts the number of non-blank cells in a range, including both numbers and text [2].
AVERAGE calculates the average of a range of numbers [2].
MIN returns the smallest value in a range of numbers [2].
MAX returns the largest value in a range of numbers [2].
Cell Referencing:
Relative referencing is the default in Excel [3]. When a formula is copied to another cell, the cell references in the formula will automatically adjust based on their relative position [3].
Absolute referencing locks a cell reference to a specific cell, which means when a formula with an absolute reference is copied to another cell, the reference will not change. An absolute reference is created by adding a dollar sign ($) before the column letter and before the row number (e.g., $A$1) [3].
Table References: When using formulas with data in a table, table references are used instead of cell references [4]. Table references use the table name and column name in the formula (e.g., employee_data[salary]) [4]. This can make formulas easier to understand [5].
Dynamic Array Formulas:
These functions allow for a single formula to generate multiple results [6].
Examples include SEQUENCE, RANDARRAY, UNIQUE, SORT, SORTBY, FILTER, XLOOKUP, and XMATCH [5, 6].
Logical Functions: These functions perform tests on data, returning results of true or false [7].
The IF function performs a test and returns one value if the result is true and another if the result is false [7].
IFS allows for multiple logical tests in one function [8].
AND returns true if all conditions are met, while OR returns true if at least one condition is met [7].
IFERROR and IFNA handle errors in formulas. IFERROR will handle any type of error while IFNA will only handle #NA errors [9].
Lookup Functions:
VLOOKUP is a lookup function that searches for a value in the first column of a table and returns a corresponding value from another column in the same row [8]. It can do an exact match or an approximate match [8].
XLOOKUP is a newer lookup function that is more versatile than VLOOKUP and does not have the same limitations [5, 8].
SUMIFS, COUNTIFS, and AVERAGEIFS: These functions allow for calculations based on multiple criteria [9].
LET allows users to define variables within a formula and use those variables in calculations. This can make complex formulas easier to read and more efficient [10].
Mastering Excel Functions
Excel functions are pre-built formulas that perform specific tasks, and they are a key component of using Excel for calculations and data analysis [1, 2]. Functions can be found in the Formulas tab of the ribbon, and are organized into categories such as financial, logical, text, date and time, lookup and reference, math and trig, and more [1, 2]. The Insert Function button, or the keyboard shortcut Shift + F3, can be used to search for and insert a function [1, 2].
Here’s a breakdown of key aspects of Excel functions:
Structure: A function typically requires an open bracket after the function name, then the arguments separated by commas, and then a closing bracket [1, 2]. Arguments are the values or cell ranges that the function uses to perform its calculation [3, 4].
Intellisense: Excel’s Intellisense feature provides a list of functions that match what a user is typing, with a brief explanation of each [1, 2].
Common Functions
SUM adds up a range of numbers [3, 4]. It is a math and trig function that can be used to add a single column or a range of cells [1, 3]. The sum function is often found under the “Recently Used” functions [3].
COUNT counts the number of cells in a range that contain numerical data [4].
COUNTA counts the number of non-blank cells in a range, including both numbers and text [4].
AVERAGE calculates the average of a range of numbers [4].
MIN returns the smallest value in a range of numbers [4].
MAX returns the largest value in a range of numbers [4].
Logical Functions: These functions perform tests on data, returning results of true or false [2, 5, 6].
The IF function performs a test and returns one value if the result is true and another if the result is false [5].
IFS allows for multiple logical tests in one function [6].
AND returns true if all conditions are met, while OR returns true if at least one condition is met [6].
IFERROR and IFNA handle errors in formulas. IFERROR will handle any type of error while IFNA will only handle #NA errors [7].
Lookup Functions:
VLOOKUP is a lookup function that searches for a value in the first column of a table and returns a corresponding value from another column in the same row. It can do an exact match or an approximate match [2].
XLOOKUP is a newer lookup function that is more versatile than VLOOKUP and does not have the same limitations [2].
SUMIFS, COUNTIFS, and AVERAGEIFS: These functions allow for calculations based on multiple criteria [6].
SUMIFS sums values in a range that meet multiple criteria [6].
COUNTIFS counts cells in a range that meet multiple criteria [6].
AVERAGEIFS calculates the average of values in a range that meet multiple criteria [6].
Dynamic Array Functions: These functions allow for a single formula to generate multiple results, and can be combined with other functions [7, 8].
Examples include SEQUENCE, RANDARRAY, UNIQUE, SORT, SORTBY, FILTER, XLOOKUP, and XMATCH [7, 8]. UNIQUE extracts a list of unique values from a range of cells [8]. SORT sorts a range of cells [8]. SORTBY sorts a range of cells based on another range of cells [8].
LET allows users to define variables within a formula and use those variables in calculations [2]. This can make complex formulas easier to read and more efficient.
When using functions, it is also important to keep in mind the following:
Formulas must begin with an equals sign (=) [1, 2].
Cell references are used in formulas rather than hardcoding numbers directly [2].
The order of operations (BODMAS or PEMDAS) dictates how calculations are performed in formulas [1, 2].
Relative and absolute referencing determine how cell references change when a formula is copied to another cell [1, 2].
Table references are used when using formulas with data in a table, using the table and column name in the formula [1, 2, 9].
Functions are fundamental to using Excel for data management and analysis [1, 2].
Data Formatting in Excel
Data formatting in Excel involves how data is displayed in cells, which can greatly affect the readability and interpretation of the information. Formatting can be applied to text, numbers, and dates, and it can control aspects such as font, alignment, colors, and number styles [1].
Key aspects of data formatting in Excel include:
Text vs. Numbers: Text in a cell is aligned to the left by default, while numbers are aligned to the right [1].
Number Formatting:
Excel has various number formats including General, Number, Currency, Accounting, Short Date, and Long Date [1].
The General format has no specific format [1].
The Currency format displays a currency symbol and two decimal places by default [1].
Number formatting can be applied using the Number group under the Home tab [1].
Dates are treated as numbers by Excel, with the date of January 1, 1900, being day zero. When a date is entered, it is actually a number with date formatting applied [1].
If a date is typed into a cell, but it looks like a number, it means that the cell has the wrong number formatting applied [1]. This can be corrected by selecting the Short Date or Long Date format [1].
When entering numbers that start with zero, Excel will remove the leading zeros [1]. To prevent this, an apostrophe can be entered before the number, which will turn the number into text [1].
Cell Alignment: Text in a cell is aligned to the left by default, while numbers and dates are aligned to the right [1].
Copying Formats:
The Format Painter tool can be used to copy formatting from one cell or a range of cells to another [2].
When using the format painter, the entire column of formatting can be copied to another column [2].
Clearing Formats:
Formatting can be cleared from selected cells using the Clear menu in the Editing group under the Home tab [2].
Options include:
Clear All, which removes everything from the cell, including text, numbers, and formatting [2].
Clear Formats, which removes all formatting while keeping the content [2].
Clear Contents, which removes the text and numbers from cells but retains the formatting [2].
Clear Comments and Notes, which clears comments and notes [2]. This is grayed out if there are no comments or notes in the worksheet [2].
Clear Hyperlinks, which removes hyperlinks from selected cells [2].
Remove Hyperlinks, which removes hyperlinks from selected cells and removes the underline [2].
Cell Styles:
Cell styles are predefined sets of formatting that can be applied to cells [3].
Cell styles can be found on the Home tab [3].
Cell styles can be used to quickly and consistently apply formatting to a range of cells [3].
When adding data to a table, the cell style formatting carries through, and it’s not necessary to do anything extra to apply it [3].
Some styles include Normal, Bad, Good, Neutral, Calculation, Input, Heading, and Title [3].
Adding a legend or a key is important to clarify what the cell styles mean [3].
Custom Formatting:Custom formatting can be used to define how numbers, text, and dates are displayed [4].
Custom formatting is divided into four parts, with each part separated by a semicolon [4].
The first part defines how positive values are displayed.
The second part defines how negative values are displayed.
The third part defines how zero values are displayed.
The fourth part defines how text is displayed.
Placeholders are used to specify how numbers are displayed.
The hash symbol (#) is a variable placeholder.
The zero (0) is a fixed placeholder [4].
Colors can be included in custom formats by using the color name in square brackets (e.g., [red]) [4, 5].
Symbols can be included in custom formats, and these can be inserted using the keyboard shortcut Alt + 30 for an up arrow or Alt + 31 for a down arrow [5].
By using different formatting options, users can make their data more readable and understandable and can help to control and standardize the way information is presented in a worksheet [3].
Mastering Excel Tables
Excel tables are a way to format data in a structured manner, and they offer many benefits when it comes to managing and analyzing data [1]. They are different from just entering data into cells and can be identified by a contextual “Table Design” ribbon that appears when a cell within the table is selected [1].
Here’s a breakdown of key aspects of Excel tables:
Creation:
To create a table, select the data, go to the Insert tab, and click on Table, or use the keyboard shortcut Ctrl + T [2].
Excel will attempt to identify the data range, and you must confirm that the selection is correct and indicate whether the table has headers [2].
When using the keyboard shortcut Ctrl+T, the default table style will be applied, although this can be changed later [2].
You can also create a table by going to the Home tab and choosing Format as Table [2].
Table Styles:
Once a table is created, various table styles can be applied from the Table Design ribbon [2].
Table style options include:
Banded rows, which alternate row colors to improve readability [2].
Banded columns which alternate column colors [2].
Header row, which can be toggled on or off [2].
Filter buttons, which allow for filtering of data [2].
Total row, which can quickly calculate totals, averages, and other functions [2].
Formatting of the first column or last column [2].
The theme of a table can be changed by changing the theme of the Excel workbook, which will then change the available table styles [2].
Naming Tables:It is important to give tables a meaningful name, which can be done in the Properties group on the Table Design tab [3].
Table names cannot contain spaces, so an underscore is used between words [3].
Table References:When using formulas with data in a table, table references are used rather than cell references [4].
Table references use the table name and column name in the formula rather than cell references [4].
For example, instead of using “F4:F23” to sum a range of salaries in a table called “employee data”, the formula would be “=SUM(employee data[salary])” [4].
When selecting data in a table for use in a formula, you can hover over the column header until you see a downward pointing arrow, and then click to select all the data in that column [4].
You can also type the table name into a formula, followed by an open square bracket, and then a list of columns will appear [4].
Table references make formulas easier to understand because they use meaningful labels rather than cell references [4].
Adding Data:
When data is added to the bottom of a table, the table will automatically expand to include the new data [5].
Any formatting, such as cell styles, will carry through to the new data [5].
Removing Tables:
Tables can be converted back to a normal range by selecting Convert to Range on the Table Design tab [2].
This will remove the table formatting and features but will keep the data and any formatting [2].
Excel tables are an effective way to manage data, and are an important feature to understand in order to use Excel effectively [1].
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This extensive guide explores Power BI, a business intelligence tool, offering a comprehensive look at its interface and core functionalities. It walks users through report creation, beginning with understanding the canvas, ribbon, and panes for filters, visualizations, and data. The text progresses to data importation from various sources, data cleaning using Power Query Editor, and dashboard construction with diverse visualizations like bar charts, column charts, and scatter plots. Furthermore, it covers advanced topics such as DAX (Data Analysis Expressions) for complex calculations, creating data models with fact and dimensional tables, and using parameters for interactive dashboards. The guide concludes with advice on sharing dashboards and best practices for effective data presentation.
Power BI Desktop: Interface and Fundamentals
The Power BI interface, primarily referring to the Power BI Desktop application, is designed for data analysis and dashboard creation, drawing inspiration from car dashboards for quick insights. It has a distinct layout and terminology compared to tools like Excel.
Key components of the Power BI interface include:
The Ribbon The ribbon is located at the top of the Power BI Desktop application, similar to other Microsoft products. It contains various tabs like Home, Insert, Modeling, View, Optimize, and Help, each offering different functionalities.
Home Tab: Primarily used for getting and editing data queries, connecting to various data sources like Excel workbooks, SQL Server, text files, and the internet. It also includes options to transform data, which opens the Power Query Editor, and to refresh queries.
Insert Tab: Allows users to insert new visuals, text boxes, shapes, and buttons into a report.
Modeling Tab: Used for creating measures, calculated columns, tables, and parameters, often utilizing the DAX language. It also includes options for managing relationships between tables.
View Tab: Enables changes to the report’s appearance, such as color themes (e.g., dark mode, light theme) and layout options. It also controls the visibility of various panes.
Optimize Tab: Contains tools like the Performance Analyzer to inspect and identify bottlenecks in report loading or cross-highlighting.
Help Tab: Provides access to help resources, though external chatbots like Gemini or ChatGPT are often recommended for more practical assistance.
Views: Located on the left-hand side, Power BI Desktop offers several views:
Report View: This is the primary area where users build their dashboards.
Table View: Allows users to view and inspect their loaded data in a tabular format, similar to a spreadsheet. It also enables formatting of data types and decimal places for columns.
Model View: Displays the data model, showing all loaded tables and the relationships between them. This view is crucial for understanding how different tables interact.
DAX Query View: A newer view that allows users to write and execute DAX queries to analyze data and define measures. It can also generate column statistics.
Panes: Located on the right-hand side, these provide interactive elements for report creation and data manipulation:
Filters Pane: Used to apply filters to visuals, specific pages, or all pages in a report.
Visualizations Pane: This is where users select different chart types (e.g., bar charts, line charts, pie charts, maps) and configure their properties, including axes, legends, and field wells. It also allows for formatting visuals, adding analytics features like trend lines, and toggling data labels.
Data Pane: Displays the data model, showing tables, columns, and measures that can be dragged into visuals.
Other Panes: Includes Bookmark Pane, Selection Pane, Performance Analyzer, and Sync Slicers, which are covered in more advanced lessons.
Canvas: The central area of the report view where dashboards are built and visuals are placed. Unlike Excel’s “worksheets,” Power BI reports consist of multiple “pages”.
Initial Setup and Terminology Differences: Power BI Desktop is available for free from the Microsoft Store. Upon opening, users can start with a blank report. The application may prompt users about features like dark mode, though the source recommends the light theme for tutorials due to contrast. Power BI refers to its files as “reports” and the individual tabs within a report as “pages,” differentiating them from Excel’s “workbooks” and “sheets”.
Interaction and Navigation: Users interact with the interface by selecting visuals, dragging fields between panes, and utilizing the various options on the ribbon. Navigation between pages can be done through page tabs at the bottom or by implementing buttons and bookmarks for more dynamic interaction.
The Power BI Service, a cloud-based platform, complements the Desktop application by allowing users to publish and share dashboards with co-workers or to the web, ensuring a single source of truth for data. However, advanced sharing features in the Power BI Service often require a Power BI Pro license.The Power BI interface, primarily referring to the Power BI Desktop application, is designed for data analysis and dashboard creation, drawing inspiration from car dashboards for quick insights. It has a distinct layout and terminology compared to tools like Excel.
Key components of the Power BI interface include:
The Ribbon: Located at the top of the Power BI Desktop application, similar to other Microsoft products, it contains various tabs like Home, Insert, Modeling, View, Optimize, and Help, each offering different functionalities.
Home Tab: Primarily used for getting and editing data queries, connecting to various data sources like Excel workbooks, SQL Server, text files, and the internet. It also includes options to transform data, which opens the Power Query Editor, and to refresh queries.
Insert Tab: Allows users to insert new visuals, text boxes, shapes, and buttons into a report.
Modeling Tab: Used for creating measures, calculated columns, tables, and parameters, often utilizing the DAX language. It also includes options for managing relationships between tables.
View Tab: Enables changes to the report’s appearance, such as color themes (e.g., dark mode, light theme) and layout options. It also controls the visibility of various panes.
Optimize Tab: Contains tools like the Performance Analyzer to inspect and identify bottlenecks in report loading or cross-highlighting.
Help Tab: Provides access to help resources, though external chatbots like Gemini or ChatGPT are often recommended for more practical assistance.
Views: Located on the left-hand side, Power BI Desktop offers several views:
Report View: This is the primary area where users build their dashboards.
Table View: Allows users to view and inspect their loaded data in a tabular format, similar to a spreadsheet. It also enables formatting of data types and decimal places for columns.
Model View: Displays the data model, showing all loaded tables and the relationships between them. This view is crucial for understanding how different tables interact.
DAX Query View: A newer view that allows users to write and execute DAX queries to analyze data and define measures. It can also generate column statistics.
Panes: Located on the right-hand side, these provide interactive elements for report creation and data manipulation:
Filters Pane: Used to apply filters to visuals, specific pages, or all pages in a report.
Visualizations Pane: This is where users select different chart types (e.g., bar charts, line charts, pie charts, maps) and configure their properties, including axes, legends, and field wells. It also allows for formatting visuals, adding analytics features like trend lines, and toggling data labels.
Data Pane: Displays the data model, showing tables, columns, and measures that can be dragged into visuals.
Other Panes: Includes Bookmark Pane, Selection Pane, Performance Analyzer, and Sync Slicers, which are covered in more advanced lessons.
Canvas: The central area of the report view where dashboards are built and visuals are placed. Unlike Excel’s “worksheets,” Power BI reports consist of multiple “pages”.
Initial Setup and Terminology Differences: Power BI Desktop is available for free from the Microsoft Store. Upon opening, users can start with a blank report. The application may prompt users about features like dark mode, though the source recommends the light theme for tutorials due to contrast. Power BI refers to its files as “reports” and the individual tabs within a report as “pages,” differentiating them from Excel’s “workbooks” and “sheets”.
Interaction and Navigation: Users interact with the interface by selecting visuals, dragging fields between panes, and utilizing the various options on the ribbon. Navigation between pages can be done through page tabs at the bottom or by implementing buttons and bookmarks for more dynamic interaction.
The Power BI Service, a cloud-based platform, complements the Desktop application by allowing users to publish and share dashboards with co-workers or to the web, ensuring a single source of truth for data. However, advanced sharing features in the Power BI Service often require a Power BI Pro license.
Power BI: Power Query and DAX for Data Mastery
Data manipulation in Power BI is a crucial process, primarily handled through two powerful tools: Power Query for data extraction, transformation, and loading (ETL), and DAX (Data Analysis Expressions) for creating calculated data within the data model.
Data Manipulation with Power Query
Power Query is described as an ETL tool that allows users to extract data from various sources, transform it, and then load it into Power BI for visualization. It provides a graphical user interface (GUI) for performing these transformations without extensive coding, though it operates on a specialized language called M.
Accessing Power Query Editor: The Power Query Editor can be accessed from the “Home” tab in Power BI Desktop by selecting “Transform data”. This opens a separate window with its own ribbon, data view area, queries pane, and query settings pane.
Key Functionalities and Interface:
Connecting to Data Sources: Power Query supports hundreds of data sources, categorized broadly into files (Excel, CSV, PDF, text), databases (SQL Server, BigQuery), cloud services (Salesforce, Snowflake), and web sources. Users can directly import data or choose to “Transform data” to open the Power Query Editor first.
Folder Connections: A common use case is combining multiple files (e.g., monthly Excel sheets) from a single folder into one table. This can be done by connecting to a “Folder” source and then using the “Combine and Load” or “Combine and Transform Data” options.
Web Sources: Data from web pages, particularly tables, can be easily imported by pasting the URL.
Database Connections: Power Query can connect to various databases, requiring credentials and allowing for optional SQL statements to extract specific subsets of data. When connecting to databases, users choose between “Import mode” (loads all data into the Power BI file, faster performance, larger file size) and “Direct Query” (data remains in the source, smaller file size, slower performance, limited DAX functionality). The source recommends using “Import mode” if possible for better performance and full functionality.
Power Query Editor Interface and Analysis:
Ribbon Tabs: The editor has tabs like “Home,” “Transform,” and “Add Column,” each offering different functionalities.
Queries Pane: Lists all loaded queries (tables).
Applied Steps: This pane on the right tracks every transformation applied to the data. Users can review, modify, or delete steps, allowing for iterative and non-destructive data cleaning. Each step generates M language code.
Formula Bar: Displays the M language code for the currently selected step.
Data View Area: Shows a preview of the data after the applied transformations.
Column Profiling (View Tab): The “View” tab offers features like “Column Profile,” “Column Distribution,” and “Column Quality” to inspect data, identify unique/distinct values, errors, and empty cells. This helps in understanding data quality and guiding transformations. Column profiling can be set to the top 1,000 rows or the entire data set.
Common Data Transformations in Power Query:
Data Type Conversion: Easily change data types (e.g., text to date/time, whole number to decimal). The editor asks if you want to replace the current step or add a new one.
Removing/Choosing Columns: Users can remove unnecessary columns or select specific columns to keep using “Remove Columns” or “Choose Columns”.
Replacing Values: Replace specific text or characters within a column (e.g., removing prefixes like “via” or cleaning up extraneous spaces).
Trimming/Formatting Text: “Format” options allow for changing case (uppercase, lowercase), and “Trim” removes leading and trailing whitespace.
Splitting Columns: Columns can be split by a delimiter into new columns or into new rows, which is particularly useful for handling multi-valued fields within a single cell.
Unpivoting Columns: Transforms columns into attribute-value pairs, useful when data is in a “pivot table” format and needs to be normalized.
Adding Custom Columns: Create new columns based on existing ones using formulas or conditional logic.
Standard Transformations (Add Column Tab): Perform mathematical operations like multiplication (e.g., calculating yearly salary from hourly pay).
Column from Example: Users provide examples of the desired output, and Power Query infers the M language code to generate the new column. This can be more intuitive for complex text manipulations or bucketing.
Conditional Columns: Create new columns based on “if-then-else” logic, similar to Excel’s IF function.
Custom Column (M Language): For more complex scenarios, users can write M language code directly to define new columns. AI chatbots like ChatGPT or Gemini can assist in generating this M language code.
Appending Queries: Combines rows from multiple tables with similar structures (same columns) by stacking them on top of each other. This is useful for consolidating data from different periods or sources.
Merging Queries: Combines columns from two or more tables based on matching values in common columns, similar to SQL joins. Different “Join Kinds” determine which rows are included (e.g., Left Outer, Right Outer, Inner, Full Outer, Left Anti, Right Anti). This is crucial for building star schemas by linking fact tables to dimensional tables.
Grouping Data (“Group By”): Aggregates data based on one or more columns, allowing for calculations like counts or sums for distinct groups, similar to pivot tables in Excel.
M Language: The underlying functional programming language that powers Power Query. Every action taken in the GUI translates into M code, which can be viewed and edited in the “Advanced Editor”. Understanding M can help with troubleshooting and advanced transformations. AI chatbots are recommended for assistance with M language queries.
Data Manipulation with DAX (Data Analysis Expressions)
DAX is a formula language used after data is loaded into the Power BI data model. Unlike Power Query which focuses on data preparation, DAX focuses on creating new calculations and enriching the data model.
Key Functionalities:
Calculated Columns: New columns added directly to a table in the data model using DAX formulas. These calculations are performed during data import or refresh and are stored as part of the model. While possible, Power Query’s custom columns are generally preferred for efficiency and better compression.
Examples include creating an adjusted salary column or a combined yearly/hourly salary column.
Calculated Tables: Entire new tables created using DAX formulas. This is useful for creating lookup tables (e.g., a distinct list of job titles) or date dimension tables.
The CALENDAR and CALENDARAUTO functions are specifically mentioned for creating date tables. The ADDCOLUMNS function can be used to add columns like year, month, or weekday name to a calculated table.
Explicit Measures: Unlike implicit measures (automatically generated by dragging fields), explicit measures are explicitly defined using DAX formulas. They are highly recommended for complex calculations, ensuring reusability, and maintaining a “single source of truth” for calculations across a report. Measures are calculated at “query runtime” (when a visualization is built) and are not stored in the table directly.
Examples include Job Count, Median Yearly Salary, Skill Count, and Skills per Job.
DIVIDE function: A safer way to perform division, handling divide-by-zero errors.
CALCULATE function: One of the most powerful DAX functions, allowing expressions to be evaluated within a modified filter context. This is crucial for overriding or modifying existing filters and contexts.
ALL and ALLSELECTED functions: Used within CALCULATE to remove filters from a table or selected columns/rows, respectively, enabling calculations against totals or specific subsets.
Parameters: While parameters are a user-facing feature, they rely on DAX to define their behavior.
Field Parameters: Allow users to dynamically switch the columns or measures displayed in a visual via a slicer. These parameters are created based on selected fields and generate DAX code.
Numeric Parameters (“What-if” Parameters): Enable users to input a numeric value (via a slider or field) that can then be used in DAX measures to perform “what-if” analysis (e.g., adjusting tax rates for take-home pay).
Context in DAX: Understanding DAX requires comprehending “context,” which dictates how calculations are evaluated. There are three types, with precedence from highest to lowest:
Filter Context: Explicitly modified using DAX functions like CALCULATE.
Query Context: Determined by visual selections, relationships, and cross-filtering.
Row Context: Operates at an individual row level, typically seen in calculated columns.
Best Practices and Considerations
Power Query for Cleaning, DAX for Calculations: Generally, it is recommended to perform extensive data cleaning and transformations in Power Query before loading data into the model, as it leads to better compression, smaller file sizes, and faster data model operations. DAX is best used for creating measures and calculated fields that enrich the analysis after the data is loaded.
Star Schema: Organizing data into fact and dimensional tables (star schema) is a recommended practice for efficient data modeling and analysis, especially when dealing with complex relationships like multiple skills per job posting.
Measure Organization: Store all explicit measures in a dedicated “measures” table for better organization and ease of access.
Commenting DAX: Use comments (single-line // or multi-line /* */) to document DAX measures, improving readability and maintainability.
Data Size: Be mindful of file size implications, especially when importing large datasets or creating many calculated columns, as this can affect performance and sharing capabilities.
Power BI Data Visualization: A Comprehensive Guide
Data visualization in Power BI is a core functionality that allows users to translate raw data into insightful, interactive reports and dashboards. It is a critical skill for data and business analysts, enabling them to communicate data-driven insights effectively.
Power BI Desktop and Its Interface for Visualization
The primary tool for creating visualizations is Power BI Desktop, a free application. When building reports, users interact with several key components:
Ribbon: Located at the top, it contains various tabs like “Home,” “Insert,” “Modeling,” “View,” “Optimize,” and “Help,” which offer tools for data manipulation and visualization.
Views: Power BI Desktop offers different views:
Report View: This is the central canvas where dashboards are built by adding and arranging visuals. Pages within a report are analogous to worksheets in Excel.
Table View: Allows users to inspect and verify the loaded data, view all values, and perform basic formatting like changing data types or currency formats.
Model View: Displays the data model, including tables, columns, measures, and, crucially, relationships between tables. This view helps in understanding how different tables interact.
DAX Query View: A newer feature that allows users to write and execute DAX queries to evaluate measures or view column statistics. It can assist in troubleshooting DAX formulas.
Panes: Located on the right-hand side, these panes are essential for building and refining visuals:
Filters Pane: Used to apply filters at the visual, page, or all-page level, controlling which data is displayed.
Visualizations Pane: Contains a gallery of available chart types and options to format selected visuals.
Data Pane: Shows the data model, listing all loaded tables, their columns, and measures, allowing users to drag fields into visual wells.
Bookmark Pane: Manages bookmarks, which capture specific states of a report page (filters, visible visuals).
Selection Pane: Controls the visibility and order of elements on the canvas, useful for managing layers in design.
Performance Analyzer: Helps identify bottlenecks and slow-performing visuals by recording the time taken for interactions.
Sync Slicers Pane: Manages the synchronization of slicer selections across different report pages.
Canvas: The central area where visuals are added, arranged, and interacted with.
Chart Types and Their Applications
Power BI offers a wide range of built-in visuals, and understanding when to use each is crucial.
Column and Bar Charts:
Stacked Bar/Column Chart: Compares values across categories, with segments of bars/columns representing proportions of a whole.
Clustered Bar/Column Chart: Compares values across multiple categories side-by-side.
100% Stacked Bar/Column Chart: Similar to stacked charts but shows the proportion of each segment relative to 100%, useful for visualizing percentages.
Often used for showing distributions or comparisons of categorical data, like “what are top data jobs” or “what are the type of data jobs”. Columns go vertically, bars horizontally.
Line and Area Charts:
Line Chart: Ideal for showing trends over time, such as “what is the trend of jobs in 2024”. Trend lines can be added for further analysis.
Stacked Area Chart: Shows trends over time while also indicating the composition of a total, useful for breaking down categories over time.
100% Stacked Area Chart: Displays the proportion of categories over time, emphasizing their relative contribution to a total.
Combo Chart (Line and Stacked Column/Clustered Column Chart): Combines columns and lines to compare different measures, like yearly vs. hourly median salary.
Pie and Donut Charts:
Represent proportions of a whole.
Donut Charts: Similar to pie charts but with a hole in the middle.
Recommended for use with only “two to three values” to maintain readability. Examples include “what portion of postings don’t mention a degree” or “what portion of job postings are work from home”.
Tree Maps:
Display hierarchical data as a set of nested rectangles. The size of the rectangle corresponds to the value.
Good for showing breakdowns and can be used to filter other visuals when clicked. Example: “what are the type of data jobs” (e.g., full-time, contractor).
Scatter Plots:
Show the relationship between two numerical values, revealing trends or correlations.
Example: “hourly versus yearly salary of data jobs”. Trend lines can be added.
Maps:
Map Visual: Displays geographical data as dots or bubbles on a map, with bubble size often representing a measure like job count. Can include legends for categorical breakdowns (e.g., degree mentioned). Requires enabling in security settings.
Filled Map: Colors regions on a map based on a measure or category. The source finds it “most useless” due to limited insights and distinct colors for all values.
ArcGIS for Power BI Map: Offers advanced mapping capabilities, allowing for color-coding based on values. However, sharing reports with this visual requires an ArcGIS subscription.
Uncommon Charts:
Ribbon Chart: Shows rank over time, with ribbons connecting values. Can be visually cluttered with too many categories.
Waterfall Chart: Illustrates how an initial value is affected by a series of positive and negative changes, common in finance. Requires specific data formatting.
Funnel Chart: Visualizes stages in a sequential process, showing conversion rates or progression.
Tables and Matrices:
Table: Displays data in rows and columns, similar to a spreadsheet. Useful for showing detailed information and allowing users to export data.
Matrix: Functions like an Excel pivot table, allowing for hierarchical aggregation and drill-down capabilities.
Both support Conditional Formatting (background color, font color, data bars, icons, web URLs) to highlight patterns.
Sparklines can be added to matrices to show trends within individual cells.
Cards:
Display single key metrics or KPIs, typically placed prominently at the top of a dashboard.
Card (original): Simple display of a single value.
Card (new): Preferred due to its ability to display multiple values in a more intuitive layout and title placement.
Gauge Card: Visualizes a single value against a target or range, showing progress or performance (e.g., median salary with min/max/average).
Multi-row Card: Displays multiple values across several rows, useful for listing several key figures.
KPI Card: Shows a key performance indicator, often with a trend line and color-coding (green/red) based on performance against a target.
Interactive Elements
Power BI enhances interactivity through:
Slicers: Allow users to filter data dynamically by making selections.
Styles: Vertical list, tile buttons, or dropdown.
Selection: Single select (radio buttons) or multi-select (holding Ctrl/Cmd). “Show select all” option can be enabled.
Types: Can be used for categorical data (e.g., job title), numerical ranges (e.g., salary), or date ranges (e.g., “between” dates, “relative date/time”).
Search: Can be enabled for large lists of values.
Sync Slicers: Allows a single slicer’s selection to apply across multiple report pages.
Buttons: Can be configured to perform various actions.
Page Navigation: Navigate to different report pages.
Q&A Button: Provides a tool tip to guide users on how to interact (e.g., “press control while clicking a button”).
Clear All Slicers: Resets all slicers on a page or report, providing an intuitive way to clear filters.
Apply All Slicers: Delays filtering until the button is clicked, useful for large datasets to improve performance.
Bookmark Actions: Activate specific bookmarks.
Bookmarks: Capture the current state of a report page, including applied filters, visible visuals, and visual properties. They allow users to quickly switch between different views or hide/show elements.
Can be set to preserve data (filters) or display (visual visibility) properties.
Drill Through: Enables users to navigate from one report page to another, passing filter context based on a selected data point. For example, clicking on a job title in one report can show a detailed view for only that job title on a drill-through page. A “back arrow” button is automatically added for navigation.
Formatting and Design Principles
Effective visualization in Power BI extends beyond just selecting chart types to thoughtful design and formatting.
Titles and Labels: Descriptive titles and clear labels are crucial for guiding the user’s understanding.
Coloring: Use color palettes consistently and strategically to draw attention to key insights. Avoid excessive or distracting colors. Dark mode themes are an option.
Font and Size: Adjust font sizes for readability.
Decimal Places and Display Units: Format numerical values appropriately (e.g., currency, thousands).
Gridlines: Often removed to reduce visual clutter.
Tooltips: Enhance interactivity by displaying additional information when hovering over data points.
Borders and Shadows: Can be used to group related visuals and add visual appeal.
Backgrounds: Can be made transparent for visuals to sit on custom backgrounds.
Edit Interactions: Control how visuals interact with each other when filtered or highlighted.
Dashboard Design Best Practices:Problem-solving and Audience Focus: Always design with a clear problem and target audience in mind.
Simplicity: Keep designs simple and avoid overwhelming users with too many visuals or colors.
Symmetry and Layout: Symmetrical layouts, often with KPIs at the top and related visuals below, can improve intuitiveness.
Visual Cues: Use background shapes or grouping to create visual cues that associate related visuals and parameters.
Performance Analyzer: A tool to check the loading times of visuals and identify bottlenecks in report performance.
Overall, data visualization in Power BI is a comprehensive process that involves selecting appropriate visuals, applying detailed formatting, and incorporating interactive elements, all while adhering to best practices for effective dashboard design.
DAX: Power BI’s Calculation Engine
DAX (Data Analysis Expressions) is a powerful formula language used in Power BI for performing calculations on data that has already been loaded into the data model. It is distinct from M language, which is a programming language used in Power Query for data manipulation and transformation before data is loaded into Power BI.
Purpose and Usage of DAX DAX allows users to add calculations to their data models, enabling more in-depth analysis and dynamic reporting. It is not exclusive to Power BI and can also be used in other Microsoft tools like Microsoft Excel, Microsoft Fabric, SQL Server Analysis Services, and Azure Analysis Services. DAX is particularly effective for performing calculations on large datasets.
Comparison with Excel Functions DAX functions share a similar syntax with Excel functions, but they operate differently. While Excel functions typically operate on a single cell or a range of cells, DAX can perform calculations on single rows, entire columns, or even whole tables. For instance, the SUM function in DAX is similar to Excel’s SUM, but in DAX, you typically insert a column name rather than a cell or range.
Comparison with M Language DAX is a formula language (like SUM, AVERAGE), whereas M language is a more verbose programming language. Functions and structures in DAX are not interchangeable with those in M language; for example, concatenating text in DAX uses TEXTCOMBINE instead of a direct concatenation symbol as might be seen in M language.
Types of DAX Functions and Their Applications DAX offers a wide range of functions categorized into:
Aggregation Functions: Such as AVERAGE, COUNT, MAX, MIN, and SUM.
Date and Time Functions: Including those for extracting day, minute, or month, and functions like CALENDAR and CALENDARAUTO for creating date tables.
Logical Functions: For operations like IF, AND, or OR statements.
Math and Trig Functions: For mathematical calculations.
DAX can be applied in Power BI using four primary methods:
Calculated Columns:
Calculated columns add new columns to an existing table in the data model.
They are computed immediately upon data import and are visible in both the data and report views.
Example: Creating a salary hour adjusted V2 column by multiplying salary hour average by 2080 (40 hours/week * 52 weeks/year). Another example is salary year and hour V2 which selects a value from either salary year average or salary hour adjusted V2 if the first is null.
Recommendation: While possible, it is generally recommended to perform data transformations and create new columns in Power Query using custom columns instead of DAX calculated columns. Power Query processes data before loading, leading to more efficient compression, smaller file sizes, and quicker data model operations. It also keeps all data cleaning in one centralized place.
Calculated Tables:
Calculated tables create entirely new tables within the data model based on DAX expressions.
They are useful for creating lookup tables (e.g., job title dim using the DISTINCT function to get unique job titles) or date tables.
Example: Date Dimensional Table: A date dim table can be created using CALENDAR (specifying start and end dates) or CALENDARAUTO (which automatically detects dates from the model). Additional columns like year, month number, month name, weekday name, week number, and weekday number can be added using functions like YEAR, MONTH, FORMAT, and WEEKNUM.
Date tables can be marked as such in Power BI to enable automatic date-related functionalities. Sorting columns (e.g., weekday name by weekday number) helps ensure correct visual order.
Recommendation: Similar to calculated columns, creating and cleaning tables is often more beneficial to do in Power Query.
Explicit Measures:
Measures are dynamic calculations that are not computed until they are queried (e.g., when a visual is built). They are not visible in the table view.
They provide a “single source of truth” for calculations across different reports, preventing inconsistencies that can arise from implicit measures (where aggregation is chosen directly in a visual).
Creation: Measures are defined with a name followed by an equals sign and a DAX formula (e.g., Job Count = COUNTROWS(‘Job Postings Fact’)).
Organization: Best practice is to create a dedicated table (e.g., _Measures) to store all explicit measures, improving organization.
Examples:Job Count: Calculates the total number of job postings using COUNTROWS.
Median Yearly Salary: Calculates the median yearly salary using the MEDIAN function. Measures can be pre-formatted (e.g., currency, decimal places).
Skill Count: Counts the total number of skills for job postings using COUNTROWS(‘Skills Job Dim’).
Skills Per Job: Calculates the ratio of Skill Count to Job Count using the DIVIDE function for safe division.
Job Percent: Calculates the percentage likelihood of a skill being in a job posting, demonstrating the CALCULATE and ALLSELECTED functions to manage filter context.
Median Yearly Take-Home Pay: Uses a numeric parameter to deduct a user-defined tax rate from the median yearly salary.
Commentation: Measures should be commented using // for single-line comments or /* … */ for multi-line comments to document their purpose and logic.
Parameters (using DAX):
Parameters allow end-users to dynamically change inputs in a chart without needing to modify the underlying DAX code.
Field Parameters:Enable users to dynamically switch between different columns or measures on an axis of a visual.
Example: A select category parameter can let users switch the Y-axis of a chart between Job Title, Country, Skills, or Company. A select measure parameter can switch between Median Yearly Salary and Job Count on the X-axis.
Numeric Parameters:Allow for “what-if” analysis by providing a slider or input field for numerical values.
Example: A select deduction rate parameter allows users to adjust a tax rate (e.g., from 0% to 50%) to see its impact on “take-home pay” calculations.
Context in DAX Understanding evaluation contexts is crucial for complex DAX calculations:
Row Context (Lowest Precedence): Refers to the current row a calculation is being applied to. Calculations in calculated columns typically operate at the row context level. The RELATEDTABLE function can be used to count related rows for the current row context.
Query Context: Determines which rows from a table are included in a calculation based on visual selections, relationships, slicers, and cross-filtering. This is an abstract context derived from the visual itself.
Filter Context (Highest Precedence): Applied on top of query and row contexts. It can explicitly modify the calculation environment, overriding other contexts. The CALCULATE function is a powerful tool used to explicitly modify filter context. The ALL and ALLSELECTED functions can remove existing filters from columns or tables within a CALCULATE expression.
DAX Query View The DAX query view in Power BI Desktop allows users to write and execute DAX queries to evaluate measures or view column statistics. It can also be used to define and evaluate measures, and even update the data model. While it requires some DAX knowledge, it can be assisted by quick queries for basic evaluations.
Learning and Troubleshooting DAX For learning and troubleshooting DAX, the source recommends consulting official DAX documentation and utilizing AI chatbots like Google Gemini or ChatGPT, which can provide step-by-step instructions and code for DAX formulas. Additional courses on DAX are also recommended for deeper learning.
Power BI Dashboard Design and Sharing Guide
Dashboard creation, particularly using Power BI, involves a structured approach that prioritizes understanding the user’s needs, careful planning, and effective utilization of Power BI’s features for data visualization and interaction.
What is a Dashboard? Analytical dashboards are inspired by car dashboards, providing users with quick insights at a glance. They consolidate key information and visuals to help users understand data and identify patterns or anomalies efficiently.
Tools for Dashboard Creation Power BI Desktop is a free and popular business intelligence tool specifically designed for creating dashboards. While Excel can be used to build dashboards, it comes with limitations regarding data manipulation, formula complexity for interactive elements, and sharing, which Power BI aims to solve. Power BI is noted as the second most popular BI tool and is gaining popularity over competitors like Tableau.
Power BI Ecosystem for Dashboard Creation and Sharing The Power BI ecosystem consists primarily of two parts:
Power BI Desktop (App): This is the application where dashboards are built. It’s free to install and allows users to load data, build reports (which contain multiple pages, unlike Excel’s worksheets), and design visualizations.
Power BI Service: This is a cloud-based platform accessible via an internet browser, designed for sharing dashboards. Dashboards published to the Power BI Service can be accessed by co-workers within shared workspaces, or even published to the web for public access if the data is not confidential. While there is a free option, it is very limited; a Power BI Pro license (paid) is often needed for sharing and collaboration. Microsoft Fabric is also an umbrella platform that consolidates various data tools, including Power BI.
Best Practices for Dashboard Design To create effective dashboards that users will actually utilize, consider the following:
Define the Problem and Audience: Always ask: “What problem are we trying to solve with this dashboard?” and “Who are we designing this dashboard for?”. Dashboards are ineffective if they don’t address the specific concerns or problems of the end consumer.
Simplicity and Clarity: Avoid overwhelming dashboards with too many visuals or distracting colors. Simple color palettes help guide the user’s eye to important information.
Key Performance Indicators (KPIs): Place cards displaying key metrics (KPIs) prominently at the top of the dashboard, as they provide immediate value and draw attention.
Symmetry and Layout: A symmetrical layout, often with KPIs at the top and equally spaced graphs below, can improve readability and intuitiveness. Visual cues like backgrounds and boxes can group related elements and draw attention.
Interactivity: Incorporate features that allow users to interact with the data, such as slicers, buttons, and drill-through options.
Planning and Rough Drafting Before building, it’s recommended to sketch out a rough design of the dashboard, or at least rough draft it within Power BI itself. This allows for early feedback from stakeholders and helps ensure the design aligns with the intended purpose.
Steps in Dashboard Creation (Power BI Desktop)
Start a New Page: Create a dedicated page for your dashboard.
Add a Title: Insert a text box for the dashboard title, formatting it appropriately for size and boldness.
Insert Slicers:Slicers enable users to interactively filter data.
Types include vertical list, tile, and dropdown.
Enable search functionality for long lists.
Allow multi-select (default with Ctrl/Cmd) or enforce single-select.
The “Show select all” option is useful.
Date and numeric slicers (between, before, after, relative) can be added, though some date slicer types may have known bugs.
Slicers can be synchronized across multiple pages using the “Sync slicers” pane.
A “Clear all slicers” button can be added for user convenience, often styled with visual cues like shadows and rounded corners. An “Apply all slicers” button can be useful for very large datasets to control refresh performance.
Add Cards (KPIs):Use card visuals (e.g., “Card (new)”) to display single, prominent data points like “Job Count,” “Median Yearly Salary,” or “Skills Per Job”.
New card visuals can display multiple fields.
Format callout values, labels, and remove borders as needed.
Other card types like Gauge cards (showing min, max, target values) and Multi-row cards are available. KPI cards show a value with a trend and color-coding based on goals.
Insert Charts/Visualizations:Choose appropriate chart types (e.g., bar charts for comparison, line charts for trends over time, scatter plots for relationships, tree maps for hierarchical breakdown).
Formatting: Adjust axes (labels, values, ranges), legends, titles, and data labels for clarity.
Conditional Formatting: Use data bars, background colors, or icons to highlight specific values based on conditions. This helps draw the user’s attention.
Trend Lines: Add trend lines to visualize patterns in data, especially in line charts or scatter plots.
Matrices and Tables: These are useful for displaying detailed data and can include conditional formatting and sparklines (mini-charts within cells) for quick trends.
Implement Drill-through: This advanced feature allows users to right-click on a visual and navigate to a separate, detailed page filtered by their selection. A dedicated button can also be created for drill-through.
Use Parameters:Field Parameters: Allow end-users to dynamically switch columns or measures displayed in a visual (e.g., changing a chart’s axis from “Job Title” to “Country” or “Skill”).
Numeric Parameters: Enable “what-if” analysis by allowing users to adjust numerical inputs (e.g., a tax deduction rate) via a slider, which then affects calculations in visuals.
Add Backgrounds and Organize Visually: Insert shapes (e.g., rounded rectangles) behind visuals to create visual groupings and a cohesive design. Set visual backgrounds to transparent to reveal these background shapes.
Hide Header Icons: Turn off header icons on visuals by making their transparency 100% to clean up the design.
Save Frequently: Power BI Desktop does not have an autosave feature, so frequent saving is crucial to prevent data loss.
Data Preparation for Dashboards Effective dashboards rely on well-prepared data.
Power Query (M Language): Used for Extract, Transform, Load (ETL) operations before data is loaded into the Power BI data model. It’s recommended for data cleaning, shaping, and creating new columns or tables (e.g., combining data from multiple files in a folder, unpivoting data, cleaning text). Power Query transformations lead to more efficient data compression and smaller file sizes.
DAX (Data Analysis Expressions): A formula language used after data is loaded into the data model to add calculations. It is used for creating calculated columns, calculated tables, and explicit measures. While calculated columns and tables can be created with DAX, it’s generally recommended to do data transformations in Power Query for better performance and organization.
Explicit Measures: Dynamic calculations that are computed at query runtime (e.g., when a visual is built), providing a “single source of truth” for consistent calculations across reports. They are preferred over implicit measures (automatic aggregations) for complexity and control. Measures can be organized in a dedicated table and thoroughly commented for documentation.
Context in DAX: Understanding row context (individual row calculation), query context (visual/filter selection), and filter context (explicit modification, highest precedence) is crucial for complex DAX calculations.
Sharing Dashboards After creation, dashboards can be shared in several ways:
Power BI File (.pbix): The dashboard file can be directly shared, but the recipient needs Power BI Desktop to open it, and version control can be an issue.
Power BI Service: Publishing to the Power BI Service allows for centralized access, sharing with specific groups (workspaces), and embedding reports (e.g., into websites). Admin settings may be required to enable features like “Publish to Web”.
GitHub: An online repository to store project files, including the Power BI file and a “readme” document that explains the project, showcases skills, and can link directly to the interactive dashboard in the Power BI Service. This method allows for version control and provides a professional portfolio for showcasing work.
LinkedIn: Projects hosted on platforms like GitHub or the Power BI Service can be linked and showcased on LinkedIn profiles, or shared directly via posts, to gain visibility and potential career opportunities.
Power BI for Data Analytics – Full Course for Beginners
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This document serves as a transcript for a video tutorial focused on Microsoft Power BI, a business intelligence tool. The tutorial, led by Kevin, explains how to download and install Power BI, import data from various sources like Excel spreadsheets and the web, and transform that data for analysis. It then guides users through creating various visualizations such as bar charts, line charts, and maps, and demonstrates how to interact with and slice the data within the reports. Finally, the document covers customizing the report’s appearance and the process of saving and publishing the report for sharing and collaboration within the Power BI service.
Power BI: From Data to Insightful Reports
Microsoft Power BI is a tool used to gain insights from data. It was utilized at Microsoft to analyze business performance and make decisions based on that performance. Power BI Desktop is entirely free to download and install, regardless of whether you have an enterprise or commercial account.
The general workflow for using Power BI, as introduced in a tutorial, involves:
Downloading and installing Power BI.
Importing sample data.
Creating visualizations and reports.
Saving, publishing, and sharing these reports with others.
This overview serves as a “101” or introduction to Power BI.
Installation Methods The easiest and recommended way to install Power BI is by clicking the “download free” button, which opens the Microsoft Store to the Power BI download page. Benefits of installing via the Microsoft Store include automatic updates, quicker downloads of only changed components, and the ability for any user (not just an admin) to install it. Alternatively, you can click “see download or language options” to download an executable (.EXE) file and install it manually, though this method does not use the Microsoft Store.
Getting Started and Interface After installation, you can launch Power BI, which first displays a welcome screen. The most crucial initial step is to “get data,” as visualizations cannot be created without it. The welcome screen also shows recent data sources and previously created reports for quick access. Power BI offers training content, including videos and tutorials, to help users get up to speed.
The main interface of Power BI Desktop includes several views:
Report View: This is the default view, a blank canvas where visuals like charts, tables, or maps are created. On the right side, there are “fields” (all available data columns) and “visuals” (different types of visuals that can be built) panes.
Data View: Clicking this option displays a spreadsheet-like view of all imported and transformed data.
Model View: This view shows the relationships between different data tables. For example, if two tables are joined based on a common field like “country name,” a line will connect them, highlighting the relationship when hovered over.
Data Import and Transformation Power BI can pull data from an extensive list of sources, including Excel spreadsheets, SQL databases, web sources (like Wikipedia articles), and Kusto queries. For example, data can be imported from an Excel spreadsheet containing revenue, cost, and profit data, along with details like country, product, sales, and dates. Additionally, data from the web, such as a Wikipedia article listing countries and their populations, can be pulled in.
Data transformation is a key step, allowing users to modify and select data before it’s brought into Power BI. This process opens the Power Query editor, where data is “shaped” and a data model is built. Examples of transformations include:
Filtering out specific data, such as removing “Fortune cookies” from product analysis. These filtered steps can also be undone.
Changing data types, like converting “units sold” from decimals to whole numbers.
Renaming columns for conciseness, such as changing “month name” to “month”.
Removing unnecessary columns, like “percent of world population,” “date,” “source,” or “rank” from imported web data.
Filtering rows to include only relevant data, such as specific countries where a company has locations (e.g., Canada, France, Germany, Mexico, United States).
Replacing values within columns, like removing an extra “D” from “United StatesD”.
Connecting Data Sources Independent data tables can be connected or joined. This is done using the “merge queries” function, allowing tables to be linked based on common fields, such as “country name” between cookie sales data and country populations data. This enables the association of data from one source (e.g., population) with another (e.g., cookie sales).
Creating and Formatting Visualizations After data is loaded and modeled, visualizations can be created on the report canvas. Users can insert a text box to add a title to the report. To create a visual, users can simply click on a data field (e.g., “profit” and “date”) and Power BI will suggest a default chart type (e.g., a bar chart). This can then be changed to another type, such as a line chart for profit by date. Other common visualizations include:
Map visualization: Automatically inserted when country data is selected, showing locations and allowing profit data to be displayed on the map, with dot sizes indicating profit levels. Can be switched to a treemap to show profit by country hierarchy.
Table: Allows presentation of data like country, population, and units sold in a structured format.
Bar chart: Used to show sales or profit by product, easily illustrating which products generate the most profit.
Visualizations can be formatted by clicking on the “format” option (paint roller icon) in the visualization pane. This allows adjustment of various elements, such as increasing title text size, to match company branding or preference. Reports can also have multiple pages.
Slicing and Sharing Data Power BI reports allow for easy data slicing (filtering). A “slicer” visual can be added to a report, where users can select specific categories (e.g., country name) to filter all other visuals on the page. Clicking directly on elements within other visuals, such as a country on a map or in a table, can also serve as a quick way to slice the data.
Once a report is complete, it can be saved. The “power” of Power BI comes from its ability to share reports with others. Reports are published to the Power BI service (powerbi.com). From there, the report can be opened in the Power BI service, where it can still be filtered. The share dialog allows granting access to specific individuals via email, setting permissions (like allowing sharing or creating new content based on datasets), and sending email notifications.
Power BI: Data Transformation and Modeling with Power Query
Data transformation in Power BI is a crucial step that allows users to modify and select data before it is loaded into the Power BI environment. This process is carried out in the Power Query editor, where data is “shaped” and a data model is built.
Here are the key aspects and examples of data transformation discussed:
Purpose of Transformation
It enables users to modify their data and choose exactly what data they want to bring into Power BI.
It helps in building a structured data model suitable for analysis and visualization.
Accessing the Power Query Editor
After selecting data from a source (e.g., an Excel spreadsheet), users can choose “Transform data” instead of “Load” to open the Power Query editor.
Common Transformation Actions
Filtering Data: Users can filter out specific rows or values that are not relevant to the analysis. For example, a product line like “Fortune cookies” might be removed from the analysis if it’s not profitable or is distracting from other products. These filtered steps can also be undone later if needed.
Changing Data Types: Data types can be adjusted to ensure accuracy and usability. For instance, “units sold” might be changed from decimal numbers to whole numbers if fractional sales don’t make sense.
Renaming Columns: Columns can be renamed for conciseness or clarity, such as changing “month name” to simply “month”.
Removing Unnecessary Columns: Columns that are not needed for the analysis can be removed, such as “percent of world population,” “date,” “source,” or “rank” from a web-imported dataset.
Filtering Rows to Specific Subsets: Users can filter down rows to include only relevant data, such as selecting only countries where a company has locations (e.g., Canada, France, Germany, Mexico, United States).
Replacing Values: Specific values within columns can be replaced to correct inconsistencies, like removing an extra “D” from “United StatesD”.
Tracking Transformations (Applied Steps)
As changes are made in the Power Query editor, each transformation is recorded in a section called “applied steps” on the right-hand side of the interface. This allows users to see all the modifications made to the data and also provides the option to remove a step if it was made unintentionally.
Connecting Independent Data Sources (Merging Queries)
Power BI allows users to connect or join independent data tables, such as linking cookie sales data with country population data from a Wikipedia article.
This is done using the “merge queries” function, where tables are joined based on a common field (e.g., “country name”).
The “Model View” in Power BI Desktop visually represents these relationships between data tables, showing lines connecting tables that are joined.
Once all transformations are complete and the data model is built, users click “close and apply” to load the refined data into Power BI, ready for report creation.
Power BI: Crafting Interactive Reports and Visualizations
After data transformation and modeling, Power BI Desktop provides a Report View, which serves as a blank canvas where users create and arrange various visuals such as charts, tables, or maps. This blank area is referred to as the report editor.
On the right side of the Power BI Desktop interface, there are two key panes that facilitate report visualization:
Fields Pane: This pane displays all available data columns (called fields) from the imported and transformed data. Users can drag and drop these fields onto the canvas or select them to build visuals.
Visuals Pane: Located to the left of the fields pane, this section offers various types of visuals that can be built using the data.
Here’s a breakdown of how report visualization works:
Creating Visualizations
Starting a Visual: To create a visual, users can simply click on relevant data fields in the “fields” pane, such as “profit” and “date”.
Default Suggestions: Power BI often predicts and inserts a default chart type that it deems most likely suitable for the selected data, like a bar chart for profit by date.
Changing Visual Types: Users can easily change the chart type from the “visualizations” pane if the default doesn’t align with their needs (e.g., switching a bar chart to a line chart for profit by date).
Defining Visual Elements: The visualizations pane also allows users to define different elements of the chart, such as what fields serve as the axis, values, or legend.
Examples of Visualizations:
Text Box: Can be inserted to add a title to the report, providing context (e.g., “Kevin Cookie Company performance report”).
Line Chart: Useful for showing trends over time, such as profit by date.
Map Visualization: Automatically inserted when geographical data like “country” is selected. It shows locations with dots, and profit data can be dragged onto the map to represent profit levels by dot size.
Treemap: An alternative to the map view, it can display hierarchical data like profit by country, illustrating which country had the most or least profit.
Table: Allows presentation of data in a structured, spreadsheet-like format, such as country, population, and units sold. Users can drag and drop fields into the table.
Bar Chart: Used to show comparisons, such as sales or profit by product, clearly indicating top-performing products.
Formatting and Appearance
Themes: The “View” tab in the ribbon provides different themes (e.g., “executive” theme) that can be applied to change the overall look and feel of the report, including color schemes, to make it appear more professional.
Individual Visual Formatting: Each visual can be formatted individually by clicking on the “format” option (represented by a paint roller icon) within the visualization pane. This allows users to adjust elements like title text size or other visual properties to match company branding or preference.
Multiple Pages: Reports can span multiple pages, allowing for comprehensive data presentation.
Slicing and Interacting with Data
Slicer Visual: A “slicer” visual can be added to the report, typically based on a categorical field like “country name”. Selecting a specific category in the slicer will filter all other visuals on the page to reflect only that selection.
Direct Interaction with Visuals: Users can also slice data by directly clicking on elements within other visuals, such as clicking on a country on a map or in a table. This provides a quick way to filter the entire report based on that selection. Clicking a blank area or re-clicking a selection can undo the filter.
Saving and Sharing Reports Once a report with visualizations is complete, it can be saved locally. The “power” of Power BI is realized when reports are published to the Power BI service (powerbi.com), enabling sharing and collaboration. In the Power BI service, reports remain interactive and can still be filtered. The share dialog allows users to grant access to specific individuals via email, set permissions (e.g., allowing sharing or creating new content based on datasets), and send email notifications.
Power BI: Collaborative Data Sharing Essentials
Data sharing in Power BI is a fundamental aspect that unlocks the full potential of the platform, moving beyond individual analysis to collaborative insights. While reports can be created and saved locally for personal use, the true “power” of Power BI lies in its ability to enable collaboration and allow others to interact with the created visualizations.
Here’s a discussion on data sharing:
Purpose of Sharing: The primary goal of sharing is to allow other individuals to view and interact with the visualizations and reports you’ve created. This facilitates collective analysis and decision-making based on the data.
The Sharing Process:
Local Saving: After creating a report and its visualizations, it is initially saved locally on your desktop as a .pbix file. At this stage, it can be used for individual analysis.
Publishing to Power BI Service: To share the report, it must first be “published”. This is done by navigating to the “file” menu and selecting the “publish” option, then choosing “publish to Power BI”.
Power BI Service (powerbi.com): The Power BI service is the online platform where all published reports are housed. Once published successfully, the report becomes accessible on powerbi.com. Reports opened in the Power BI service remain interactive, allowing users to filter data just as they would in the Power BI desktop application.
Sharing Options and Permissions:
From the Power BI service, you can click on the “share” button, typically found in the top right-hand corner.
This opens a “share dialog” that provides various options for granting access.
You can grant access to specific individuals by entering their email addresses.
Crucially, you can define permissions for those you share with:
You can allow recipients to share the report with others.
You can enable them to create new content based on the underlying datasets.
An option to send an email notification to the recipients is also available, which can include any changes made to the report.
Power BI Report Customization Guide
Report customization in Power BI allows users to refine the appearance and layout of their reports to enhance clarity, professionalism, and alignment with specific branding or preferences. This process goes beyond merely creating visualizations and focuses on making the report aesthetically pleasing and user-friendly.
Key aspects of report customization include:
Adding Contextual Elements:
Titles: Users can insert text boxes to add a main title to the report, providing immediate context (e.g., “Kevin Cookie Company performance report”). These titles can be resized and positioned to span the entire report.
Formatting Visuals:
Changing Chart Types: While Power BI often suggests a default chart type (e.g., bar chart) for selected data, users can easily switch to other visual types (e.g., line chart, treemap, map, table, bar chart) from the “visualizations” pane to better represent their data.
Defining Visual Elements: Within the visualization pane, users can explicitly define what fields should serve as the axis, values, or legend for a chart. They can also add secondary values.
Individual Visual Formatting: Each visual can be formatted independently. By selecting a visual and clicking on the “format” option (represented by a paint roller icon) in the visualizations pane, users can adjust various elements. For instance, the title text size of a visual can be increased to make it stand out. This allows users to match the visuals to their company’s brand, look, and feel.
Applying Themes:
Power BI provides different themes (e.g., “executive” theme) under the “View” tab on the ribbon. Applying a theme changes the overall color scheme and appearance of the report, contributing to a more professional look.
Organizing Layout:
Users can drag and drop visuals around the report editor (the blank canvas) to organize them as desired.
Reports are not limited to a single page; users can add multiple pages to their report to accommodate extensive data and different views. Pages can also be renamed.
By leveraging these customization features, users can transform raw data visualizations into polished, insightful reports that effectively communicate their findings. Once satisfied with the customization, the report can be saved locally and then published to the Power BI service for sharing.
How to use Microsoft Power BI – Tutorial for Beginners
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This comprehensive guide provides an in-depth look into Power BI, a powerful business intelligence tool from Microsoft. It details the step-by-step process of installing and utilizing Power BI Desktop, covering essential data manipulation techniques such as text, numerical, date, and time transformations. The sources further explore advanced concepts like merging and appending queries, managing data relationships through primary and foreign keys, and understanding different cardinalities. Finally, the guide concludes with a focus on data visualization, demonstrating the creation of various charts and filters, and the process of publishing dashboards to Power BI service.
Mastering Power BI: Data Analysis and Visualization
Power BI, developed by Microsoft, is a powerful business analytics tool designed for analyzing and visualizing data in insightful and interactive ways. It has gained popularity due to its user-friendly interface and robust features. Power BI is suitable for business analysts, data analysts, data scientists, or anyone who wants to work efficiently with data, providing necessary skills and knowledge to become proficient in data handling.
Key Capabilities and Features Power BI allows users to transform, clean, analyze, and visualize data. It enables effortless data gathering from various platforms, including Excel, CSV files, different databases like MySQL, Postgres, Oracle, or other datasets. It is noted for its strong visualization capabilities, offering a wide range of charts such as bar plots, pie charts, and stack plots. Unlike Excel, Power BI has the capacity to work with large datasets and offers numerous deployment options. The end result of working with Power BI is often the creation of interactive and visually appealing dashboards.
Installation and Interface To install Power BI Desktop for Windows, users typically download the executable file from Microsoft’s website. Once installed, its user interface is very similar to Excel, making it easy for Excel users to adapt. Power BI also offers tutorials, blogs, and forums for support. While desktop usage is common, Power BI reports can also be created and viewed on mobile phones. A company domain email address is generally required for login, though free business emails can be created for this purpose.
Data Handling and Transformation Power BI provides various data connectors to import data from diverse sources. These include:
Files: Excel workbooks, Text/CSV files, XML, JSON, and PDF. Data can also be pulled from folders.
Databases: SQL Server, Oracle, Postgres, MySQL, and other databases.
Power Platform: Existing datasets loaded in Power Platform can be accessed.
Cloud Services (Azure): Azure SQL Database and other Azure options are available.
Online Services: Google Analytics, GitHub, LinkedIn Sales Navigator, and many more.
Other: Data can be scrapped from the web, or connected to Hadoop, Spark, R script, and Python script.
Power BI offers extensive tools for data transformation:
Text Tools: Used for text manipulations like converting to lower/upper case, trimming whitespace, replacing values, combining values (concatenate), finding specific text, formatting text, and extracting specific parts of text using delimiters (e.g., username from an email address). These tools can either transform the existing column or add a new column with the transformed data.
Numerical Tools: Used for mathematical operations, statistics (maximum, median, average, standard deviation, count), rounding values, and applying filters. These can be applied by adding a new column or transforming an existing one.
Date and Time Tools: Essential for analyzing time-based patterns, such as identifying peak order times or days. They allow extraction of year, month, day, age calculations, and conversion of time formats (e.g., 24-hour to 12-hour). Regional settings may need adjustment for proper date parsing.
Pivoting and Unpivoting: These techniques allow converting rows to columns (pivoting) and columns to rows (unpivoting) to restructure data for easier analysis.
Conditional Columns: New columns can be created based on specified conditions, similar to conditional statements in programming.
Creating Tables: Users can manually create tables within Power BI by entering data directly.
DAX (Data Analysis Expressions) DAX is a collection of functions, operators, and constants used in Power BI to create new data or transform existing data.
Purpose: DAX is used to calculate complex formulas, create measures, develop time intelligence calculations, and dynamically or statically analyze data.
Calculated Columns vs. Measures:
Calculated Columns: Create a new column in the data model, adding static data that consumes memory and updates when new data is added. They work row by row.
Measures: Dynamically calculate values at runtime, primarily for aggregations like sum, count, or average, and are used to create visual reports. They do not consume memory for each row. Measures can be implicit (automatically created by Power BI) or explicit (user-defined).
DAX Functions: Broadly categorized into:
Date and Time: Work on date-related calculations (e.g., NOW, YEAR, WEEKDAY).
Text Functions: Manipulate text strings (e.g., CONCATENATE, FIND, FORMAT, LEFT, LEN, LOWER, REPLACE, RIGHT, TRIM, UPPER).
Informative Functions: Provide information about data types and handle errors (e.g., IFERROR, IFNA).
Filter Functions: Filter data based on conditions (e.g., FILTER, CALCULATETABLE).
Math and Trigonometric Functions: Perform mathematical calculations (e.g., ABS, SIN, COS, TAN).
Statistical Functions: Used for statistical calculations (e.g., percentile, standard deviation).
Financial Functions: Aid in financial computations.
DAX Syntax: Typically involves a column name, an equals sign, a function, and then references to table and column names (e.g., ColumnName = Function(TableName[ColumnName])).
Operators: Used in DAX formulas for various purposes:
Arithmetic: +, -, *, / for mathematical operations.
Logical: AND, OR, NOT for combining or negating conditions.
Concatenation: & for joining text from multiple columns.
Reference: TableName[ColumnName] for referencing specific columns.
Parentheses: () for controlling execution order of formulas.
Miscellaneous: : (colon) for separating elements in date and time.
Data Modeling and Relationships Data modeling is crucial for connecting different tables and sources of data within Power BI, especially in companies with diverse datasets (e.g., product, sales, customer details).
Merge and Append Queries:
Merge: Combines two tables based on a common key (like a primary key and foreign key), increasing the number of columns, similar to SQL joins (inner, left, right, full, anti-joins).
Append: Stacks rows from multiple tables with similar columns into one table, increasing the number of rows.
Keys:
Primary Key: A unique identifier for each record in a table (e.g., product ID, Aadhaar card number).
Foreign Key: A column in one table that refers to the primary key in another table, allowing for duplicate values.
Cardinality: Describes the nature of the relationship between two tables based on primary and foreign keys.
One-to-one (1:1): Both tables have unique primary keys related to each other.
One-to-many (1:*): One table has a primary key, and the other has a foreign key that can be repeated multiple times.
Many-to-one (*:1): The reverse of one-to-many, where the foreign key is on the “many” side and the primary key is on the “one” side.
Many-to-many (:): Both tables have foreign keys that can be repeated.
Cross-Filter Direction: Defines the flow of data filtering between related tables (single or double direction).
Managing Relationships: Power BI can automatically detect relationships. Users can manually manage and edit these relationships, including setting cardinality and cross-filter direction, and activating/deactivating multiple relationships between tables.
Data Visualization Visualization is a critical step in Power BI, revealing patterns and trends that are not apparent in raw row and column data.
Dashboard Elements: The report section is where visuals are built using fields (columns from tables) that can be dragged and dropped.
Visual Types: Power BI offers a wide array of built-in visuals:
Charts: Stacked bar, stacked column, clustered bar, clustered column, line, area, pie, scatter, donut, funnel, map, tree map.
Matrices: Powerful tools for visualizing data across different parameters and dimensions, allowing drill-down into subcategories.
Cards: Number cards (for highlighting single large numbers) and multi-row cards (for multiple pieces of information).
KPI Visuals: Show key performance indicators, often with trend lines, useful for comparing current and past performance.
Custom Visuals: Users can import additional visuals from the Power BI marketplace (e.g., boxplot, flow map, calendar).
Formatting and Customization: Visuals can be extensively formatted, including changing font size, colors, titles, background, borders, data labels, and themes.
Filtering:
Filter Pane: Allows applying filters on a specific visual, on the current page, or across all pages. Advanced filtering options like “greater than” or “less than” are available.
Slicers: Interactive tools for filtering data across the entire dashboard or different pages. They can display data as lists, dropdowns, or ranges (e.g., date sliders).
Sync Slicers: Allows the same filter to be applied consistently across multiple pages.
Interactivity Tools:
Buttons: Can be added to navigate between pages or trigger other actions.
Bookmarks: Capture the current state of a report page (e.g., filters applied, visuals visible) allowing users to return to that view.
Images: Can be inserted for branding (e.g., logos) or icons.
Publishing and Sharing Once a dashboard is complete, it can be published to Power BI service, which typically requires a user to be signed in. Published reports retain their interactivity and can be viewed online, shared with co-workers, or even published to the web without security if desired. Power BI also allows creating a mobile layout for dashboards, optimizing them for phone viewing.
Power BI: Data Analysis from Gathering to Visualization
Data analysis is a critical process for extracting insights and patterns from raw data to inform decision-making, and Power BI serves as a powerful business analytics tool to facilitate this. It involves several key steps, from data gathering and cleaning to sophisticated analysis and visualization.
The Role of a Data Analyst
A data analyst’s primary responsibility is to gather, interpret, process, and clean data, ultimately representing it in a graphical format. This graphical representation allows business strategists to understand the information better and use it to grow their business. Power BI is designed to provide the necessary skills and knowledge to become proficient in working efficiently with data.
Key Steps in Data Analysis using Power BI
Data Gathering (Data Connectors): Power BI offers extensive data connectors that allow users to effortlessly gather data from various platforms. These sources include:
Files: Excel workbooks, Text/CSV files, XML, JSON, and PDF. Data can also be pulled from folders.
Databases: SQL Server, Oracle, Postgres, and MySQL are among many databases from which data can be extracted.
Power Platform: Existing datasets loaded in Power Platform can be directly accessed.
Cloud Services (Azure): Azure SQL Database and other Azure options enable data retrieval from the cloud.
Online Services: Google Analytics, GitHub repositories, and LinkedIn Sales Navigator are examples of online services that can connect to Power BI.
Other: Data can be obtained by scrapping from the web, or connecting to Hadoop, Spark, R scripts, and Python scripts.
Data Transformation and Cleaning: Once data is gathered, Power BI provides robust tools for cleaning and processing it. This includes:
Text Tools: Used for manipulations such as converting text to lower or upper case, trimming whitespace, replacing values, combining values (concatenate), finding specific text, formatting text, and extracting parts of text using delimiters (e.g., username from an email address). These tools can either transform an existing column or add a new one with the transformed data.
Numerical Tools: Applicable for mathematical operations, statistics (maximum, median, average, standard deviation, count), rounding values, and applying filters. Like text tools, they can transform existing columns or create new ones.
Date and Time Tools: Essential for analyzing time-based patterns (e.g., peak order times or days). They allow extraction of year, month, day, and age calculations, and conversion of time formats (e.g., 24-hour to 12-hour). Regional settings may need adjustment for proper date parsing.
Pivoting and Unpivoting: These techniques allow restructuring data by converting rows to columns (pivoting) or columns to rows (unpivoting) for easier analysis.
Conditional Columns: New columns can be created based on specified conditions, similar to conditional statements in programming.
Creating Tables: Users can manually create tables within Power BI by entering data directly.
Data Analysis Expressions (DAX): DAX is a collection of functions, operators, and constants used in Power BI to create new data or transform existing data.
Purpose: DAX is used to calculate complex formulas, create measures, develop time intelligence calculations, and dynamically or statically analyze data.
Calculated Columns vs. Measures:
Calculated Columns: Create a new column in the data model, adding static data that consumes memory and updates when new data is added. They work row by row.
Measures: Dynamically calculate values at runtime, primarily for aggregations like sum, count, or average, and are used to create visual reports. They do not consume memory for each row. Measures can be implicit (automatically created by Power BI) or explicit (user-defined).
DAX Functions: Broadly categorized into Date and Time, Text, Informative, Filter, Aggregation, Time Intelligence, Logical, Math and Trigonometric, Statistical, and Financial functions.
DAX Syntax: Typically involves a column name, an equals sign, a function, and then references to table and column names (e.g., ColumnName = Function(TableName[ColumnName])).
Operators: Used in DAX formulas, including arithmetic (+, -, *, /), comparison (>, <, =, >=, <=, <>), logical (AND, OR, NOT), concatenation (&), reference (TableName[ColumnName]), and parentheses () for controlling execution order.
Data Modeling and Relationships: Data modeling is crucial for connecting different tables and sources, especially in companies with diverse datasets (e.g., product, sales, customer details).
Merge and Append Queries:
Merge: Combines two tables based on a common key, increasing the number of columns, similar to SQL joins (inner, left, right, full, anti-joins).
Append: Stacks rows from multiple tables with similar columns into one table, increasing the number of rows.
Keys: Primary keys are unique identifiers, while foreign keys can be duplicated and refer to a primary key in another table.
Cardinality: Describes the relationship type between tables (one-to-one, one-to-many, many-to-one, many-to-many).
Cross-Filter Direction: Defines the flow of data filtering between related tables (single or double direction).
Managing Relationships: Power BI can automatically detect relationships, and users can manually manage and edit them, including setting cardinality and cross-filter direction.
Data Visualization: Visualization is a critical step in data analysis within Power BI, as it reveals patterns and trends not apparent in raw row and column data.
Dashboard Elements: Visuals are built in the report section by dragging and dropping fields (columns from tables).
Visual Types: Power BI offers a wide range of built-in visuals, including stacked bar, stacked column, clustered bar, clustered column, line, area, pie, scatter, donut, funnel, map, tree map, matrices, cards (number and multi-row), and KPI visuals. Users can also import custom visuals from the Power BI marketplace.
Formatting and Customization: Visuals can be extensively formatted, including changing font size, colors, titles, background, borders, data labels, and themes.
Filtering: Filters can be applied via the filter pane (on specific visuals, pages, or all pages) or interactive slicers (displaying data as lists, dropdowns, or ranges). Slicers can also be synced across multiple pages.
Interactivity Tools: Buttons can be added for page navigation or other actions, and bookmarks capture report states to allow users to return to specific views. Images can be inserted for branding or icons.
Publishing and Sharing: Completed dashboards can be published to Power BI service, requiring login, to be viewed online, shared with co-workers, or published to the web without security. Power BI also supports creating mobile layouts for dashboards, optimizing them for phone viewing.
Power BI: Mastering Data Visualization and Reporting
Data visualization is a crucial step in data analysis, transforming raw data into insightful and interactive visual representations to reveal patterns and trends that are not apparent in simple rows and columns. Power BI, a business analytics tool developed by Microsoft, is designed to facilitate this process, offering powerful features for visualizing data.
The Importance of Data Visualization
Visualizing data helps users see new things and discover patterns that might otherwise be missed. When data is presented in a graphical format, business strategists can better understand the information and use it to grow their business. Power BI provides the necessary skills and knowledge to become proficient in efficiently working with and visualizing data.
Key Aspects of Data Visualization in Power BI
Report Section and Visuals:
The primary area for creating visuals in Power BI is the report section.
Users can build visuals by dragging and dropping fields (columns from tables) from the “Fields” pane on the right-hand side.
Power BI offers a user-friendly interface with a wide range of interactive and powerful features for visualization.
Types of Visuals: Power BI includes many built-in chart types and allows for the import of custom visuals:
Bar and Column Charts: Stacked bar, stacked column, clustered bar, and clustered column charts are available for comparing values across categories.
Line and Area Charts: Used to show trends over time or categories.
Pie and Donut Charts: Represent parts of a whole. A donut chart can become a pie chart by reducing its inner radius to zero.
Scatter Plot: Displays relationships between two numerical variables.
Funnel Chart: Shows stages in a linear process.
Maps: Allows visualization of data geographically, using locations like countries or continents. Bubbles on the map can represent values, with their size corresponding to a measure like population. A “flow map” visual can also be imported to show destinations and origins or flows between regions.
Tree Maps: Display hierarchical data in a set of nested rectangles, where the size of each rectangle is proportional to its value. An existing chart, like a donut chart, can easily be converted into a tree map.
Matrices: A powerful tool for visualizing data on different parameters and dimensions, allowing for hierarchical drilling down from categories (e.g., continents) to subcategories (e.g., countries).
Cards: Used to highlight specific numeric information or text.
Number Cards: Display a single large number, such as total population or average values.
Multi-row Cards: Show multiple pieces of information, like sum of population, average life expectancy, and average GDP, in one visual.
Text Cards: Display textual information, such as the top-performing category based on an order quantity filter.
KPI (Key Performance Indicator) Visuals: Allow for showing performance metrics, often with a trend graph in the background, like the sum of population over time or company profit/loss.
Slicers: Interactive filtering tools that allow users to filter data across the entire dashboard or specific pages. Slicers can display data as a list, a dropdown, or a range slider (e.g., for years). They can also be synchronized across multiple pages.
Tables: Simple tabular representations of data.
Custom Visuals: Users can import additional visuals from the Power BI marketplace (AppSource) to enhance their dashboards.
Formatting and Customization: Power BI provides extensive options for customizing the appearance of visuals and dashboards:
Canvas Settings: Users can change the background color or add images to the canvas background to match a particular theme. Transparency can also be adjusted.
Themes: Different built-in themes are available, and users can also create their own custom themes.
Gridlines: Can be added to help arrange visuals neatly on the canvas.
Object Locking: Visuals can be locked in place to prevent accidental movement.
Axis Formatting: Users can change font size, colors, define ranges (minimum/maximum), and customize titles for X and Y axes.
Data Labels: Can be turned on or off to display specific values directly on the chart, with customizable colors and positions.
Colors: Colors of bars, slices (in donut charts), and text can be customized. Conditional formatting can be applied, for instance, to show a gradient of colors based on value (e.g., light blue for lowest to dark blue for highest).
Borders and Shadows: Visuals can have customizable borders and shadows to make the dashboard more interactive and visually appealing.
Spacing and Padding: Adjusting inner and outer padding for elements within charts helps control visual spacing.
Titles: Visual titles can be customized in terms of text, color, and font.
Filtering and Interactivity:
Filter Pane: Filters can be applied to individual visuals, to all visuals on a specific page, or to all visuals across all pages. Advanced filtering options include operators like “less than” or “greater than”.
Buttons: Can be added to dashboards for various actions, such as page navigation. Users can define the destination page for a button.
Bookmarks: Capture the current state of a report (including filters, sort order, and visible visuals), allowing users to return to specific views easily. Bookmarks can be linked to buttons for navigation.
Images: Logos or other icons can be added to the dashboard for branding or aesthetic purposes.
Publishing and Mobile View:
Mobile Layout: Dashboards created on desktops can be optimized for phone viewing by arranging elements within a mobile grid layout. This allows for scrolling and resizing visuals to fit mobile screens.
Publishing: Once a dashboard is complete and satisfactory, it can be published to the Power BI service for online viewing and sharing with co-workers. Reports can also be published to the web without security for public viewing.
Power BI Data Modeling: Relationships and Cardinality
Data modeling is a crucial aspect of data analysis in Power BI, particularly when dealing with information from various sources. It involves connecting different tables and managing the relationships between them to enable comprehensive and accurate data visualization and analysis.
Purpose and Importance of Data Modeling
Data modeling is essential because companies often have data stored in separate tables or databases, such as sales, product, and customer details. Creating relationships between these disparate tables allows for a unified view and accurate visualization of the data, which is vital for data analysis. Without proper data modeling, tables remain independent, and it becomes difficult to see relationships between them, leading to inaccurate or incomplete data display.
Key Concepts in Data Modeling
Primary Key: A column that contains unique values and is not repeated or duplicated within a table. For example, a product ID in a product table or an Aadhaar card number are primary keys because each is unique to a single entity.
Foreign Key: A column that can contain duplicate values and acts as a clone of a primary key from another table. For instance, a customer key in a sales table might appear multiple times if a customer buys several products, making it a foreign key, whereas the same customer key in the customer data table would be a primary key.
Relationships and Cardinality
Relationships are built between tables based on common primary and foreign keys. Power BI can automatically detect these relationships upon data load. The type of relationship between tables is known as cardinality:
One-to-One (1:1): Occurs when both tables involved in the relationship have unique primary keys in the joined columns. For example, an employee ID in an employee details table and the same employee ID in a bonus table, where both IDs are unique in their respective tables, form a one-to-one relationship.
One-to-Many (1:N): This is a common relationship where one table contains a primary key, and the related column in another table is a foreign key with multiple occurrences. An example is a product table with unique product IDs (primary key) linked to a sales table where product IDs can repeat for multiple sales (foreign key). The data flow typically goes from the ‘one’ side (primary key) to the ‘many’ side (foreign key).
Many-to-One (N:1): This is the inverse of one-to-many, where the foreign key is in the first table and the primary key is in the second.
Many-to-Many (N:N): This relationship occurs when both related columns in two tables are foreign keys, meaning values can repeat in both. It is generally advised to create this type of relationship rarely.
Cross-Filter Direction: This refers to the direction of data flow between tables in a relationship.
Single Direction: Data flow is from the primary key side to the foreign key side (1 to Many).
Double Direction (Both): Data flow is bidirectional, allowing filtering from either side (primary key to foreign key and vice versa). This enables a third connected table to access data more easily, even if it doesn’t have a direct relationship.
Managing and Editing Relationships in Power BI
Power BI offers tools to manage and edit relationships:
Automatic Detection: Power BI can automatically detect and create relationships between tables when data is loaded, especially if common column names or keys exist.
Manual Creation: Users can manually create relationships by dragging and dropping common keys between tables in the ‘Model’ view.
Editing Relationships: Existing relationships can be edited to change their type (cardinality) or cross-filter direction. For instance, a user can modify a relationship from one-to-many to many-to-many or change its filter direction.
Activation/Deactivation: Only one active relationship can exist between two tables at any given time. If multiple potential relationships exist, others will appear as dotted lines, indicating they are deactivated. To activate a deactivated relationship, another active relationship between the same tables must be deactivated first.
Proper data modeling ensures that relationships are correctly defined, leading to accurate data analysis and visualization in dashboards.
DAX Functions for Data Analysis and Power BI
DAX, which stands for Data Analysis Expressions, is a powerful functional language used in Power BI to create custom calculations for data analysis and visualization. It includes a library of functions, operators, and constants that can be used to perform dynamic aggregations and define new computed columns and measures within your data models.
Purpose and Application of DAX Functions
DAX functions are essential for transforming and analyzing data beyond what simple transformations can achieve. They allow users to:
Create calculated columns: These are new columns added to a table, where each row’s value is computed based on a DAX formula. Calculated columns are static and consume memory, updating when new data is added to the model.
Create measures: Measures are dynamic calculations that aggregate data, such as sums, averages, or counts, and are evaluated at query time, making them efficient for reporting and dashboard interactions. They do not consume memory until used in a visual.
Calculate complex formulas: DAX enables the creation of sophisticated calculations, including time intelligence calculations, to group data and derive insights.
Analyze data dynamically and statically: DAX expressions provide flexibility for various analytical needs.
Categories of DAX Functions
DAX functions are broadly categorized to handle different types of data and analytical needs:
Date and Time Functions: Used for operations on date and time data, such as extracting parts of a date (year, month, day), calculating age, or finding differences between dates. Examples include NOW(), YEAR(), WEEKDAY(), DATE_DIFFERENCE().
Text Functions: Used to manipulate text strings, such as concatenating text, changing case, trimming whitespace, or finding specific substrings. Examples include CONCATENATE(), FIND(), FORMAT(), LEFT(), RIGHT(), LEN(), LOWER(), UPPER(), REPLACE(), and TRIM().
Informative Functions: Provide information about data types or handle errors, like checking for text, even/odd numbers, or missing data. Examples include ISERROR() or ISNA().
Filter Functions: Work based on specified conditions to filter data, often used with CALCULATE or FILTER to modify contexts. Examples include SUMX (sum if condition) or COUNTX (count if condition).
Aggregation Functions: Used to summarize data, such as SUM, COUNT, AVERAGE, MIN, and MAX.
Time Intelligence Functions: Specialized functions that enable calculations over time periods, essential for trend analysis.
Logical Functions: Implement conditional logic, evaluating expressions based on true/false conditions. Examples include IF(), AND(), OR(), NOT(), and SWITCH().
Math and Trigonometric Functions: Perform mathematical operations like absolute value, square root, exponents, or trigonometric calculations such as sine, cosine, and tangent. Examples include ROUNDUP(), ROUNDDOWN().
Statistical Functions: Used for statistical calculations like percentile or standard deviation.
Financial Functions: Help compute financial calculations.
Other Functions: A category for functions that don’t fit into the above, such as NOW() or GOOD().
DAX Syntax
The general syntax for a DAX expression typically involves:
Column Name: The name of the new calculated column or measure being created.
Equals Sign (=): Indicates that the column or measure is defined by the subsequent expression.
Function: The DAX function to be used (e.g., SUM, COUNT, IF).
Table Name (optional for measures, often needed for calculated columns): Specifies the table containing the data.
Column Reference: The specific column on which the function operates, often enclosed in square brackets [].
Example: Total Price = SUM(‘Order Items'[Price])
Practical Examples of DAX Functions
LEN(): To find the number of digits or characters in a column, such as digit count of ID = LEN(‘Zomato Asia Africa'[Restaurant ID]).
LEFT() / RIGHT(): To extract a specified number of characters from the beginning or end of a text string. For instance, creating a “Short Day” column from “Day Name” using short day = LEFT(‘Customer Data'[Day Name], 3) to get “THU” from “Thursday”.
LOWER() / UPPER(): To convert text in a column to lowercase or uppercase. For example, LOWER(‘Customer Data'[Day Name]) converts “THU” to “thu”.
Concatenation (&): To combine values from multiple columns into one, like creating a full name: ‘Customer Data'[Prefix] & ” ” & ‘Customer Data'[First Name] & ” ” & ‘Customer Data'[Last Name].
DATE_DIFFERENCE(): To calculate the difference between two dates, useful for determining age. For example, DATE_DIFFERENCE(‘Customers Data'[Birth Date], TODAY(), YEAR) to get age in years.
IF(): To apply conditional logic. For instance, creating a payment data column: IF(‘O list order payments'[Payment Value] > 100, “High Price”, “Low Price”).
Arithmetic Operators (+, -, *, /): Used for mathematical calculations on column values.
Comparison Operators (>, <, =, etc.): Used to compare values, yielding true/false results, often within conditional statements.
DAX functions are fundamental for performing advanced data manipulation and aggregation, enabling users to derive deeper insights from their data in Power BI.
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John Michaloudis of MyExcelOnline.com presents a free, 10-hour Excel PivotTable course comprising 230 tutorials. The course covers a wide range of PivotTable functionalities, from basic customization to advanced techniques like calculated fields, PivotCharts, and macros. Step-by-step instructions and practical exercises are included, using sample datasets for hands-on learning. The course also promotes Michaloudis’s paid MyExcelOnline Academy, offering more comprehensive Excel training. A link to download accompanying workbooks is provided.
Pivot Table Mastery: A Comprehensive Study Guide
Quiz
Instructions: Answer the following questions in 2-3 sentences each.
How can you change field names in a Pivot Table, and what is one reason you might want to do so?
Explain the process of formatting values in a Pivot Table, including how to ensure the formatting is maintained even when new data is added.
What happens when you drop multiple metrics into the “values” area of a Pivot Table, and how can you adjust the view?
Describe the “compact form” layout of a Pivot Table, and explain how to modify the indentation of row labels while maintaining this layout.
How can you alter the layout of a report filter in a Pivot Table, including changing the display order and fields per column?
What are two ways you can handle error values in a Pivot Table?
How can you customize the display of empty cells in a Pivot Table, and why might you choose to display “no transactions” instead of “0”?
Explain how to prevent column widths in a Pivot Table from automatically resizing when you refresh the data.
What are the steps to change a calculation to average instead of sum and how do you format the result as a number with a comma and zero decimal places?
How can the PRODUCT function be used with binary values (1 and blank) to analyze datasets?
Answer Key
You can change field names by clicking directly on the name in the Pivot Table or through the options menu, choosing the active field. Changing field names can make the Pivot Table more readable and user-friendly by using custom names.
To format values, right-click a value, select “number format,” and adjust decimal places and separators. To ensure formatting is maintained, select “entire Pivot Table” under options, then values, and format from there to retain format when new data is added.
When multiple metrics are added to the “values” area, they appear as columns by default. To adjust the view, you can move the “values” field to row labels, creating a different perspective of the data.
Compact form keeps data labels in a single column, which can be modified using layout options. To maintain compact form but indent the labels, use the “indent row labels” option under the layout and format tab and specify number of characters.
You can modify the layout by going into options and changing the display order (“down then over” or “over then down”). Additionally, you can set the number of report filter fields per column to better organize filter options.
Error values can be addressed in the Pivot Table options, where you can choose to display a blank, zero, or specific text (like “error”) in place of the error. This makes the table easier to read.
Empty cells can be customized in the Pivot Table options to show a zero amount or custom text such as “no transactions”. Displaying “no transactions” is appropriate for situations where no data is present.
To prevent auto-fitting column widths on updates, you must uncheck “auto-fit column widths on update” in the options tab, This will maintain your customized layout when the table is refreshed.
To change to average, click on the dropdown for that value, then “value field settings.” Select “average.” Then, click “number format”, choose “number,” 0 decimal places, and enable the separator.
The PRODUCT function can be used with binary data to show if all values in a selection are blank, or if a 1 exists which means there is a defect. A result of 0 would indicate all blank (no defects) and a result of 1 means at least one defect.
Essay Questions
Instructions: Answer each of the following questions in a well-structured essay format. Your response should demonstrate a comprehensive understanding of Pivot Tables as presented in the source material.
Discuss the various ways that Pivot Tables allow users to customize the presentation of data. Your response should include examples from the source material of changes to layout, formatting, error handling, and calculated values.
Explain how Pivot Tables can be used to perform various statistical calculations, including average, maximum, minimum, standard deviation, and variance. How does each calculation help to gain deeper insights from the raw data?
Discuss the different ways that you can group data in a pivot table and explain how that grouping can be used to create different views of the data, and describe how to create calculated items within grouped data.
Explain how slicers can enhance the interactivity of Pivot Tables. Your answer should cover how slicers function, options for styling slicers, and how slicers can be used to control various elements of a dashboard, including calculated fields and conditional formatting.
Describe and discuss calculated fields and items, explaining the differences between them, the limitations of calculated items and how they can be utilized to solve real world business challenges using formulas and functions.
Glossary of Key Terms
Calculated Field: A virtual field created in a Pivot Table that uses a formula to perform calculations on other fields within the data source. These are defined by the columns of the source data. Calculated Item: A virtual data item created within a Pivot Table using existing row or column label items. These use formulas against the row and column headings of a pivot table. Compact Form: A layout option for Pivot Tables that keeps all row labels within a single column and provides indentation for hierarchical levels. Conditional Formatting: A feature in Excel that allows you to automatically format cells based on specific criteria. Data Model: A feature in Excel that allows for creating relationships between multiple tables. External Data Source: Data that is imported into Excel from external files, such as databases or text files. Field Settings: Options that allow you to change the summarization method (e.g., sum, average, count) for data in the values area, as well as choose custom subtotal calculations. GETPIVOTDATA: An Excel function that retrieves data from a Pivot Table based on specified criteria, making it useful for creating dynamic reports. Grand Total: The final sum of all data within a Pivot Table. Grouping: A feature that allows you to combine row or column label items into broader categories or ranges, often used for dates or numbers. Macro: A recorded sequence of steps in Excel that can be run automatically. Pivot Table: A tool in Excel that summarizes and analyzes data, allowing users to dynamically rearrange and view information. Pivot Table Cache: An internal memory in Excel which stores data retrieved from a data source for a pivot table. Report Filter: A way to filter data in a Pivot Table by selecting specific items or groups for a field, allowing different views of the data. Slicer: A visual tool used to filter data in a Pivot Table, allowing for interactive data exploration. Solve Order: Defines the sequence in which calculated items are calculated. Sparklines: Small charts within a cell that visually represent trends in data. Standard Deviation: A statistical measure of the amount of variation or dispersion of a set of values. Timeline: An interactive slicer that filters data within a pivot table based on date ranges. Variance: The measure of how far a data set is spread out from the average. Value Field Settings: The settings used to change the summarization method, number formatting, and custom calculations within the values area of a Pivot Table.
Excel Pivot Table Mastery
Okay, here is a detailed briefing document summarizing the key themes and ideas from the provided source (“01.pdf”):
Briefing Document: Excel Pivot Table Mastery
Document Overview:
This document summarizes a series of techniques and best practices for working with Pivot Tables in Excel, as presented in the source document “01.pdf.” The document covers a wide range of topics, from basic formatting and layout adjustments to advanced calculations and data analysis methods. It is designed for users who want to enhance their Pivot Table skills to create more insightful and customized reports.
Key Themes & Ideas:
Customizing Pivot Table Field Names:
Users can rename field names directly within the Pivot Table or via the Options menu.
Changing the name in either location will update the name displayed in the Pivot Table.
“Another way we can change the field names is to click in the Pivot Table and go to options. And because we’re in now sales, we get the active field as sales. We can click in there and we can see that the change that we made.”
Formatting Values:
Direct formatting (e.g., number formats, decimal places) of values in a Pivot Table can be lost when new fields are added.
To maintain formatting across changes, users should apply formatting using the “Format Cells” dialog box, accessible through the Options > Actions > Entire Pivot Table > Values menu or Ctrl+1 shortcut.
“And what we need to do is go into our Pivot Table tools and under options in the actions group, select entire Pivot Table, then select values. Press Control + 1 to bring in the format cells dialog box. And from in here, you can make your formatting changes.”
Manipulating Pivot Table Layout:
Users can rearrange metrics between row and column labels.
“Compact Form” can be adjusted to include indentation, mimicking an “Outline Form” appearance.
“Now under options and on the left-hand side options in layout and format tab, you have here when in compact form indent row labels. So let’s move it to the right by 10 characters and press okay. And as you can see, our salespeople have moved to the right, but they’re maintained in column A.”
Report filters can be customized with different layouts (down then over or over then down) and fields per column.
“We have here display field and report filter area. Our default is down then over. And in the dropdown box, we can choose over then down.”
Handling Errors & Empty Cells:Pivot Tables can display custom text instead of error values (e.g. “#DIV/0!”) by using the Options > Format > For error values show option.
“Now under format, there’s an option that says, for error values show. Let’s tick that. And we can put anything in there.”
Empty cells can be replaced with a custom text or numeric value, using Options > Format > For empty cells show.
“So we tick that box and in there we can put in there a zero amount, and that feels in our Pivot Table blank cells with zero.”
Column Width Preservation:
The “auto-fit column widths on update” feature can be disabled under Options > Options to prevent column widths from reverting to default on refresh.
“Under the options tab and options, there’s an option at the bottom here that says, auto-fit column widths on update. So upon a refresh it auto-fits that back to where it was previously. Well, let’s uncheck this and press okay.”
Refreshing Pivot Table Data:
Users can refresh a pivot table manually through the options.
There are issues with shared workbooks with refreshing and remembering to do so.
Understanding Common Calculations:Average: Demonstrates calculating average sales by product, salesperson, year and order date.
Maximum: Shows finding the largest sale transaction by product, salesperson and year.
“So as you can see here, for each product and each salesperson, we have the maximum sales transaction that I made for that year.”
Minimum: Illustrates finding the smallest sale transaction by product, salesperson and year.
“In 2012, for bottles, Homer’s smallest sale was 10,780. Ian Wright’s was 20,650, John Michaloudis’ was a 48,378, and Michael Jackson’s smallest sale was $17,030 out of all his sales in 2012 for the bottles product.”
Product: Demonstrates using a product function to identify months with flawless (zero defects) defect rates.
“So if we give a zero that means we had our flawless month and that’s a great result for our company.”
Percentage: Explores finding out the percentage of overdue transactions.
“So 55% of our total transactions are past due, which is a bad result.”
Standard Deviation: Explains the concept of standard deviation and its relationship with data distribution. It provides step by step guide on how to generate and analyze a standard deviation graph and determine the volatility of the data.
“So what it means is you can go either way to the left or right of 44,000 by about 20,000. So we have a high volatility there. So therefore, as you can see, our graph is pretty flat.”
Variance: Show how to generate and analyse variance, demonstrating both a low and high variance.
“So as you can see here, we have a very high variance and also a very high standard deviation.”
Subtotals and Grand Totals:Users can customize subtotal calculations.
Shows users how to add multiple grand total calculations (average, max, min, etc.) by adding a blank column to the data table, then creating new grand total rows using the field settings.
“So what wanna do is put in there some extra grand total. Now there’s a way around this. First of all, we need to go to our data table and in our table, just add another column field named grand total, press enter.”
Accessing Field Settings and Value Field Settings
Demonstrates the multiple ways to access both field settings and value field settings.
Explores doing this via the field list, right clicking in the pivot table, and using the options tab from the ribbon.
Advanced Calculations and Analysis
Demonstrates how to create a bonus scheme using sales data to determine the bonus amount paid based on the channel sales made in different zones.
Shows how to create a group of customers to do further analysis.
Provides guidance on grouping dates on a Monday.
Explores how to isolate dates to do further analysis.
Explains how to group by fiscal year or quarter, using custom formulas in the data source.
Slicers
Explores how to format and style slicers.
Explains what slicer elements are.
Demonstrates how to copy slicer styles to other workbooks.
Provides insight on how to change a slicer name.
Explains how to use a customer list in slicer settings to sort data.
Camera Tool and Dynamic Pictures
Provides guidance on how to add the camera tool to the quick access tool bar.
Explains how to use the camera tool with an offset range to create dynamic pictures.
Profit and Loss Statements
Demonstrates how to create a P&L statement using slicers.
Provides step by step guide on how to compare the actual and plan numbers and create a variance.
Shows how to set up three different scenarios: base, best, and worst.
Explores the use of calculated fields.
Details how to correct calculate the sales margin, how to edit and modify it.
Calculated Fields and Items
Show how to create calculated fields with IF Statements.
Explains how to set up and use a calculated item.
Explains calculated item shortcomings.
Shows how to use solve order with calculated items.
Provides guidance on how to view calculated field and item formulas.
Demonstrates how to remove a calculated field temporarily.
Explores order of operations.
Explains how to create a P&L using sparklines and calculated items.
Shows how to set up a variance report using calculated fields.
Conditional Formatting
Explains how to keep conditional formatting alive when changing a field.
Shows how to create a conditional formatting using slicers.
Demonstrates how to show text values using conditional formatting.
Explores how to highlight blank cells.
Financial Reporting
Explains how to create an accounts receivable aging report.
Shows how to highlight highest and lowest values using conditional formatting.
Advanced Formulas
Demonstrates how to use the end of month date to show actual or plan data based on today’s date.
Shows how to use the GETPIVOTDATA to generate complex reports and also the use of slicers for comparison reports.
Macros
Provides guidance on how to record macros.
Explains how to assign macros to shapes.
File Optimization and Data Source
Provides guidance on how to reduce file memory by saving the file as a Excel Binary Workbook.
Shows how to use Microsoft Access to create a pivot table when there is over a million rows of data.
Explores compatibility issues with Excel 2007 and 2010.
Cloud Sharing and Forecasting
Demonstrates how to share a pivot table via Microsoft’s OneDrive.
Shows how to create sales forecasts based on a percent increase using calculated fields.
Graphing and Analysis
Demonstrates how to use a Pivot Table to create a frequency distribution graph.
Explains how to do a break-even analysis using a Pivot Table and a slicer.
Additional Slicers, Dashboards, and Reports
Shows different types of slicers and the flexibility when creating them.
Explores how to create a balance sheet using slicers and Pivot Tables.
Provides guidance on how to create a sales manager performance report showing variances using conditional formatting.
Demonstrates how to reconcile customer payments.
Provides information on the pivot power add-in.
Timelines and Data Models
Explains how to use the timeline feature in Excel 2013
Introduces the data model and how it works by combining data from different tables to create a Pivot Table.
Conclusion:
The source document “01.pdf” provides a comprehensive overview of Pivot Table functionality in Excel, covering essential techniques for data manipulation, formatting, and analysis. By following the practices and methods explained in this document, users can create more informative, dynamic, and visually appealing reports to support better decision-making.
Pivot Table FAQs
How can I change the field names in a Pivot Table? There are a couple of ways to change field names. First, you can click just after the last character in the existing name in the Pivot Table field list, press the space bar, and then press “Okay.” This makes it recognized as a different name. Alternatively, select the field within the Pivot Table, go to “Options” in the PivotTable Tools menu, find the active field, and you can directly edit it there. Changes will reflect both in the field list and in the Pivot Table itself.
How can I maintain number formatting in a Pivot Table after adding more fields? To ensure your formatting remains consistent, do not format directly within the values of the pivot table. Instead, click anywhere in the Pivot Table, then within the “Pivot Table Tools” menu, go to the “Options” tab, then to the “Actions” group and select the entire Pivot Table, then select values. Press Control + 1 to open the “Format Cells” dialog, and apply your desired formatting here. This formatting will be maintained even when you drop additional fields into the values area.
Why does adding multiple metrics to the values area change the Pivot Table layout, and how can I adjust it? When you add multiple metrics to the values area, the Pivot Table automatically places them under “Column Labels.” To change this, drag the “Values” field from the column labels into either the row labels or place it at the top of the row labels area. This lets you display metrics side-by-side or stacked, as desired.
How can I create an outline-like view in a compact format Pivot Table? Although the report layout can be changed to outline form, you can achieve a similar effect with the compact form by going to “Options”, then “Layout and Format”. In “when in compact form indent row labels”, you can set an indent value. This moves the labels to the right while maintaining the compact layout.
How do I customize the layout of my report filters? To adjust report filter layout, go to “Options,” then “Options.” Under the “Display” field in “Report Filter Area” you can choose to show filter fields “down then over” or “over then down”. You can also change the “report filter fields per column” setting, where you can specify how many filter options show per column. This is useful for more readable and manageable report filters.
How do I manage errors or blank cells within a Pivot Table? To handle error values, go to “Options” and then “Options,” and in “Format”, select “For error values show”. There you can either leave it blank, show a zero or type something like “error” to handle the errors in a way that’s useful to you. To handle empty cells, go to “Options”, then “Options” and format, then tick “For empty cells show”. Here, you can enter a value, like “0” or text like “no transactions”. This allows you to differentiate between missing data and zero values.
How can I prevent column widths from resetting after refreshing the Pivot Table? To stop column widths from auto-adjusting after a refresh, go to “Options” and then “Options” and uncheck the option called “AutoFit column widths on update”. After unchecking this, you can manually adjust column widths, and they will remain fixed, even after refreshing the data.
How do I access and use different calculation functions like average, maximum, minimum, product, and percentages in Pivot Tables? To change the calculation function applied to a value field, right-click on any value in your Pivot Table and select “Summarize Values By.” Here you can choose from sum, count, average, max, min, product, or other calculations. For custom formatting, click “Value Field Settings” and format it as desired. For example, you can format as a date, percentage, or number with separators and decimal places. You can use functions like average, maximum, minimum, and product by dropping your value into the values area, then selecting value field settings and choosing the function you want. You can do other types of calculations, like show a percentage of the total, or the percentage difference from previous, in the value field settings dialog. You can use the Product function within a calculated field, or you can show a percentage of total transactions by creating a calculated field that counts overdue transactions divided by total transactions.
Mastering Excel Pivot Tables
Excel Pivot Tables are a powerful tool for analyzing data [1]. They allow users to analyze thousands of rows of data with drag-and-drop ease [1]. With Pivot Tables, you can create reports that analyze your data and make business decisions [1].
Here are some key concepts and features of Excel Pivot Tables discussed in the sources:
Data Preparation: Before creating a Pivot Table, data should be in a tabular format, with no gaps, and with labeled columns [1]. Column names should be at the top, showing a distinct category of information [1].
Creating a Pivot Table:
You can create a Pivot Table by selecting your data and going to Insert > Pivot Table [1].
Alternatively, if your data is in an Excel table, you can go to Table Tools > Design > Summarize with Pivot Table [1].
Pivot Tables can be placed in a new worksheet or an existing one [1].
Pivot Table Fields:
The Pivot Table field list shows all the column names from your data source [1].
Fields can be dragged and dropped into four different areas:
Row Labels: Shows unique values from chosen fields on the left side of the Pivot Table [2]. This is used for grouping items such as products or company names [2].
Column Labels: Shows a trend of data across the top of the Pivot Table, such as time periods or years [2].
Values: Where fields to be calculated or quantified are placed, including sum, count, average, maximum, or minimum [2].
Report Filter: Optional field to drill down on and focus on, such as regions or staff [2].
The layout of the Pivot Table can be changed by dragging fields between the different areas [2].
Refreshing Pivot Tables:
When the original data is updated, the Pivot Table must be refreshed to reflect those changes by right-clicking and choosing refresh or by going to the Pivot Table tools tab under options, and in the data group, press refresh [3].
Changes to the data range must be updated in the Pivot Table data source unless the source is an Excel table [4].
You can set a Pivot Table to automatically refresh when the Excel workbook is opened [4].
Formatting Pivot Tables:
You can sort the field list alphabetically to make it easier to find the fields [3].
You can format specific parts of the Pivot Table by enabling selection, which allows you to select subtotals, columns, or unique row entries [4].
You can also format number values, for example, to show currency, by selecting value field settings and number format [5].
You can also change the names of the value fields to your liking [6].
You can use the “select entire Pivot Table” to ensure formatting applies to new fields [6].
Layout Options:Pivot Tables can be displayed in compact form, outline form, or tabular form [7]. Compact form displays multiple fields in one column, while outline and tabular forms separate the row fields into separate columns [7].
You can also add or remove blank rows after each item to make the Pivot Table easier to read [7].
Drill Down and Expand/Collapse:
Double-clicking on a value in the Pivot Table will provide a snapshot of the underlying data that makes up that value [3].
The expand and collapse options allow you to drill down on specific rows or columns or summarize at a higher level [7].
You can expand or collapse entire fields, or individual items [7].
Moving Items:
Items within a Pivot Table can be moved by right-clicking and selecting move [5].
You can also move items by typing the item name, which will bring it to the top of the list, or moving fields by dragging and dropping them within the area sections [5].
Fields can also be removed by right-clicking and selecting remove field [5].
Filtering:
You can filter data using report filters, which are located at the top left of the Pivot Table [8].
You can also filter data using label filters and value filters by right-clicking on the row labels and choosing filter, or from the Pivot Table field list [9].
You can select multiple items by using the “select multiple items” option in the report filter [8].
You can also keep only selected items by highlighting your selection and right-clicking [8].
Slicers:
Slicers are buttons that show what has been selected in your filters [8].
To insert a slicer, you must click inside your Pivot Table and go to the Pivot Table tools tab under options or the Analyze tab and choose insert slicer [8].
Slicers can be moved and resized and can have multiple columns [10].
You can connect multiple Pivot Tables with a single slicer to filter them simultaneously [10].
Calculated Fields and Items:Calculated fields allow you to perform calculations using the data within the Pivot Table, such as adding or subtracting fields, or applying a percentage [11].
You can create calculated items to see the difference between, for example, revenue and COGS [12].
Show Values As:
The “show values as” function allows you to display values in different ways, such as a percentage of the grand total or a difference from a base value [12].
Conditional Formatting:
You can apply conditional formatting to the cells of a Pivot Table to highlight certain values or trends [13].
Pivot Charts:
A pivot chart is a visual extension of a Pivot Table that changes as the Pivot Table is modified [14].
Pivot charts are created by selecting a Pivot Table, going to the options tab, and clicking Pivot Chart [14].
You can filter a pivot chart directly from the chart or by using a slicer [14].
GETPIVOTDATA Formula:
The GETPIVOTDATA formula allows you to extract specific values from a Pivot Table into your own customized reports that are outside of the Pivot Table layout [13].
This formula can be used to create custom reports that reference cells for items to enhance reporting [13].
Consolidating Data:
The Pivot Table wizard can be used to consolidate data from multiple sources into a single Pivot Table [11].
The wizard can also be used to transform data from a tabular format into a Pivot Table [11].
Excel Versions:
In Excel 2013, the “options” tab is renamed to “analyze” [15].
Excel 2013 also introduced the recommended Pivot Tables, distinct count calculation, and the timeline slicer [15].
Excel 2016 has auto-grouping for date columns, multi-select for slicers, and the ability for pivot charts to expand or collapse its data [16].
Excel 2019 introduced 3D maps [16].
This information should give you a comprehensive understanding of the features, uses, and nuances of Excel Pivot Tables, as described in the sources provided.
Excel Pivot Tables: Data Analysis and Visualization
Data analysis is a key function of Excel Pivot Tables, allowing users to summarize and interpret large datasets to make informed decisions [1-8]. Pivot Tables can perform various calculations and statistical analyses, offering multiple ways to view and understand data [1]. Here are some ways that Pivot Tables can support data analysis:
Summarizing Data: Pivot Tables summarize data by grouping similar items together and applying calculations, such as sums, averages, counts, minimums, and maximums, to these groups [1, 4, 9].
For example, you can calculate the total sales for each product over different years [1].
You can also calculate the average, maximum, and minimum sales for each product and salesperson [9].
The count function can show the number of transactions that occurred within a specific time frame or sales range [1, 3, 5, 10].
Filtering Data: Pivot Tables allow users to filter data by specific criteria, focusing on relevant subsets of information [1, 6, 11, 12].
Report filters can be used to drill down on specific fields such as regions, time periods, business units, and staff [1].
Label filters and value filters can be used to select specific items, or to show the top or bottom performers [6].
Slicers provide visual buttons to quickly filter the data in a Pivot Table [7, 11, 13, 14].
Timelines filter date fields, allowing you to quickly select specific time periods [12].
Calculating Variance and Trends: Pivot Tables can be used to calculate variances between different data points and identify trends over time [7, 14-16].
You can calculate the difference between the actual and planned sales, both in terms of dollar value and percentage [15].
You can calculate percentage differences from a base field, such as a previous year or a planned target [7, 15].
Calculated fields allow you to create new metrics by using formulas with existing fields [7]. For example, you could calculate profit margin as a percentage of revenue [7].
Statistical Analysis: Pivot Tables provide tools for statistical analysis of data [3, 4].
You can calculate the standard deviation of your data to understand its volatility [3]. A low standard deviation means that data points tend to be very close to the average [3]. A high standard deviation means that the data points are more spread out [3].
The variance calculation measures how far a set of numbers are spread out from the average and from each other [4].
Pivot Tables can help you understand data distribution, such as whether it is normally distributed, or has a higher volatility [3].
Grouping Data: Pivot Tables can group numerical and text data to summarize trends across categories [5, 10].
Numerical data can be grouped by range to see the number of transactions or sales that fall within a certain range [3, 5].
Date data can be grouped by days, weeks, months, quarters, or years [10].
Text data can be grouped into new categories to consolidate data [5].
Time data can be automatically grouped into hours and minutes [17].
Visualizing Data: Pivot Tables allow you to create visualizations to aid in data analysis [8, 11, 13].
Pivot charts are visual extensions of Pivot Tables, and update as you make changes to the Pivot Table [11].
You can customize charts by changing the chart type, layout, style and colors [11, 13].
You can insert different chart types, including column charts, pie charts, or scatter charts [11, 13].
Sparklines are small charts that fit within a cell to quickly show trends across data [16].
Consolidating Data: Pivot Tables can consolidate data from multiple sources, such as different spreadsheets or databases [18].
You can use the Pivot Table wizard to consolidate data from different salespersons into one report [18].
You can also use the wizard to convert data from a tabular format into a Pivot Table layout [18].
Data Models: Excel 2013 and later versions can create a data model by relating multiple tables based on common fields [17, 19].
You can create a relationship between different tables when there is a one to many relationship using a primary key [19].
You can then create Pivot Tables by combining data from these related tables [17, 19].
By utilizing these features, Pivot Tables can transform raw data into actionable insights for effective business analysis [1, 2].
Mastering Excel Pivot Tables
Excel Pivot Tables offer a wide array of features that enable users to analyze and manipulate data effectively. These features can be broadly categorized into data preparation, creation, layout, filtering, calculations, visualization, and more [1-18].
Here’s a detailed look at some of the key features of Pivot Tables, as discussed in the sources:
Data Preparation: Before creating a Pivot Table, the source data should be in a tabular format, with no gaps, and with labeled columns [1]. Column names should be at the top, representing distinct categories of information [1].
Creating Pivot Tables:
A Pivot Table is created by selecting the data and going to Insert > Pivot Table [1].
If the data is in an Excel table, you can go to Table Tools > Design > Summarize with Pivot Table [1].
Pivot Tables can be placed in a new worksheet or an existing worksheet [1].
Pivot Table Fields:
The Pivot Table field list shows all column names from the data source [1].
Fields are dragged and dropped into four areas:
Row Labels: Shows unique values on the left side of the Pivot Table, used for grouping items [1].
Column Labels: Shows trends across the top of the Pivot Table, such as time periods [1].
Values: Where fields to be calculated are placed, such as sums, counts, or averages [1].
Report Filter: An optional area to filter and focus on specific fields [1].
Refreshing Pivot Tables:
When the original data is updated, the Pivot Table must be refreshed by right-clicking and choosing refresh, or by using the Pivot Table tools tab [1].
You can set a Pivot Table to automatically refresh when the workbook is opened [7].
A pivot cache stores a snapshot of the data, and is updated when you refresh the Pivot Table [2].
Formatting Pivot Tables:
The field list can be sorted alphabetically [1].
You can format specific parts of the Pivot Table by enabling selection, allowing formatting of subtotals, columns, or unique row entries [1].
Number formats can be changed (e.g., to show currency) by selecting value field settings and number format [1].
The names of value fields can be customized [1, 5].
Use “select entire Pivot Table” to ensure formatting applies to new fields [6].
Layout Options:
Pivot Tables can be displayed in compact form, outline form, or tabular form [4]. Compact form displays multiple fields in one column, while outline and tabular forms separate row fields into columns [4].
Blank rows can be added or removed after each item [4].
Drill Down and Expand/Collapse:
Double-clicking on a value in the Pivot Table will provide a snapshot of the underlying data [2].
The expand and collapse options allow drilling down on specific rows or summarizing at a higher level [5].
Entire fields or individual items can be expanded or collapsed [5].
Moving Items:
Items within a Pivot Table can be moved by right-clicking and selecting move [5].
Items can also be moved by typing the name, or by dragging and dropping fields within the area sections [5].
Fields can be removed by right-clicking and selecting remove field [5].
Filtering:
Report filters are located at the top left of the Pivot Table [2, 10].
Label filters and value filters can be used by right-clicking on the row labels or from the Pivot Table field list [10].
You can select multiple items by using the “select multiple items” option in the report filter [10].
You can also keep only selected items by highlighting your selection and right-clicking [10].
Slicers:
Slicers are visual buttons that show what has been selected in the filters [11].
To insert a slicer, click inside the Pivot Table and go to the Pivot Table tools tab > options or Analyze tab > insert slicer [11].
Slicers can be moved, resized, and can have multiple columns [11].
Multiple Pivot Tables can be connected to a single slicer to filter them simultaneously [11].
Calculated Fields and Items:
Calculated fields allow performing calculations using data within the Pivot Table [15].
Calculated items can show the difference between revenue and COGS [8].
Show Values As:
This function allows displaying values in different ways, such as percentage of grand total or a difference from a base value [8].
Conditional Formatting:
You can apply conditional formatting to highlight specific values or trends in a Pivot Table [14].
Pivot Charts:
A pivot chart is a visual extension of a Pivot Table that changes as the Pivot Table is modified [12].
Pivot charts are created by selecting a Pivot Table and choosing Pivot Chart from the options tab [12].
You can filter a pivot chart directly from the chart or by using a slicer [12].
GETPIVOTDATA Formula:
This formula allows you to extract values from a Pivot Table into customized reports outside the Pivot Table [14].
The formula can reference cells for items to enhance reporting [14].
Consolidating Data:
The Pivot Table wizard can consolidate data from multiple sources into a single Pivot Table [15].
The wizard can also transform data from a tabular format into a Pivot Table [15].
Excel Versions:
In Excel 2013, the “options” tab is renamed to “analyze” [17].
Excel 2013 introduced recommended Pivot Tables, a distinct count calculation, and the timeline slicer [17].
Excel 2016 has auto-grouping for date columns, multi-select for slicers, and the ability for pivot charts to expand or collapse its data [18].
Excel 2019 introduced 3D maps [18].
These features collectively make Excel Pivot Tables a versatile tool for data analysis, reporting, and visualization.
Mastering Excel Pivot Tables
Excel skills can be enhanced through the use of Pivot Tables, which are a powerful tool for data analysis, reporting, and visualization [1, 2]. The sources describe a variety of Excel skills related to Pivot Tables, including:
Data Preparation:
Organizing data in a tabular format with labeled columns and no gaps is a fundamental skill for using Pivot Tables effectively [1, 2].
Data should be in a list with labeled columns, also known as tabular format [1].
Data must be arranged so that column names are on the top, showing a distinct category of information, with the rows below containing the corresponding data [1].
Creating Pivot Tables:
Inserting a Pivot Table is done by selecting the data and going to Insert > Pivot Table [1, 2].
If the data is in a table format, a Pivot Table can be created using Table Tools > Design > Summarize with Pivot Table [1, 2].
Pivot Tables can be created in either a new worksheet or an existing worksheet [1, 2].
Understanding the Pivot Table Field List:
The Pivot Table field list contains all the column names from the data source and is used to drag and drop the fields into the different areas of the Pivot Table [1, 2].
The four areas of a Pivot Table are row labels, column labels, values, and report filter [1, 2].
Understanding which fields to place in each area is crucial for effective data analysis [1, 2].
Manipulating Pivot Table Layout:
You can move fields to different areas to get different views of the data [1].
Items in the Pivot Table can be moved by right-clicking and selecting move or by dragging and dropping [1, 2].
Fields can be removed from the Pivot Table by right-clicking and selecting “remove field” [1, 2].
Pivot Tables can be displayed in compact, outline, or tabular form [2, 3]. You can also adjust the indentations for row labels when in compact form [3].
Report filter layouts can be changed to display fields down then over, or over then down [3].
Data Analysis Skills:
Summarizing data by using sum, average, count, min, max calculations in the values area [1, 2].
Filtering data using report filters, label filters, and value filters to focus on relevant information [1, 2].
Using slicers to filter Pivot Table data visually [1, 2, 4].
Using timelines to filter data based on dates [5].
Calculating variance between different data points [6].
Identifying trends over time by grouping data by time periods [1].
Performing statistical analysis, such as calculating standard deviation [7].
Grouping data by range to see how sales or costs are distributed [7, 8].
Understanding how to use calculated fields and calculated items [1, 6, 9].
Using the “show values as” option to display values as percentages, differences, or running totals [1, 6, 10].
Formatting Pivot Tables:
Applying number formats to values to improve readability [1, 3, 11].
Customizing the names of value fields [1, 11].
Applying conditional formatting to highlight specific values or trends in a Pivot Table [1, 10].
Removing field headers to present a cleaner table [11].
Visualizing Data:
Creating Pivot Charts to visualize data from the Pivot Table [1, 2, 12].
Customizing charts by changing the chart type, layout, and colors [1, 12, 13].
Inserting sparklines to quickly see trends [1, 12].
Advanced Skills:
Using the GETPIVOTDATA formula to extract data for customized reports [1, 14].
Consolidating data from multiple sources using the Pivot Table wizard [1, 8].
Creating data models by relating multiple tables for complex analysis [1, 5, 15, 16].
Working with 3D maps to visualize geographical data [15].
Improving Efficiency:
Using Pivot Power add-in to set default styles, apply formatting quickly, and clear filters with one click [14].
Saving files as an Excel Binary Workbook to reduce file memory [9].
Using Microsoft Access with over a million rows of data [9].
Sharing a Pivot Table via Microsoft OneDrive to view and make changes [9].
Version-Specific Skills:
Being aware of the new features in different Excel versions such as recommended Pivot Tables, timelines, distinct count calculations, auto grouping dates, and the data model [1, 5, 15].
By mastering these Excel skills, users can effectively analyze data, create insightful reports, and make informed business decisions using Pivot Tables [1, 2].
Mastering Excel Pivot Tables: A Free 10-Hour Course
The sources describe a free Excel Pivot Table course that includes the following:
Course Overview: The course is a comprehensive, 10-hour long training program, consisting of 230 short and precise tutorials designed to help users learn Excel and Pivot Tables efficiently [1].
Course Goal: The course aims to help users become more efficient and skillful, gain confidence, and potentially get promotions and pay raises [1].
Cost: The course is available for free, having previously been sold for $300. This decision was made because many people need to learn Excel but cannot afford expensive online courses [1].
Target Audience: The course is suitable for any Excel user, regardless of their skill level, whether they are a beginner, intermediate, or advanced. It is also for people of all ages and employment statuses [1].
Course Content:
The course focuses on Pivot Tables and their various functionalities [1].
Specific topics covered include:
Customizing Pivot Table layouts [1].
Summarizing values and showing values as calculations [1].
Grouping, sorting, and filtering data [1].
Using slicers [1].
Working with calculated fields and items [1].
Creating Pivot Charts [1].
Using conditional formatting with Pivot Tables [1].
Using the GETPIVOTDATA formula [1].
Integrating Pivot Tables with macros [1].
Exploring new features introduced in Excel 2013, 2016, 2019, and Office 365 [1].
Learning Approach:
The course uses a start and finish format for each tutorial, with downloadable workbooks for practice [1].
Users are encouraged to practice along with the tutorials to improve their skills [1].
The course is designed to allow users to jump to specific sections they want to learn, without having to complete the entire course [1].
Support: The course instructor will monitor and respond to questions posted in the comments area below the videos [1].
Downloadable Workbooks: There is a link to download all 230 tutorials so users can practice along with the instructor [1].
Additional Resources: The course also invites users to join the MyExcelOnline Academy for more advanced Excel training, which includes over 1000 video tutorials covering various topics such as formulas, macros, Power BI, and more [1].
This free course is presented as a way for users to dramatically improve their Excel skills by focusing on Pivot Tables, with the promise of making them more proficient in data analysis and business decision-making [1].
Master Excel Pivot Tables, Excel Slicers and Interactive Excel Dashboards – FULL COURSE!
The Original Text
– Good day guys and girls, I’m John Michaloudis here from MyExcelOnline.com and I want to welcome you in this free Excel Pivot Table course. Now this is a massive course, it is over 10 hours long, and it has 230 short and precise tutorials. So you can learn Excel and Pivot Tables straight away. So you can become more efficient, more skillful, gain confidence, you can get the promotions and pay rises that you deserve. Now, I used to sell this course here, this individual course here, over at my website for $300. And I’ve decide to put these on the issue platform for free. Because I know a lot of people need to learn Excel and there are not that many good tutorials or courses on YouTube. So this is free, this is for you because a lot of people don’t have money to spend on online courses and I understand that. So this course is for you and it’s going to make you much, much better at Excel. Now in this course you’re gonna learn about Pivot Tables. And with Pivot Table, you can analyze thousands of rows of data, we drag and drop ease. So when you drag and drop into your Pivot Table, it’s gonna create a report that analyzes your data. And with that data, you can make some awesome reports and you can make some great business decisions and also it’s gonna give you the power that you need to take your Excel skills to the next level. In this course, we’re going to talk about the following topics. First of all, we’re gonna talk about how to customize your Pivot Table in a different layout. Then we’re gonna go into the summarize values by, and also show values as calculations. Next, we’re gonna go into grouping your data, then into sorting, then we’re gonna go into filtering. After that we’re gonna show you slicers which is an awesome feature that was introduced in Excel 2010. Then we’ll go into calculated fields and items. Then we’ll dive into Pivot Charts, we’re gonna show you a bit of conditional formatting, with Pivot Tables. Also, we’re gonna show you the GETPIVOTDATA formula. Then we’re gonna into Pivot Tables and Macros. Also, there are a bonus videos with some awesome tutorials there, and we’re gonna go through the new Excel Pivot Table features that were introduced in Excel 2013, in Excel 2016 and Excel 2019 and Office 365. So 230 short and precise free guide tutorials, 10 hours of Excel training free for you. Now, this course is for any Excel level. Whether your a beginner, intermediate, or you think you’re an advanced Excel user, this course is for you. Whether you’re young, you’re old, you’re unemployed, this course is for you. Once you learn Excel Pivot Tables, your Excel skills are going to skyrocket. Now in the description area below, there’s a link to download all 230 tutorials that I’ll through in this course. And each tutorial is in a start and finish format. So you need to download it so you can practice along with me as I show you. Now, the more you practice, the better we get. That’s with anything in life. So click on the button below, download the workbooks and let’s get straight into it. Now, finally, if you have any doubts any questions about any video tutorials, use the comments area below. Put in your question and I will be manning the comments and replying back to you with an answer. Also give this video a thumbs up. The more thumbs up we get, the more videos that we’re gonna create for you in YouTube. So go ahead and do that right now. And finally, after you watch this course, then we invite you to join our MyExcelOnline Academy Online course. This course here has over 1000 Excel video tutorials and covers, formulas, macros, PBI, Pivot Tables, Power BI, power query, power pivot, charts, axes. Also, we go into Microsoft Word, Microsoft PowerPoint, and also Outlook. And we also cover dashboards and heaps of more videos. Over 1000 video tutorials and if you really wanna elevate your Excel skills to the next level, we invite you to join the MyExcelOnline Academy the details are in the card that will pop up now or in the description below, click on that, but first of all, let’s get into this Pivot Table course. I want you to get better at Excel and Pivot Tables, jump onto different Pivot Table areas. We’ve listed every tutorial in the description. So you can click the button and go directly to an area that you want to learn. And once you learn Pivot Tables, you don’t have to finish all the course. You can just do different sections. Then you are gonna be ready to take your skills to the next level. And we are here, I am here, my team is here to support you in your journey to become better at Excel so you can stand out from the crowd and get the promotions and pay rises that you deserve. Now let’s get into it. (upbeat music) Before you begin with a Pivot Table, you gotta arrange your data set. Now there are three rules to follow. Number one, is to have your data in a tabular format. Number two, is to make sure that there are no gaps in the data. And number three is formatting. Now here, I’ll talk about tabular format. So what type of format means is that for a Pivot Table to work, you must make sure that your data is organized as a list with labeled columns, also known as tabular format. So you should have your column names on the top showing a distinct category of information. As you can see here, we have customer and going down the rows, we have the different customers. And we have products and we have information on the products. Salesperson, we have the different salespeople. And then as you can see, we go all the way up. We have order dates and so on. So let’s try to do a Pivot Table by pressing Control + A to select all of our data and then going into insert and Pivot Table. And then let’s put into a new worksheet and press okay. Wow, we’ll get an error message. It says here, “The Pivot Table field name is not valid. To create a Pivot Table report, you must use data that is organized as a list with labeled columns.” So the key data is labeled columns. Let’s cancel out of here. As you can see here, our years and our quarters don’t have any names. So therefore it’s not gonna work. Now let’s put in the names in there. Sales year and sales quarter. And once again, Control + A to select everything. Now, when you press Control + A makes sure that it gets everything. Insert, Pivot Table, new worksheet press okay. Here we go. We can start building our Pivot Table. (upbeat music) The second rule to arrange your data set is having no gaps. What that means is having no blank columns and no blank rows. The reason is that that section of your data might not get picked up when you create a Pivot Table. Now, as you can see here, we have column F that is blank and rows 11 and 22. Now let’s create a Pivot Table from in here and see what happens. Let’s select all, we’re going to the right and all the way down. Okay, so we’ll pick up everything here and go to insert and Pivot Table and press okay. We’ll get an error message. It says “The Pivot Table field name is not valid. To create a Pivot Table report, you must use data that is organized as a list with the labeled columns.” Press okay, and cancel to get out of there. Well, in here it’s picked up that we don’t have a labeled column so obviously we gotta delete it. Right-click and delete. Now we have to delete row 11 and 22. Now imagine you had lots of rows in your data set that were blank. And I’ll show you a quick way where you can delete all those blank rows. Now, once again, let’s highlight all your data set and then go to the home tab and find and select, go to special. In here, we go to special dialog box and choose blanks and press okay. So what it does is within your selection, it chooses all the blanks. So another way in here, what we can do is, we can hover over here and right-click and delete from there. Or instead of doing that, let’s press a shortcut, which is Control + the minus key. Now in here, we want to delete the entire row. So all the row gets shifted up. Okay. And then press okay, there you go. Now, what we gonna is press Control + A, make sure that it picks up everything. OKGo to insert, Pivot Table and press okay. (upbeat music) To have a great data set, you got to make sure that your formatting is in order. This is because it avoids inaccurate reports when creating a Pivot Table. So it is essential to format each column that contains numbers and each column that contains dates. Now, for example, our sales column here, we’ve got to make sure that it’s in a number format. To do this, we just click on the column F and then from the number group, the dropdown box, we can choose a number from in here and press okay. We’re gonna also put in a comma and then give it to the decimal places. Now in our older date here, we have numbers as well. Now Excel treats dates as a sequential number with the first of the first 1900 being day one. Now does this in order to perform arithmetic operations. Now this information here doesn’t make much sense to us. So we need to convert that to date. To do this, let’s click on column eight and once again, from the dropdown arrow, let’s choose short date. That’s much better. So now with all of our information in the right format, we can begin with our Pivot Table. (upbeat music) Excel Tables are a new feature from Excel 2007 and onwards and they’re great. You should always use them. The best feature is that it has a structured referencing. This means that as your data expands with more rows or columns being added, then the table automatically gets updated, as Excel refers to the table as a whole. Now when creating a Pivot Table and your data changes in a table, to update your Pivot Table, you only need to refresh and avoid having to update your data source. Now to insert a table, first, you got to click anywhere in your data source and press insert and table, and Excel is smart enough to detect your data source. Now you could scroll down to make sure that it’s inserted. Another way is to press Control + T which is a shortcut. Now this dialog box says create table. Where is the data for your table? So it’s taken out data and in here check it if your table has headers. And then press okay. So now it creates an Excel table. Now, if we step out of it and then step back in, once you’re in the table, you get the table tools option. And in here you have the design and different styles. So you have all these different styles that you can choose. Now also you can put in a total row, which means that from in here, you go different ways to summarize your data. So you can put in some in there. Now, if wanna expand your data, what you got to do is just grab the edge and just drag it down, or you can just go anywhere in here, right-click and insert. Let’s go back up again. Now you can also change the name of the table from in here. It’s called table1 but we can change it to my table. And once you’re in here, you can summarize the Pivot Table or you can export to SharePoint list. Another thing is you have your different filters in here. Now Excel tables are a great feature, and whenever you’re having data, you should always use them. Because they’re gonna save you lots of time in the end. (upbeat music) We have some data information here, and we’re gonna put it into a Pivot Table to see what the results are gonna give us. Go to insert and Pivot Table and let’s put it here next to our data. Now let’s get our data and put in our row labels and then our data into our values to get the count. So what it says is we have three separate values for IN123C104Z, but that can’t be right. This here should be equal to three. Now there’s a problem in here, and it usually happens when you’re importing data from external data sources. Now, what happens is you may get some leading or trailing spaces. Now let’s have a look in there and press F2. We can see that’s fine. Let’s go down and press F2, here we have a trailing space. And going there and press F2 here we have two trailing spaces. So the Pivot Table treats these values as separate so therefore it gives us a different count. Now I’ll show you a way to clean up your data before you create a Pivot Table. One ways to use the trim function. So press trim and click in there, and then it trims all your values like that and you can just double-click and you have the trim values there. Now another way is to use an add-in from Abelbeats.com, which is called the Trim Spaces. And that’s one that I use all the time. All you gotta do is just press a button and then it trims all your selected area. Now I’ll show you another way where you can trim your data, highlight your data like this, the whole column, go to data and text to columns, and then choose delimited and press next. And in here, make sure that the space is checked and then press finish. So let’s go back in here and have a look at second value. Press F2, you see that it’s cleaned the space and in there again it’s cleaned that. So let’s go in our Pivot Table, right-click and refresh, And now you see our data is being cleaned up and it counts it correctly. (upbeat music) So we have our data set here and it’s in a table, and we know that because when we click in our data source, we get the table tools option in there. And we can see there that the table name is table 13. Now to insert the Pivot Table, on the table tools tab, design, we can choose, summarize with Pivot Table, or we can actually go to insert tab and then Pivot Table like this. Now Excel is smart enough and it selects the table 13, so you’ll see that it’s all selected all the way to the bottom and we scroll to the right. Now, it tells us, “Where do we want to put a Pivot Table?” Now we can choose a new worksheet or we can actually put it into an existing worksheet. So we can actually go somewhere in here and put our Pivot Table there. Now, because we don’t have that much space, we’ll put it into a new worksheet and press okay. So you see it’s created a new worksheet called sheet one, and the Pivot Table is in here. Now if we step out of the Pivot Table, We don’t see the Pivot Table tools tab. We got to actually step into it to activate the Pivot Table tools and in here we can choose options and design. Now in the options we have the Pivot Table name, which is Pivot Table number one, and we can change that to customize that and call it my Pivot Table. And you can see here, it changes the name as well. On the right-hand side we have our Pivot Table field list, and we have all the column names here that were in our data source. Now if you can’t see this, then under Pivot Table tools tab options, you can activate it and disactivate it by the field list button there. Now our Pivot Table is gonna look similar to this design here. Now let’s go over to the right-hand side and I’ll show you how to create a Pivot Table. So the Pivot Table is gonna look similar to the design that we’ve just brought over here. The fields that get dropped into the report filter, will be shown on the top left-hand corner of the Pivot Table, fields that get dropped into the column area, will be shown on the horizontal area of the Pivot Table. Fields that get dropped into the row labels area will be shown on the left-hand side of the Pivot Table, fields that get dropped into the values area will be shown into the middle part of the Pivot Table. Now let’s go in and drop some fields into the respective areas. Now we can just hover over the name, grab it and drop it in there, just like that. And you can see on the left-hand side, the Pivot Table is gonna be built. Let’s get salespersons into the row labels. Let’s get sales here in the column labels and finally, let’s get the sales into the values area. And you can see we’ll get the live preview of our Pivot Table and then we have it, we’ve created a quick Pivot Table with just a few clicks. And as you can see, the design is similar to the one that we saw before. (upbeat music) When you click into a Pivot Table, just like I’ve done now, and now you’re onto the field list, ’cause there’s a couple of ways where you can bring it up. One of them is to go to the Pivot Table tools tab, under options choose the field list button. Here you can show it or hide it. And let’s get out of this. Another way is to click anywhere into the Pivot Table, right-click, and the last option is show field list. Now we can do a couple of things in here. We can actually move or resize the field list, from the drop-down arrow we can choose move and then with the mouse, just click and drag to the left and we can move it out here. Let’s move it back in. With your mouse again, move it all the way as if you’re throwing it out of the screen and the locks back in. The other option is to resize so you can resize it from in here. And then we can close it. Let’s bring it up again. Now from this dropdown box, we have five different views that we can see the field listing. The first is that field session and areas sessions stacked which is a default, then we have the field section and area section side-by-side. Then we have the field section only, then the area section only two by two, and then area section only one by four. Now I personally like the default view. (upbeat music) In our Pivot Table field list, on the top half, we have our fields or column headings. If we go back to our data, you can see these column headings from customer products, salesperson, sales region, order date, sales, sales year, sales month and sales quarter. They’re all inputted into this area here. Now in the bottom half of our Pivot Table field list, we have our four different areas where we can drag and drop our fields or column headings into. Now let’s talk about these. First we have out row labels. In here, you can show the unique values from the fields chosen on the left-hand side of the pivot. So here you should look to add fields that you’re looking to group, for example, products, company names, locations and business units. For example, we’ll take our products. Now you can actually click in the box and it will dropdown in to the row labels. And sometimes by clicking, it doesn’t actually drop into the area that you want. So the best way to do it is to drag and drop. So you can drag that all the way down and you can drop it in here. When you see the little blue line underneath row labels and just let go of your mouse and you see products has been dropped into the row labels. Now on the left hand side, our Pivot Table is automatically updated, you get a live preview. So here we have our unique values that are within the products column. We have bottles, ice cubes, soft drinks and tonic. Now we can check that if we go back to our data set and go to our products and in the dropdown box, we can see that we have our four unique values in there. So these are transferred into the left-hand side of the Pivot Table. And next we have our column labels. In the column labels, you’re mainly looking to show the trend of your data. For example, periods, phases, time, months, and years. So in that case, we can go and grab our sales here and drag it all the way into the column label area. And as you can see on the top side of the pivot, we have our unique years, which are 2012, 2013 and 2014. Now in the values area, this is where you put fields that you want to calculate or quantify. The different type of calculations that you can use to summarize your data include sum for sales, count for number of units, average for prices, and maximum or minimum for your values. So in here, we’re gonna grab our sales and drag and drop in there. As you can see on the left-hand side, we have our sum of sales in there. So what it says in here is that in 2012, we sold $2,754,838 worth of bottles. So what it’s done here, it summarized, so it summarized all the sales and put into a neat little table here where you can quickly analyze it within a few seconds. Now, finally, we have a report filter. This is an optional filter. Here you can put fields that you want to drill down on and focus on. For example, regions, periods, business units and staff. So for example, we’re gonna grab our salesperson and drop them in there and sales region and drop them in there. As you can see on the left-hand side, we have our report filters with a dropdown box and we can see the unique values that make up the salesperson, and sales region, we can also see the unique fellows in there. Now, Pivot Table is very powerful because you can chop and change until you get the outcome that you like, that your boss like, or that your business is looking for. Now, if we want to move products from row labels to columns, you can do that. You just grab, drag and drop in the columns and then grab the slaes year and put into the row labels. As you can see on the left-hand side now we have our years and on the top column cycle, we have our products. So you can analyze the information in a different way. It depends on what you’re looking for. If you don’t get it right the first time, don’t worry, with trial and error, you will end up with your desired look. Now Pivot Tables are that easy. (upbeat music) So that you’re analyzing your data and you come across a strange value, and it doesn’t add up. For example, in 2012, for bottles, we have $2.7 million, but it should be more like 3 million. Or you can actually drill down and order that. To do that, you just click in the sale and then double-click and you get a snapshot of your data set, only for bottles and 2012. So in here you can go into the sales and see where the error was. Now, if you wanna make any changes, this is not the place to do it. You need to do it in your data set. Now let’s get out of here, Control + Z to get out and press the delete. So any changes you got to make has to be in your data set. And then you got to make sure that when you’re in your Pivot Table, that you refresh it by right-clicking and refresh to update any changes that you made in your data set. And you can also drill down into the grand totals, so say you wanna look at 2013, you just double-click and it gives you all the values for 2013. And you can begin with checking your information there. And once again, Control + Z to get out and delete. (upbeat music) We have our field list here, but it’s not in alphabetical order. And sometimes it can get confusing if you wanna try and find out some fields, especially if you have more than 20 different fields. Now to put this into alphabetical order, all we’re gotta do is go to the options and then options, and under display at the bottom, you have the field list and you can sort from A to Z. Press that, we’ll press okay, and you can see this will change to an alphabetical order. (upbeat music) You can click on any row or column label items, so we can show more fields. For example, in the row labels here, we double-click, you wanna get these show detail dialog box. And in here it says, “Choose a field containing the detail you want to show.” So it has all the fields not already chosen in the row labels, so we can choose for example, sales quarter and press okay, and then we have the sales quarters in there, and as you can see the areas in here sales quarter, has also been added. And the same thing we can do in the column labels. Double click, and we can add anything from in here, Let’s use sales month and press okay. (upbeat music) If you have many rows in your data source, and when you create a Pivot Table, it takes time to generate the live preview and the results, and all you can do is click here on the bottom left-hand corner, the, defer layout update. What this does is, when you drop in your information like sales in your values area, you see you don’t get a live preview here. So you can just drop into whatever you like in here and then sales years up there, so you can drop whatever you like and then when you’re happy with it, just press update, and then it updates it. So what it does is, it defers the layout update until you press the update button. (upbeat music) When your data changes either by your data source having its values updated or more rows or columns having been added to your data source then you need to refresh your Pivot Table. The reason is that when you created your first Pivot Table, a snapshot of your data was stored in a pivot cache. A pivot cache is a snapshot of your data set and this is where your Pivot Table is created from. You don’t see this pivot cache, but it runs in the background system. This attributed a copy of your data set allows for your Pivot Table to run faster when you’re making changes to it. So when changes are made to your original data set then you need to refresh, so you can update the pivot cache and ultimately update your Pivot Table. (upbeat music) When your data gets updated, you need to refresh the Pivot Table to reflect the changes made in your data set. For example, if we going through our data and we go into bottles and we change the sales here to $10 million, then if we go back to our Pivot Table we see that no change has been made here. What you need to do is refresh the Pivot Table to update the values. There are two ways to do that. One of it is to click in the Pivot Table and go to the Pivot Table tools tab under options, and in the data group, press refresh. As you can see here, our bottles for 2012 have changed. Now let’s press Control + Z to go back. The second way to do this is just to right-click anywhere in your Pivot Table and you have the refresh option there, you just click on there and your values get updated. (upbeat music) In this example, we have two separate Pivot Tables that were created from two distinct data sets. So our Pivot Table on their left-hand side was created from data1, which is over here. Pivot number two on the right-hand side was created from data2 in here. So now what we’re gonna do is go in and change the information in each of the datasets. And we’re gonna use the refresh all button to refresh both Pivot Tables simultaneously. So what we’re gonna do is we’re gonna update bottles in 2012, so we’ve highlighted that in red so we can see the change. And on our second Pivot Table, we’re gonna change the value in soft drinks for 2012. So let’s go to data1 first and I’ve highlighted this in red so we can make the change. So I wanna add in 10 million in there. And data2, let’s scroll up, it’s for soft drinks. So I wanna add 10 million in there as well. So let’s go back to our pivots. Now, if we have multiple Pivot Tables, we can actually use the refresh all option, which is from the dropdown box and you have their refresh all and what that does, it updates both Pivot Tables simultaneously. So let’s press a button and we’ll see the numbers change. There you go. So as you’ve seen on the left here, the numbers to change the 12 million and soft drinks it’s changed to 11 million. So if you have more than one Pivot Table in your workbook, then you can use a refresh all button to update those Pivot Tables simultaneously. (upbeat music) Say that in your company, you have a workbook that you and your colleagues are sharing and updating on a hourly basis or a daily basis. And you want to create a Pivot Table on your personal desktop, well, you can do that. Now in here, we have our shared data set and let’s imagine that this is sitting in your company’s server and everyone has access to it and they update it accordingly. So let’s have a look at that. So this is a dataset that we’ve been using in our previous lessons. So we can get out of here and let’s go into our workbook, which sits in your desktop. So we can click on that. And now here we can create our Pivot Table. So to do that, we have to go to insert and Pivot Table, and we choose the use an external data source option, and then we have to choose a connection on the bottom left-hand corner, we click on browse for more, and then we have to search for our data set, which is sitting on our imaginary server and press open. And we have a pop-up box that comes up and we’ll have to select the data, which is the first one. The check pop here says that the first row of data contains column headers, and that’s correct, and we can press okay. Let’s create a Pivot Table. Let’s put in our products on the row labels, our sales in the values and our sales here in the column labels. So there you go. You have created your Pivot Table from an external data source. Now let’s save this and we can get out of it. And let’s go back into our shared dataset, which is my server, and let’s start making some changes. So imagine that your colleagues are making changes to this data set on a daily basis. So let’s put in some fictitious numbers in there. And we can just… Okay, so we have that, so we can get out of that. And imagine the next morning you come into work and you’re having this workbook and it hasn’t been refreshed. Well, there’s a couple of ways that you can update it. You can right-click and refresh, and that will get updated as you’ve seen there. Let’s Control + Z to get out of that. Now, another way that you can a refresh it is by clicking on the connection properties under refresh, and we get this connection properties pop-up box, and we have a few options here. We can actually refresh every X number of minutes. So let’s just refresh after one minute and press okay and we’ll see what happens. Well, there you go. The updates have been made. So this is a great feature to have. So every X number of minutes, depending on the default that you put on there, your personal Pivot Table will get updated. So we can go back in here and change that again, under condition properties, we can uncheck that. And let’s check the refresh data when opening the file. So what that means is when you open your personal workbook, that the Pivot Table will get refreshed automatically you don’t need to do anything. So let’s save this and we’ll get out of there. And let’s go back to our shared data set which sits in our imaginary company server. And let’s imagine that more changes have been made during the day. Well, these changes have been cleared out and we can save there, and we can get out. And let’s go back into your personal workbook and look at this. It has refreshed automatically, the information from your external data source without you having to do anything. This is a great feature because sometimes you can come into your work in the morning, open your Pivot Table without refreshing, it happens. And this is a great feature to have so it’s automatically it gets updated without you having to do anything. Now, the last refresh control in here is enabled background refresh. Now you’re only gonna use that when you’re running a query in the background, which will enable you to use Excel while the query runs. Refresh every X number of minutes and refresh data when opening the file, they’re the options that you’d be using when you linking your workbook to an external data source. (upbeat music) So if you’re working with an access database, you can certainly export that information into an Excel workbook and pivot that information accordingly. Now we have our database here, which is a similar data set that we have been using in our previous lessons. So I have saved this database number one in my desktop. Now let’s get out of here and we can open up our new workbook. So to import the access database information into a Pivot Table, we need to go into data and choose from access, and then go to my desktop where I saved my database1, double-click on that and we’ll get our dialog box that says, “How do you want to view the data in our workbook?” We can view it as a table, as a Pivot Table report, as a pivot chart and Pivot Table report, so now we will choose the second option, Pivot Table report, and we’ll put into our existing worksheet in here and press okay, and we’ll get our Pivot Table. So now we can create our Pivot Table here, we can put our products in the row labels, sales year in the column and the sales in there. So we have our Pivot Table here. Now we can also refresh our Pivot Table, so when the exit that access database gets updated accordingly, well, we can actually refresh it automatically by pressing refresh, or we can put in a time refresh every X number of minutes, or we can also refresh the data when we opening our Excel workbook. And this was covered in lesson 1.34. So there you have it, you can insert information coming from an access database and use it inside a Pivot Table to analyze the data. (upbeat music) So we have our Pivot Table here which is referenced to a data range. We can save that by going into options, change data source, and we can see here that the range is all the way here. Now when our range gets changed by having more rows or columns into there, then we need to go into our change data source and capture the new range. So let’s go in there and add in some extra information. So press Control + Down to go to the end of our data set. And let’s enter some fictitious data in here. Let’s press Control + D to fill there. Let’s go back to the Pivot Table and go to options and change data source. As you can see here, it only goes all the way to row 577. So our extra rows that we’ve added in there haven’t been captured in our range. So what we need to do is include all that in our Pivot Table data source. So to do that press Control + Shift + Across + Down and press okay. So as you can see here, the information now has been refreshed and included in our Pivot Table. Now that is a long way to do it. When you’re using a Pivot Table, you should always have an Excel table as your referenced information. So what we’re gonna do now, going to our table here and select that. So as you can see here, it’s looking at it as a table as a whole. So every time we add in the extra rows or columns, then we don’t need to go back into the change data source button and include the extra lines, because it’s already gonna include it into these table 13. So let’s have a look here, our amount is 3.2 million, and let’s add in here a few extra rows or you can actually drag down. And then once again, we can copy down, we’re pressing Control + D. So all we need to do now is just go back into our Pivot Table and refresh. Click at options and refresh. As you can see there, the new information has been updated. Now because Excel tables use structured referencing, then we don’t need to go in and change the data source because it looks at a table as one whole data set. So you should always use Excel tables when you’re doing Pivot Tables and even if you’re not doing Pivot Tables, they’re great for data analysis. (upbeat music) If you have many fields of reports in here, as you can see, and you wanna clear them quickly, one a quick way to clear them is to go into options and into your actions group, and under clear, choose clear filters. Now if you’ve been working with your Pivot Table and you don’t like the look of it, and you wanna start again, but you don’t want to delete your pivot cache, then you can easily do that by going into the options and clear and clear all. So what it does is it clears all your field list items in your areas, and you can start fresh again. So now you can put in your new fields into your areas, just like that, and you can do your new analysis. (upbeat music) To format a section of a Pivot Table, such as sub-totals, columns, or unique row entries, then you need to go into your Pivot Table tools tab on the options in the actions group, under select, you gonna make sure that enable selection, let’s tick. As you can see there, we have the orange border around that. So now what you can do here is actually go into the sub-totals as you can see the black arrow is pointing and click there. So now we can go into our home tab and format so we can put that into red. Now, if we move our products from row labels to the column labels, then the bottles product is still gonna be formatted in red, as you can see there. So let’s put that back. Now we can also format the individual row items, for example, Q1. So by right-clicking in there, we can highlight that in a different color. And once again, if we move sales quarters from row labels to column labels, then that formatting stays there. So let’s move that back. Now, if we go on top of the row label and click there, then we can actually make some adjustments in there. Right-click to make those in italics. Now we can also go into our column headings and do the same thing. Let’s go to the grand total, right-click, and we can put in there a border, the same thing we can do for the grand total down here, right-click and put in there a border. Now, if you’re not highlight the whole Pivot Table, then all you got to go to is on the top left-hand corner, where it says sum of sales and you have the black arrow, you click on there, that’s one way. The other way is going into the options tab, select an entire Pivot Table. So when you’re in here, you can put in a different color if you like, or you can press delete and delete Pivot Table let’s press Control + Z and get out of there. So there are many things that you can do with the options and select item to make your Pivot Table look a little bit funkier. (upbeat music) Now, if you want to move out Pivot Table to another location, we can certainly do that. All we’re gotta do is click anywhere in the Pivot Table, go into the options tab and the move Pivot Table button, click on that, and now we get two options. We can either move it to a new worksheet or to an existing worksheet. So let’s move it to an existing worksheet and let’s choose up here, press okay. As you can see, it’s moved there. Now let’s move into a new worksheet and press okay. As you can see a new worksheet has been created called sheet1, and our Pivot Table has been moved from the pivot sheet into sheet1. (upbeat music) The default Pivot Table style is pretty dull looking. But luckily you have different styles where you can use and apply and make the Pivot Table look bright and beautiful. Now to activate that you need to go under your Pivot Table tools tab on the design, and you have your Pivot Table styles here. Now in the dropdown box, there are 85 different styles from light as you can see here, you get a live preview as you’re scrolling through each style. And there are some nice colors and some not so nice colors. You have your medium. As you can see there, you have a few nice styles, and then you have your dark styles. And depending on what you like or what your boss is looking for, you can choose one of these 85 different styles. I personally like this style here. You can make further changes under the Pivot Table style options over here. You can put in banded rows, and also banded columns. Now you can also uncheck the row headers and also the column headers. And once again, it’s up to you, whatever style you like, you choose and use that style for your Pivot Tables. So now let’s customize our row headers or make it into italics. And now if say we wanna change the style to a dark style, and if you right-click in there, you’ve got the first option apply and clear formatting. What that means is it’s gonna apply the new style and clear the italic formatting or any other formatting that you would have had in your Pivot Table. So let’s click that and you can see the italics have gone. Now again, if I change this to italics and then I choose another style and right-click apply and maintain formatting, then I will maintain the italics in the row headers. Now, the other option that we have there is a duplicate. So we can actually duplicate this Pivot Table style and change the styling in there. And we’re gonna talk about that in another chapter. Now, the other option is set as default. So you can set this as default and when you’re creating another Pivot Table within your current workbook, then you’re gonna get the same style. So let’s create a quick Pivot Table here and we’ll put into a new worksheet and press okay. And let’s put in some values in there. As you can see, it creates the Pivot Table based on your style that you have chosen, but it’s only gonna work in your current workbook. And the third option that we have when we right-click in there is add gallery to quick access toolbar. So we click on that quick access toolbar is down here, so we have the other option in there. (upbeat music) Now in the Pivot Table styles, you can create your own style. All you need to do is go under your Pivot Table styles, and then you have the option at the bottom here called new Pivot Table style, click in there, and you get this dialog box where you can name your new Pivot Table style, and you have your table elements. And here is where you can format your Pivot Table and you get a preview here. And you got 25 different elements in here, so you can start from scratch and create your own style. Now, if you’d like a style from one of these 85 predetermined styles, if you like one of them, you can just right-click and press duplicate. So what it does is it duplicates the Pivot Table and you can make changes from there. So we can rename this, I can rename it to John’s Pivot Table Pivot Table1 and you have your different table elements here. Now we’re gonna go to first column and we can format the first column and that relates to here. So let’s put her into a great color. Now what we need to do is we don’t get a live update, we actually gotta go back into the Pivot Table style and then choose our custom, which is the second one here and we got to activate it like that, to see the changes. So watch out for that. Now we can go back in and right-click in there and press on modify, so we can keep on making our modifications in there. So in our header row, we can format that into a different color, you see it’s blue now, but we can make it into a different field effect. You can choose one of this. We have the color white and the color blue and the shading styles, the variance here, we can choose any one of these just to spice it up a bit. Let’s choose that. Press okay. And you see, that’s changed there. And let’s go back again, modify, and let’s go to the grand total row and format that. And we can make the grand total row black with a bold white color. As you can see there, the change has been made there in the preview. Okay. And also here now we have made that change. We can go back in there, we can see grand total row and the element formatting, what we’ve chosen, bold background one and where we have shaded. So now if we don’t like this, we can clear up and go back to the start. Press Control + Z. Now, as I said, within modify, we have the table elements. We have 25 different elements now to change every single one of it I think is a bit over the top. So what I’ve done here is I’ve created a table of what the different elements are and where the changes will occur. So just the important ones, you don’t have to go through all 25, but the main ones I’ve highlighted here for you to go in and play around with them when you have some spare time and you’re bored. So you’ve got all these different styles that you can change and they’re all highlighted here. (upbeat music) when you customize a Pivot Table style, you can only use it in that workbook that you created it in. Now this is a new workbook and we created a new Pivot Table. As you can see, the customized style that we created previously is not in here. Let’s say you wanna bring it over in here. Well, we can do that. All we have to do is go back into our customized style that we created in our previous lesson 1.52, go to options and select the entire Pivot Table, press Control + C to copy the Pivot Table. Now let’s go through our new workbook and paste the Pivot Table here, right-click and paste it in there. And what happens now is that the customized style has been embedded into this new workbook. So what we can do is click on our Pivot Table, apply the custom style, and then we can go and delete the Pivot Table that you brought over by selecting all and pressing the delete button in our keyboard. So now we have our customized style brought over into our new workbook. (upbeat music) Under Pivot Table design tab, you have more options on the left-hand side, under the layout group. And the first one is sub-totals. So in here you got the three options. The first one is, do not show sub-totals. So the sub-totals disappear. Second option is show all sub-totals at bottom of group. So you can see sub-total is at the bottom of each item. And the third option is to show all sub-totals at the top of the group up here. So depending on what you like, you can choose to have those three different options. (upbeat music) So the other option under design and layout group is the grand totals. So in here we’ve got four different options. The first one is off for rows and columns. So the rows and columns grand totals disappear. The second option is on for rows or columns, as you can see there, they come back on again. The third option is on for rows only, so we just have the row grand total here. And the last option is on for columns only. So you can see the grand total is down here. So you have four different options, but I like using on for rows and columns. (upbeat music) Under the report layout, you have three different ways that you can show your Pivot Table. The first one is new in Excel 2010, and it’s called show in compact form. Now in this form, you can see multiple fields in one column. As you can see here, we have our products and our salesperson in our row labels. So they’re all compact into column A. So if I grab sales region and bring it there, as you can see, it would just drop it into column A. So it’s all compacted into one singular column. Let’s take our sales region from here. And the second form is called the outline form. As you can see there, this layout separates the row fields into separate columns as you can see, we have products, we have that have salesperson and it’ll drop in the sales region, it’ll go into column C. So you see sales region is in column C. And the third form that we have is show in tabular form. Now this is the legacy form, and this was created many years ago. As you can see, you can still use it here, but the new compact form for me works the best. Now another feature that we have here is the repeat all item labels. And now let’s go into show in outline form first, and if we choose a repeat all item labels, what it will do is it’ll fill in all the gaps that we have here. And this is fantastic if you want to copy and paste this information to analyze it into another sheet. So let’s put it in there. And as you can see, we have the information here and we can analyze it. We can just delete the gaps there. And we have it into a tabular format that we can use to make our analysis. And in here, I have the different layouts for you to have a look at. We’ll have the compact, the outline, tabula and the outline but with repeat all item label. So you can have a look and see which format you like. (upbeat music) Now under design and the layout group we have the blank rows button here. And what it does is insert a blank line after each item, or you’re gonna remove a blank line after each item. So let’s insert a blank line. And as you can see there, we have a little bit more space in our Pivot Table, and it just looks a little bit more presentable. But if you don’t like that, you can always switch it up. (upbeat music) For all of the old schoolers out there, that still like the 2003 version of the Pivot Tables, well you can actually bring that to life in Excel 2010 and 2013. Now to do this, you got to click anywhere in your Pivot Table, right-click and go to Pivot Table options, in display, choose the classic Pivot Table layout. Now this will enable dragging our fields into the grid just like in 2003 and press okay. Now finally, just to make it look like the 2003 version, just choose a none in the design layout. So we get this view here. So there you have it. We have our sales year there, so we can drag it and move it out there. We can get our sales month and then drag it all the way and drop it into there and it take you back to 2003. (upbeat music) The expand or collapse option allows you to drill down on specific rows or columns, or you can summarize at a higher level. Now this is located next to the item names and you can see there by the minus sign. So if we press on that, we can collapse the individualized item and click again, you can expand it. There’s no way to do that, just right-click anywhere in the item name and go to expand collapse and press collapse or expand. Now, if you want to collapse all the fields all you have to do is go up to the ribbon, which is under the options tab, and you have the green plus sign there, which says expand entire field or the red minus sign, which says collapse entire field. So if you click on there, you collapse or the fields, and then the plus sign, you expand them. Another way is to go into one over the field items, right-click in there and go expand collapse and go to expand entire field or collapse entire field options. Now the salesperson don’t have the minus sign next to them because of they’re last and the hierarchy, as you can see there, But what you can actually do, you can actually expand them. So you can bring in more fields to analyze. So we can do that by right-clicking anywhere in the salesperson and go to expand collapse and choose expand entire field. Now you get a dialog box. So in here you have all the fields that are not part of the row labels. So you’ve get everything except products and salesperson. So you can bring fields into analyze. So let’s bring in our sales quarter and press okay. So as you can see there, each sales quarter has been added into the individual salesperson within the products. So you get all that down there, so you can do some in-depth analysis if you like, and you can bring in more as well. Let’s right-click and bring in the months, expand entire field and choose sales month and you get that in there. Now as you can see on the row labels, the sales quarter and the sales month have been added in there automatically. Now expanding and collapsing is not only for row labels, you can also do it in the column labels. So let’s put in our quarters in there, as you can see our months are collapsed so we can click on the box there and expand them, or you can just do it individually into each year. And also you can right-click on the last field, which is sales quarter and expand the entire field. We’ll get a pop up box and we’d get add in there our sales month. So you see sales month its gonna move from row labels to column label when we press okay. Now we can collapse everything, so click in the quarters and press a collapse, click on the years collapse, let’s click in the row labels products and collapse. So you have the high level view that you can analyze where you can take a screenshot and send it to your boss, or if you want, you can actually click on individual items and drill down from there. Now on the right-hand side here, under options under the show group, you have the plus or minus buttons. You can uncheck that, but that doesn’t mean that you cannot drill down. Well, you can. It just means that the plus or minus signs are not evidence. So you can use the expand and collapse buttons even though you don’t see the plus or minus signs. (upbeat music) There are a few ways to move items within a Pivot Table. One way is to click in one of your items. Right-click, and you’ve got the move option there, and you’re gonna move the ice cubes down. So move down one, or you can move that to the end. And it goes all the way to the end. Now we can bring that back to the top, just by highlighting where the box is, and you get the four point the arrows and then bring it all way to the top, that’s another way. Or another way we can bring tonic from the bottom to the top is actually type it in with a keyboard. TO, then it gives us the options, tonic, and then press enter. And that gets moved up there. And the same thing we can do with our salespeople, we can type in the names. We can put in John, press enter, and John gets moved up to the top of the list, or we can bring in Homer to second place. And as you can see, he’s moved in each item there as well. Now we can do the same thing in the columns. We can bring in 2014 at the start, and then 2013 and then 2012 goes to the end. So there’s a couple of ways we can do that. Now we can also move the fields around. One way is to right-click, and then it says, move. And you’ve got the products to the right to the end, or you can actually move the products to the columns area. So let’s move it to the end. So as you can see, salespeople have gone up and then the products have gone down a level, but the best way to do it is from the areas here. So you can move this around here, or if you wanna move it from row labels to the column labels, this is the best way and the quickest way to do it. Now we can also remove just by grabbing it and dragging it all the way back up there. Control + Z. Another way is from a dropdown box, you’ve got the remove field. And then finally we can actually right-click anywhere in there, and it says the options to remove products. So there’s a few ways where you can move and remove fields and items to make your Pivot Table to your liking. (upbeat music) There’s a couple of ways to show your field list. If you click in your Pivot Table, go to options and under show, choose field list, that’s one way. Let’s uncheck it. Another way is in your Pivot Table, right-click, and the last option is show field list. (upbeat music) If you wanna get rid of your field headers, for example, here row labels and column labels, all you gotta do is go into options, and then the last option on the right-hand side under show is called the field headers. Just uncheck that and you’ll see that they go away. (upbeat music) Let’s create a Pivot Table. Let’s grab our products and put into our row labels, salesperson into our row labels. Our sales here into the column labels and our sales in to our values area. Whoa, what’s happened here? We’ll get a count of sales. I’m sure you’ve come across is at least once. Let’s have a look in our data table. Look at this, in F2 we have a blank cell. Now Excel treats blank entries as texts, and therefore chooses to count rather than sum. So what we’ll need to do is go back to our Pivot Table field list and make some changes. In our values area, count of sales, there’s a down box, click on there and choose value field settings. Now in summarize value field by, we choose sum rather than count and press okay. And there you have it. Our Pivot Table is being analyzed by sum of sales. (upbeat music) There are a couple of ways to format the numbers when creating a Pivot Table. As a default format is in general format. Now the first way is to go into your values area and in the dropdown arrow, choose value field settings. And on the bottom left-hand corner, you have number format. You click on there, and you can make your changes from in there. Just cancel out of there. Another way, you can go into your options tab, and in the field settings, click on there, and then the dialog box comes up again and you can go into the number format and make your changes from there. Now I like the third option, which is click anywhere in the Pivot Table, right-click and choose value field settings. And you get the same dialog box, choose number format. And then in here you can make your changes to a number or currency and you have accounting and time. Depends on what values you’re showing. Now we’re showing sales. So let’s go into currency and we’ll put in some dollar signs there, and we’ll put negative four minus signs in red and zero decimal places. Press okay, and okay. And then you have it. Your numbers have been formatted and it looks much better than it was previously. (upbeat music) One to nine feature in Pivot Tables is that the values field are named sum of sales or count of sales to distinguish them. Now, if you want to just name them total sales or sales, then you can make these changes a couple of ways. In the dropdown arrow here, choose a value field settings. And then in the custom name, you have sum of sales. You can make the changes in there. So we can actually put in there, total sales, and press okay. As you can see, the name has changed there, but in your data table, it hasn’t changed there. It remained as sales. So what’s happening is that it’s only changed in your pivot cache and therefore you can only see it in here. Let’s say that we wanna amend that name instead of total sales we wanna put in sales. Press okay. We’ll get an error message. It says here, “Pivot Table field name already exists.” Well, that’s true because sales is already here. So a work around, is the click just after the S, and press the space bar. Now Excel recognizes that as a character, and then we can actually use that as a different name and then press okay and you have sales there. Another way we can change the field names is to click in the Pivot Table and go to options. And because we’re in now sales, we get the active field as sales. We can click in there and we can see that the change that we made. And let’s click on the column labels sales here. Okay, so we’ll have sales here in there and we can actually go in there and change it, and let’s call it financial year. And press the Enter key. And they’re changed to financial year. And also, as you can see, the column label name changes into financial year as well. So there’s a couple of ways to change the field names, just to make it to your liking. (upbeat music) We have our months and our sales in our Pivot Table. And we want to format to include a comma and no decimal places in our values. So what we need to do is just right-click anywhere in the values and choose number format, and then decimal place is zero, and you use the 1000 separator. So now let’s grab our sales again and drop it into our values just so we can analyze something again. And look at this, our formatting doesn’t maintain. Now, we’ll show you how you work around to fix for this. Let’s press Control + Z and go back to where we were before. And what we need to do is go into our Pivot Table tools and under options in the actions group, select entire Pivot Table, then select values. Press Control + 1 to bring in the format cells dialog box. And from in here, you can make your formatting changes. And now when we drop in our sales again, to make some further analysis, you can see the formatting has been kept. (upbeat music) We have our sales region in our row labels and our sum of sales in our values area. Let’s grab our sales again and drop it into our values area. Now let’s see what happens as soon as we drop it in there. We’ll get the sum of values field in the column labels. Now that happens because we have more than one metric in our values area. Now let’s change this to the count. And all we’re gonna do now is grab the values field and move it into the row labels. And you see, we have a different view of our metrics there. And we can also grab it and move it to the top. And then we see this different view once again. (upbeat music) In this Pivot Table, our report layout is compact form. Now if I wanna change it into an outline form, but without choosing that option. And there is a way. Let’s go back to show in compact form. Now under options and on the left-hand side options in layout and format tab, you have here when in compact form indent row labels. So let’s move it to the right by 10 characters and press okay. And as you can see, our salespeople have moved to the right, but they’re maintained in column A. So we get to feel as if we’re using an outline form, but we’re actually using a compact form. (upbeat music) We can also make changes to the layout of the report filter. Let’s go into options, and options. And we have here display field and report filter area. Our default is down then over. And in the dropdown box, we can choose over then down. Press okay. And as you can see, our report filter is in one row. Now let’s go back and choose down then over, and press okay. Now the second option here is report filter fields per column. The default is zero. You can actually change it to whatever amount you like Now let’s choose two per column, and press okay. So as you can see here we have two report filters per column, and we have the third one in another column. So say we’re dropping sales region into our report filter, you’ll go into the second column and let’s drop in customers into our report filter and it goes into our third column. So there’s a couple of ways where you can play around with your report filter. (upbeat music) Sometimes you may get error values in your Pivot Table like the one shown here. With a DIV on the name. Now we’re gonna fix that, click in that Pivot Table, go to options and options. Now under format, there’s an option that says, for error values show. Let’s tick that. And we can put anything in there. We can leave it as a blank and press okay. Or we can put in there a zero and press okay. Or we can write in there, error. So let’s do that and press okay. As you can see, the changes have been made. (upbeat music) Sometimes you comes across a Pivot Table with empty cells as you can see here. We can actually change that. We can go to options and options and we’ll get under format the, for empty cells show. So we tick that box and in there we can put in there a zero amount, and that feels in our Pivot Table blank cells with zero. Now, if you’re an accountant or an orderor and you go to your data table, you can see that in April, we had no transactions. So something’s gone wrong in there. So instead of having zero, which in accounting terms can be a credit in a debit summed up, so you can have minus 10 and plus 10, and that equals zero. But in this case, we have actually no transactions. So we can go back in there and click under options and options, or we can actually change that. Instead of saying, for empty cells show zero, we can say no transactions and press okay. And then you can make sure that there are no transactions in there rather than the zero values. (upbeat music) One of the thing that really annoys me within Pivot Tables, is that when you refresh your Pivot Table, the column widths go back to where they were previously. Now there’s a way around this. Under the options tab and options, there’s an option at the bottom here that says, auto-fit column widths on update. So upon a refresh it auto-fits that back to where it was previously. Well, let’s uncheck this and press okay. And now all we can do, we can move our columns and how we like them. And let’s refresh again. Right-click, refresh and I pressed them, they haven’t moved. (upbeat music) Now say that you have a shared workbook that you and your colleague keep updated. Now say you open these shared workbook and you need to refresh the data, you would go into the options and refresh. And sometimes you may forget. Now that is usually the case when you’re sharing with a colleague. So to avoid the mistake of working with Pivot Tables that haven’t been refreshed, a quick tip is to go into the options tab, and under options choose the data tab and then select the refresh data when opening the file. So next time you open this file, your Pivot Table will be automatically refreshed. (upbeat music) Now to print a Pivot Table, click anywhere in the Pivot Table, and go to options, select the entire Pivot Table. And then in the page layout, print area, set print area. And go to the file, and then under print, you can see that it’s in there. Now let’s go back. Say that you wanted to put in a page break in here, in between the years, we just click in there and choose breaks and insert page break. We’ll do the same thing for 2014. Now let’s go back to print. You can see our view here. If you press right, you can see the different pages. But we don’t get the titles of the Pivot Table. Now let’s go back again and go into our Pivot Table, go to options, and under options and printing, there’s a set print titles option there. Choose that, press okay. We’ll go back to our print preview, where you can see that in each page we have the Pivot Table titles. (upbeat music) We have our sales result from 2012 to 2014 showing for each month. And in our report filters, we have our products and salesperson. And all we can do is show each salesperson’s values into separate tabs. And to do this, you go on to the options tab and then under options dropdown box, choose show report filter pages. In here, you get a dialog box to choose which of the two report filters you want to show. Let’s choose the salesperson and press okay. And then when we press that, you’ll see at the bottom of the tab here that we get the different salespeople’s names in there. See that we get Homer Simpson, Ian Wright, John Michaloudis and Michael Jackson, that show their values for each of the years. We’re in Michael Jackson here hold on the Shift key and go all the way to Homer Simpson, and we grouped our sheets there. We know that because on top of the page, it shows the group in there. What we can do now, while they’re grouped, we can actually make a change into one, and then every one of them will get amended as well. So you can see there, we’ve got these there. So you got to format each one of them. Okay, now they’re still grouped, we can go to file and print. And in here, because they’re grouped, we have the four different salespeople in there and we can print to PDF. So let’s choose your PDF and then press print. We can call it individual salesperson reports. Press save, and it brings it up in here. We’ll go to the second page, third page and fourth page. Okay, let’s get out of here. And then make sure when you’re back in your Pivot Table, you right-click at ungroup the sheets. So that’s a quick way where you can see our report filters items on separate sheets with the filtered results. (upbeat music) Now there are different types of sub-totals that you can include in your Pivot Table. You’re not only limited to a sum. For example, you can include a count of transactions, the average sales, the maximum amount, the minimum amount, the product and so on. Let me show you. What you need to do is go into your Pivot Table field list and into your row labels area, let’s choose products, and then dropdown and go into field settings. And now we get our sub-totals and filters tab. Now it’s set at automatic, and we can change that. Choose custom. We can click on sum, we can also click on count, on average, maximum, minimum, and we have a few other sub-totals that we can include there, but let’s just include these and press okay. And look what happens. Each field item has its own sub-total for 2012, 2013 and 2014. Let’s scroll down. You can see for bottles here we have the sum, count, average, maximum, minimum. The same thing for ice cubes. Same thing for soft drinks and the same thing for tonic. Now, a Pivot Table has all that information summarized in a few rows. And it’s fantastic to have, if you wanna do some quick reports, quick metrics, all in one page. (upbeat music) We can summarize value fields by different calculations. Now to do that, we need to go into our Pivot Table field list and under sales, grab it, drag it and drop it again into the values area and let go. So we get a second calculation called sum of sales with the same results, but we can change that. Instead of sum, we can change that into a count. So click on the dropdown box and the value field settings, and we have a summarize the values by tab. And in here, we can summarize the value field by different types of calculations as you can see in here. Now, there are 11 different types of calculations. And now I’m gonna talk about the count calculation. So let’s double-click in there. And as you can see here in our values area, we get count of sales, and in our Pivot Table report we have our count of sales. So what the count of sales does is it counts all the cells that include text numbers and error cells. Now, one thing that it doesn’t include are blank cells. So watch out for that. If you have any blank cells, then it’s not going to count that in there. Now let’s check our numbers. So we have 48 transactions in bottles for 2012. So let’s go in here. Now I’ve filtered it by bottles and 2012. So if we go down here and we do our count, we’ll get 48. Now let’s manually count this, go all the way up. And as you can see here, count, we get 48. Now, if we have any blank cells in there, then it’s not going to include that in its total. So let’s check that. Let’s highlight a few cells and press delete to clear it. So we’ve cleared four cells in there. Now we’ll go back to our Pivot Table and right-click and refresh to update what we’ve done now. And you see there, 44. Now the count calculation will include all the cells except the blank ones. (upbeat music) The average calculation is like your normal average function. What it does, it takes the totals of all the values and it divides it by the number of values. Now we use the average calculation for sales for days to complete a project, for overdue days or for accounts payable or accounts receivable days. Now to include the average calculation, we have to grab our sales and drop it into our values area. And in the dropdown triangle, choose develop your settings, and then choose the third option, average and press okay. Now, as you can see here, we have our average values. To customize the numbers, we need to go into our average of sales field and in the value field settings. And on the left hand corner, we choose a number formats, and then we can choose the number, putting zero decimal places, and we can use a separator for the thousands and press okay, and okay. So as you can see our results much neater. So we have our average sales for each of our products and each are our salesperson for their respective years, as well as their grand total down here. And then we have the average sales from 2012 to 2014, which is $55,667. Now we can also get the average for the order dates. So in our data table, we have our order date in here. So what we can do is grab the order date, drop into the values area, and then choose the average from in there, okay? So now what we’ll need to do is to change the format in to a date, and then press okay and okay again. Let’s make this a little bit bigger. So we have the average date that the order gets placed. For bottles, for ice cubes, soft drinks, tonic and so forth. So you can do many things with the average calculation. And it’s a great metric to use when you’re doing your analysis. (upbeat music) The maximum calculation gives us the largest value from the values area. The things that you can calculate the maximum function with are sales, quantity unit sold, salary and cash position. Now to get our maximum sales, we need to get the sales and drop it into the values area. Now from the drop-down arrow, choose the value field settings, and then choose a maximum and press okay. So as you can see here, for each product and each salesperson, we have the maximum sales transaction that I made for that year. So Homer had his largest sale as being a 96,209, Ian Wright had 99,220, John Michaloudis had a 98,116, being his largest sale out of all his sales in 2012 for bottles. And Michael Jackson had 95,527 as being his largest sale. So obviously in here we have Ian Wright having the largest sale. So bottles will have the same amount as Ian Wright. So we can see here that from 2012 to 2014, that the largest sale amount was 99,878. So you can also go in and analyze and see which of the salesperson had the highest sale for each particular year and give them a bonus. So the maximum calculation highlight the extreme amounts from your data set, and you can do some pretty meaningful analysis from it. (upbeat music) The minimum calculation gives us the lowest value from the values area. The things that you can use to calculate a minimum sales, quantity unit sold, salary and cash position. Now to get the minimum sales amount, what we need to do is grab the sales and drop it into our values area. And from the dropdown box, choose the value field settings and then choose minimum and press okay. In 2012, for bottles, Homer’s smallest sale was 10,780. Ian Wright’s was 20,650, John Michaloudis’ was a 48,378, and Michael Jackson’s smallest sale was $17,030 out of all his sales in 2012 for the bottles product. So from this information you can see who made the smallest sale throughout the three years, and then go to that person and ask them why the sales were low for that period, and find out ways you can improve your product. (upbeat music) The product function multiplies all the numbers given as arguments and returns a product. For example, let’s type in the product function and choose our first number which is 25 and a comma. So it multiplies 25 by 0.4, press comma. And then it multiplies that result by the number two. Close brackets, and we’ll get out number 20. So in our analysis here, we want to know which month has products that were sold with no defects. So I wanna know which month had a flawless defect rate. So we wanna show a defective product with the number one, and a non-defensive product with a blank. Now we got a little example here that I can show you. So the first of the first 2012, that day later, and on the third of the first 2012, we had a defect, we had a defect and we had a defect. Now down here, we have another example with a defect, another defect, another defect. And the third example, we have three days with no defects. So let’s do our product function here. And let’s choose these cells. So if we have three defects and then we’ll get the number one. So obviously our result will be a defect. Now let’s copy this formula, right-click and paste that in here. So if we had at least one defect and the rest are all non defects, then we are gonna get a result of a one. So that means that we have at least one defect during that period or that month. So that month wasn’t a good month. We wanna have zero defects. So let’s copy this formula into our next example and we’ll get a zero. So what it says here is that during our three days, we had no defects and we get our return of zero, which means a great result for our company. Now let’s go to our data table. And what I’ve done is I’ve included another column here with blanks and ones. So, as it goes all the way down here, these random numbers, and we have defects and non defects. So what we’re gonna do is get our defects from our Pivot Table and drop it into our values. Now we don’t wanna count of defects. What we wanna do is choose value field settings and go to our product and press okay. So what this has done, it has multiplied all the defects with all the non defects during that particular month. So if we give a zero that means we had our flawless month and that’s a great result for our company. Now we can check this. Let’s go to one of the zeros in here and double-click. And as you can see on the defects column here, it’s all blank. So we had no defects. This is fantastic for product managers and quality managers, because zero defects means a great product and a happy customer. (upbeat music) In our example here, we want to find out what percentage of our total transactions are overdue. Now let’s go over to our data table. And in here we have our overdue days column, which shows us the number of days elapsed from the customer payment date. So we have here lots of overdue days. And also we have a comment here, which says paid when our customer has paid. So we have a few paid customers and lots of unpaid customers. Okay, so let’s go up and go to our Pivot Table. So let’s click in our Pivot Table here. On the left we have our financial year, and let’s grab our sales and drop into our values area. And from our dropdown, we choose value field settings and choose count. So it’s gonna count all of our transactions, and we have 576. Now let’s rename this, instead of count of sales, we rename it to total transactions. Okay, so let’s get out our overdue days and drop it in here and choose count numbers. Any customer with a number means that they’re overdue. So this is gonna return us to the number of overdue customers. Let’s press okay. Okay, so we have our numbers here and we can change this to overdue, overdue and press okay. So let’s go through our formula. Let’s choose our number of overdue transactions, which are in here and divide it by the total transactions in there and we’ll get 55%. So 55% of our total transactions are past due, which is a bad result. (upbeat music) In statistics, standard deviation shows how much variation from the average exists. So in our graph here on the top, we have our X-axis, which shows the values and our Y-axis, which shows the number of data points. So in our graph here, we have a normal distribution. And our average is right up in the middle. So this indicates a low standard deviation, which means the data points tend to be very close to the average, and we get this bell shaped curve, which is steep. An example of this may be the daily high temperature for a coastal city will be less than that of an inland city. Now higher standard deviation will indicate the data points are spread out over a large range of values which shows volatility. An example may be money. So a standard deviation may mean the risk that a price will go up or down. Here the bell curve is relatively flat. So what we’re gonna get is something like a straight line here. Now in Excel, we can also do a standard deviation graph. As you can see the bottom here, we can represent it by a column graph, and then we can get a shape similar to the one shown here if we have a normal distribution. Now let’s create a graph using our data table. We’ll go into our data table and insert pivot, and we’ll go into our existing worksheet and let’s put it into here and press okay. So what we’re gonna do now is find out the units sold and group them, and then find out by using the count of unit sold, how our data would be distributed. Let’s get our units sold and we’ll put into our row label. Now let’s group of this. Now in the next chapters, we’re gonna talk about grouping. Okay, let’s right-click. And click on group. And we have our dialog box that comes up, and we could start at a pretty determined minimum level, which gives us as being 1,011 and ends up 79,902. But we can start at any point. Let’s say zero and end at 80,000. An increments of 10,000 we’ll keep that and press okay. So we have our groupings in there. Now the next step is to get our unit sold again and drop it into our values area. And we get our count of units sold, which is what we wanted. Now, from in here, we can create a graph to see whether we’re gonna get a normal distribution or whether it’s gonna be volatile and have a flat graph. Now, our Pivot Table here says that 17 transactions lay between zero and 10,000 units sold. 79 transactions are between the 10,000 and 20,000 units sold mark and so on as you can see here. So let’s insert the graph, go to pivot chart, and let’s insert an area graph ’cause this will show a much better, and press okay. Let’s customize a couple of things. Let’s take out all the field buttons on chart, and we can just click on that and get rid of the chat name. So let’s just put up here, and we can click on the axis name and get rid of that. So as you can see, we have a pretty flat distribution. We’ll then get the bell curve as per our chat on the left here. And the reason is our standard deviation’s high. Now let’s check that. Let’s create another Pivot Table. Go to insert, pivot, and go to an existing worksheet. And we just put it down here. Okay, so now we’re gonna do is we’re gonna grab our units sold and we’ll get our average of all the total units sold. Now to get that, we just click on the dropdown box, value field settings and get the average. Now, the next thing we can do is, again, drop in the unit sold. Now, instead of choosing the dropdown box, we can actually go on field settings in here. And from there we can make our selection. So let’s get our standard deviation. Now the P signifies that we’re using a whole population. So that’s true because we’re using all of our data, we’re not just sampling 10 transactions. We’re using everything. Now for sampling a few transactions, we use a standard dev. So for our purpose, we use a standard dev. P, which means population, and press okay. Okay, so now we can get our values here and from column, we can move it over to the labels. So we can see it in much better. And then we can format these as well. One thing we haven’t done is the average. The average, okay, there you go. Okay, so what it says here, our average is 44,500, which is around here in the middle point. Okay. And our standard deviation is 20,689. So what it means is you can go either way to the left or right of 44,000 by about 20,000. So we have a high volatility there. So therefore, as you can see, our graph is pretty flat. Now, if our standard deviation was somewhere between zero and 5,000, then we would have got a graph similar to this. Let me get my squiggly line. And it would have been something like this. Okay. Would have been about there, and then like that, and then over there, would get a normal distribution. Okay. Maybe I can format the shape in red so you can see it better. So we would have had this if we had a low standard deviation, but as we have a highest end deviation, we get this graph, which is pretty much flat as you can see there. And which means that our unit sold can vary. It can be from zero to 10,000, or it can be from 70,000 to 80,000. So we have a high volatility there. So by using the standard deviation, you can see the variation that you get from your average and determine whether your product is volatile or not. So it’s a pretty great tool to have when you’re analyzing your products. (upbeat music) The variance calculation, measures how far a set of numbers are spread out. A small variance indicates the data points tend to be very close to the average. A high variance indicate that the data points are very spread out from the average and from each other. So let’s create a Pivot Table to highlight the variance. So let’s insert Pivot Table and go through our existing worksheet. And we’re gonna put it in there and press okay. So in our rows labels, we’re gonna put in our products and our sales month, and in our values, we’re gonna drop our units sold. And from the dropdown box, we’re gonna get our average units sold. So we can see where our average is at for each product. Now let’s right-click in there so we can format the numbers. And let’s use a number with no decimal points. Now next is we’ll get our standard deviation. So let’s put in the unit sold again, and then let’s choose a standard deviation population and press okay. So we have a one here and again, we can format our fields in there. And finally just get our unit sold for the third time. So we can get our variance. From the dropdown box, value field settings. Let’s use the variance P. Variance P means variance population. It means that our data set is a whole data set, and we using all of our population before using a few rows of transactions within all of our population and we use the variance sample which is indicated by Var. So let’s format the fields here again. Okay. So as you can see here, we have a very high variance and also a very high standard deviation. Now, if you note in here, we get one value here, which is very low. So if we drew down to here, then we’ll see that our units sold for ice cubes in June was pretty close to the average. So to test that, let’s get our unit sold here and let’s see what our average is. Now, our average is about 34,739. So let’s see our transactions. Our transactions pretty much around that 34, 40,000 mark. So our variances is very, very low. So that’s the only value here that we have pretty low variance or standard deviation. We can actually use this table to highlight months where we’ve had a low variance. And that means that our product sold a consistent amount of units. (upbeat music) In chapter 2.1, we created multiple sub-total, by going into our row labels and then choosing products, field settings, and then under sub-totals and custom, selecting the sum and average. And as you can see in our Pivot Table, each shown here under bottles, ice cubes, soft drinks, and tonic. Now another way we can do this is right-click in there and press field settings, and we can change it from in there. Okay, so now the grand total doesn’t show us an average or a maximum, it only shows us the sum. So what wanna do is put in there some extra grand total. Now there’s a way around this. First of all, we need to go to our data table and in our table, just add another column field named grand total, press enter. And because we’re using a table it’s added automatically. So that’s all we need to do. We don’t need to add any details in there. We just need the field header. Let’s go back to our pivot, right-click anywhere in here and press refresh. Now on the right-hand side, you’ll see that the grand total has been added in there. Now let’s grab the grand total and drop it on top of the row labels. Okay. So it’s shown up here. So the next thing we need to do is press the space bar and press enter. So we get rid of the name. In our new blank field, we right-click, and then choose the field settings. And in here we can use a custom and we can have sum, we can have account, average, maximum, minimum and press okay. Now, as you can see, it has gone all the way down here. It’s added that information at the bottom of the group. So what we need to do now is get rid of the grand total, click in the grand total name, right-click and choose remove grand total. Now we have our different grand totals summarized by sum, count, average, maximum, or minimum for the whole data set. (upbeat music) Now, there are a few ways to access the field settings and value field settings. Now let’s talk about the field settings first. In our Pivot Table field list on the row labels, under your first field and the dropdown box, choose fill settings, and then custom, and choose from in their sample count. Now, for this to work, you need to have at least two fields in your row label or in your column label. Now, the other way is to choose anywhere in our Pivot Table and make sure we select one of our items, so our ice cubes. Right-click, and then choose field settings and we can add in there. So let’s add the average in there. And the third way is to go into our Pivot Table tools tab under options and field settings. And now we’re under products and choose that, and we can put in there maximum and minimum. Now let’s talk about the value field settings. In our Pivot Table field list, under the values area down box, choose the value field settings. And we have it as sum, but we can change that to count, and press okay. The other way is to right-click anywhere in the Pivot Table and choose summarize values by, and we can change it from there. Let’s choose average. The other option is again, is to right-click anywhere in the Pivot Table and choose value field settings, and then we can choose a maximum. Another way is to go into where our Pivot Table tools tab in the ribbon, under options field settings, choose there. And we can change from there, let’s put minimum. And again, in the options tab under calculations, we have summarize values by, we can click that and we get our different options. Now we can click on more options and we can count the numbers. So it depends on what you’re more comfortable with. You decide what’s best for you. (upbeat music) In our example here, we want to find out what bonus you pay per zone and per year based on the channel sales made. As to do that, first let’s go to our data table. And what we’ve done is we’ve included zone numbers. Zone one, two and three. And also we’ve added a new column called channel sales. So we have our channel sales that pertain to each particular zone for each transaction. So let’s create a Pivot Table. Go to insert and the Pivot Table and existing worksheet, and let’s choose A1, press okay. So in our Pivot Table, field list, in our row labels, we’re gonna put in our months and our zones. In the column labels, we’re gonna drop in our financial year. In our values area, we’ll grab our channel sales and our report filter we’ll have our sales quarters. Now, one thing is let’s get rid of the grand total, click in there, right-click and then remove grand total. And we want to choose only Q1 for our example. So we need to do a formula that shows us the sales for 2012, zone one, two and three, and multiply by the bonus to be paid in the respective years. Now to do that, we’ll need to have each zone one, two and three in each month. Now we don’t have that because in February zone three, there weren’t any sales. And in March in zone two, there weren’t any sales. And we need to bring that up, regardless of any sales being made. Now to do this, we need to click anywhere in the row labels, and right-click and choose the field settings. Then under layout and print, choose the show item with no data So if we check that box and press okay, we’re gonna show the items that don’t have any channel sales. And now we can make our formula. Let’s put in sum product and choose 2012 January, press comma, and then choose the respective bonus to be paid here, which is 2012 for zone one, two, and three, close brackets. Now we’re gonna move this formula down and we need to make sure that the rows in here are an absolute reference. So number six, and number eight should have a dollar sign in front of them. Now, a quick tip is to click anywhere in there and press F4 twice, and that makes the row six, an absolute reference, or we can just put in our dollar sign and press enter. So we can move this across. So now let’s grab this formula and drag it down so we can feel in the February month. Double-click, and let’s just drag this all the way down. And as you can see, because of the absolute reference, the cell reference doesn’t move in there. Okay, and press enter. And then we can move that across and double-click 2014 with 2014, perfect. Now let’s finish off by dragging down to March. Double click and grab that and then go all the way across. Okay, so we have our three months, now let’s put in our sub-total. Now to do that, we just need to highlight at the bottom there and press the AutoSum and it will automatically sum it up. So let’s make this bold. And in here we can just put a comma and get rid of decimal places. So now, finally let’s put in our months where you just press the plus or equal sign and then reference it into cell A5 and press enter, and the same thing for February, and the same thing for March. Now let’s put in our total name in there. Plus we can actually reference the filter and then put in the end and then reference the name that bonus to be paid and press enter. So we’ll have Q1 bonus to be paid. Now let’s fix this up a bit and put in a space. Now to do that, we can actually put in an end in there and then in brackets and have a space. So that will give us the space. So we have our Q1 bonus to be paid, right-click and make that bold. So now we can make this interactive. Let’s choose Q2. So everything changes. The months, the title and our bonus to be paid. Now one thing we need to make sure is go into options and then get rid of this auto-fit column widths on update. So every time we make an update, these column widths stay the same. So the update being about making a change into our filter selection, Q3. As you can see there, it stayed put. So Q3 gets updated automatically and then Q4 as well. So here we have an interactive channel bonus to be paid per quarter. (upbeat music) We want to show here the unique occurrences between the channel partners and the products. To show our unique count between our products and our channel partners, it’s impossible to do with a Pivot Table. But what we need to do is insert a sum product formula in there and then pivot that information to give us our results. So our formula here says to look up in column B and in column C. And by using the sum product formula, it’ll give us trues and falses. So if we get one true in here and another true in here, then a true and a true equals one. Anything else is a zero. So if we get two matches of the same channel partner and product, then that’s gonna be two trues. So obviously that’s more than one. So if it’s more than one, then we’ll wanna show it by a zero. So that means it’s not unique. If there’s only one unique combination then we’ll want to show it as a number one, which means a unique combination. Now let’s escape here. And as you can see here, the first couple of values, because it’s the first time they’re being purchased, they’re all unique. So they’re all depicted by the number one. If we go all the way down here, and you’ll see Acme purchased soft drinks. Well, Acme purchased soft drinks up here. So it’s shown as a number one here ’cause it was the first time it was purchased. And then down here, number zero, because it was a second time it was purchased. So it goes all the way down here and it does the same thing for each row. Now let’s go to our Pivot Table. And what we’ve done here is we’ve put in our sum of unique combinations in here. And then we dropped in our products on the left-hand side. So in here we can see that there are 54 unique customers that purchase bottles. There are 63 unique customers that purchase ice cubes. There are 63 unique customers that purchase soft drinks, and there are 57 unique customers that purchase tonic. Now to see which customers are part of this number, then we can just grab the channel partners here and drop it into the row labels, and we’ll get our list here. So we get all our list of unique customers that purchased the products. (upbeat music) The percentage of grand total calculation displays values as a percentage of the grand total of all the values or data points in the reports. So what it means is that each individual data point here will show as a percentage of this grand total here highlighted in a red border of $32 million. So to include the percentage of grand total, we need to activate our field list, right-click and show our field list. Now let’s grab our sales and drop it into our values area. And in their dropdown arrow, value field settings, and choose show values as, and in the dropdown box, choose percentage of grand total. Now let’s change our name to percentage of grand total, and press enter. So we have our percentages in here as you can see. So each individual percentage will sum up to 100%. So our field items here sum to 8.26% which is up there. And if we sum across the columns, that’s 7.32, and that’s confirmed in there. So if we sum the 26%, 25, 25 and 23, that equals to 100%. And if we’ll go down here and sum base rate amounts, then that equals to 100% as well. So each value item is divided by the grand total to give us the percentage of grand total calculation. (upbeat music) The percentage of column total calculation displays all the values in each column as a percentage of the total for that column. So we have our years in our columns here, 2012 to 2014. And in the bottom, we have our grand totals and they’re highlighted in a red border. So each individual field item here will be a percentage of its grand total. So what we’re gonna get is our proportion of sales for each sales rep in each quarter in 2012, in 2013 and in 2014 respective to the totals. So to include the percentage of column total calculation, we click in our Pivot Table and grab our sales, then drop it into our values area. From the dropdown arrow, we choose the value field settings. And then we show values as, and from the dropdown we choose percentage of column total. And then we rename this to percentage of column total and press enter. So as you can see here, we have the percentages that make up each column total. So we can check this. If we highlight the 2012 Homer Simpson’s sales, they add up to 25.49%, which is up here. So if we hold down our Control key, and then with our mouse button, choose each sub-total, they should equal to 100%. As you can see here at 100% and we have here 100%. And the same thing is done for our 2013 and 2014 numbers. (upbeat music) The percentage of row total displays the value in each row as a percentage of the total for the row. So everything here highlighted in red will be 100%, and we are gonna get the percentages over the three years for each sales rep and each quarter. Now to include our percentage of row total, we click in our Pivot Table, and in our Pivot Table field list we’ll grab our sales and drop it into our values area. From the dropdown arrow, we choose the value field settings and in show values as, we select the dropdown box and choose percentage of row total. And we can change the name here to percentage of row total, and press okay. We can see that we have 100% in each of our rows and in our individual rows, if we hold down the Control key and choose 2012, 2013 and 2014 for Homer Simpson, we get 100%, which is correct here. So we can see that the proportion of sales that have occurred over three years. And the same thing can be broken down into Q1 for each respective sales rep. So let’s get Homer Simpson again and press down the Control key and choose 2013 and choose 2014. And again, we get 100%. (upbeat music) The percentage of calculation displays the value of one item, which is also called the base field, as a percentage of another item, also called the base item. Now to put this into an example, we want to find out the change of sales from year on year. So we wanna see the change in 2003 versus 2012, and also the change in 2014 versus 2013. So to do that, we click in our Pivot Table and we grab our sales and drop it into our values area, and from the dropdown arrow, choose value field settings, you show values as. In the dropdown box, we choose the percentage of calculation. And in the base item we choose previous, in the base field we choose financial year. So the way to read this is we’re showing values as the percentage of the previous financial year. So percentage of previous financial year and press okay. And now we have our percentages. Now, obviously 2012 doesn’t have a previous year, so it will always be 100%. And if we look at 2013 here for Homer Simpson’s sub-total, we can see that in 2013 it was 112% of the 2012 value. And in 2014, it was 90% of with the 2013 value. So from 2.9 million it went down to 2.7 million and that’s correct. And you can also see here in the grand totals, in 2013, we had an increase of 6.06%. So from 10.3 million to 11 million. And in 2014, our sales reduced to 96.73% from 2013, or you could say it was a drop of 3.3%. So one minus 96.73%. Now let’s do another example. And here, we have our sales regions over the three years, and we’ll wanna compare our sales to the African sales. So we’re comparing the American sales to the African sales, and then we wanna compare the Asian sales to the African sales and also the European sales to the African sales. Now to do that, we click in our Pivot Table and we’ll grab our sales and drop it into our values area. From the drop-down arrow, go to value field settings, show value as percentage of, and what we’re gonna do now is we have our sales region as our base field. And we want to put our base item as Africa. So we’re gonna show the percentage of African sales. Press okay. So obviously African sales will be 100% always. So what it says here in 2012 is that Americas is 94% of the African sales and Asia is 96% of the African sales, and Europe is slightly higher than the African sales for 2012. We have the same calculations for 2013 and then 2014. And we can also put in here products and we can compare that to one particular product being your best product and see how the other products relate to it. (upbeat music) The percentage of parent row total is a new calculation in Excel 2010. It shows us an item’s percentage based on his parents sub-total. So the calculation is the value for the row item divided by the value for the parent total row item. So in here for Homer Simpson in Q1, what it will give us is the percentage of 776 into $2.6 million. And then we’ll do the same for Q2, Q3 and Q4. So it’ll give us a percentage of 100% here, which is the total of its parent total, which is $2.6 million. Now to do this, we grab our sales and drop it into our values area. From the dropdown arrow, choose the value field settings and under show values as tab, from the drop-down, we choose the percentage of parent row total. And press okay. So as you can see here, Q1 is 29% of the total. Q2 for Homer Simpson is 24% of the total. Q3 is 22% of its total. And Q4 is 23.6% of its parent total. So if we sum all this up, you can see it’s 100%. And also the Homer Simpson’s sub-total and the subsequent salespersons sub-total, if we sum those up by holding down the Control key, they too will equal into parent total, which is the grand total, which is 100%. As you can see here, 100%. The same calculation is done in 2013 and 2014. Now let’s go on to another example. So all we have now is our years and our months in our row labels. Let’s scroll down to see that. And we want to get the percentage of each month into the parent total which is 2012. And in here or it will be 2013 and 2014. So once again, let’s grab our sales, drop into our values area and let’s choose our percentage of parent row total and press okay. So here we have our percentages. So once again, the January sales are 7% of the whole 2012 sales. February sales are 8% of the whole 2012 sales and so forth. Now let’s check by highlighting all of 2012, and that should equal to 100% of the parent row total, which is 10.3 million. And this is a great feature. And once again, it’s new in Excel 2010, and you should give it a try. (upbeat music) The percentage of parent column total shows an item’s percentage based on parent’s sub-total. So the calculation is valued for the column item divided by the value for the parent total column item. So in our Pivot Table, we have our sales reps and in our columns we have let’s show our field list. So in our columns we have our sales quarter on the top, and then the bottom, we have our sales years. And we have our sub-total for each quarter. So the percentage of parents total column will give us the percentage for Homer Simpson in Q1, based on its parent column total, which is 2.3 million and so on for Ian Wright, Johnny Michaloudis and Michael Jackson. And this will happen in Q1. We will also have it in Q2 in Q3 and then in Q4. So let’s put in our parent column total. So to do that, we grab our sales and drop it into our values area. From the dropdown arrow, which has a value field settings. And it show values as, we select the percentage of parent column total and press okay. So as you can see, we have Homer Simpson, 33%. Let’s hold down the Control key and press the 2013 amount, and then also the 2014, and that equals to 100%. So we have 100% of Homer’s parent column total, which is 2.3 Million. And the same thing happens for the rest of the sales reps. And if we go on to Q2. Let’s grab Homer’s again for 2012, 2013 and 2014, and that’s 100% of it’s parent column sub-total for Q2. And then for Q3 and Q4 the same calculation. (upbeat music) The percentage parent total calculation shows the sales percentage based on it’s chosen parent base field item total. So the calculation is value for the item divided by the value for the parent item of the selected base field. Now to include the calculation of percentage of parent total, we click in the Pivot Table and right-click, so we can show our field list. And in here, we can see that in the row labels, we have products, salesperson and sales quarter. So our selected based field will be the products. Now let’s grab our sales and drop it into our values. And from the dropdown arrow, choose the value field settings. And in show values as, in the dropdown arrow, we choose a percentage of parent total. Now, from in here, we have to choose our base field. Now our parent based field is products ’cause it’s right on top. So we have to choose products. And before we do anything, let’s rename this to percentage of, we can call it parent total, or we can call it product total. You can say parent and put here product, so we can distinguish them. And press okay. So here we have the values. So if we highlight Homer Simpson’s values for bottles, they equal to 25.19%, which is a sum here. So all of these, we’ll hold down the Control key. Now all these different sales reps totals will equal to 100%. As you can see that 100%, which is the 2.7 million. And the same thing happened for ice cubes. So let’s highlight that. And that will equal to 100%. So it’s 100% of 2.4 million. And for the soft drinks, we have 100% of 2.6 million. And finally for tonic, again, that should be 100% of the $2.5 million of sales. And the same thing, let’s scroll up. And the same thing happens for 2013 and 2014. (upbeat music) The difference from calculation calculates the difference of one item from another item. So what we’re gonna do here is get our months and see the difference between one month and its previous month. And we’re gonna also do another calculation where we see the difference between one month and the corresponding month from the previous year. So let’s click on our Pivot Table and we’ll go into our sales and drop it into our values area. And from the drop-down arrow, we choose the value field settings and show values as. In the dropdown arrow we choose difference from. Our base field will be the sales month because we’re comparing sales months. And the base item will be previous. So the previous month. So the way to read this is the difference from the previous sales month. Now let’s change the name here to call it diff. from previous month, and press okay. In our Pivot Table, we have the difference from the previous month. So the 96,000 is the difference between January and February. And then you see from February to March, we have a drop of 83,000. Now let’s format the numbers here. So we can right-click and number format. We can go to number. No decimal places, 1000 Separator, and then we’ll put in the red for any negative values. It just stands out better. We can see there that’s much better. Now let’s do another calculation. We’ll put in our sales and we’ll get the difference from the previous year. So again, the dropdown arrow, show value as, choose difference from, and now we’re gonna get the financial year and previous. So we’ll get the difference from the previous financial year. And press okay. And in here again, we can format the numbers. So what it says here, it’s comparing January, 2013 with January, 2012. So difference is 100,000 increment. And then it’s getting February, 2013 and comparing it to February, 2012, and that’s a $42,000 increment. As you can see in a 2012, it’s all blank because there’s no sales in 2011. So it starts in 2013. And then in 2014, it compares the January, 2014 amount to the January 2013 amount. Okay, let’s go into our second Pivot Table example. And now we have our salesperson on our row labels and our years. So what we wanna do now is compare our sales to one salesperson. So we’re gonna compare Homer Simpson. So to do that, we’ll grab the sales, drop it into our values area, dropdown box, value field settings, show values as, then choose different from. And we choose salesperson, and our salesperson will be Homer Simpson. So we’re gonna see the difference that each salesperson has on Homer Simpson. And press okay. And let’s format the numbers, and press okay. So what it says here is that Ian Wright in 2012 had $26,000 more sales than Homer Simpson. Johnny Michaloudis had 80,000 less sales than Homer Simpson. And Michael Jackson had 148,000 less sales than Homer Simpson. So the same thing in 2013, it’s comparing Ian Wight 2013 to Homer Simpson, 2013. John Michaloudis 2013 to Homer Simpson, 2013 and Michael Jackson, 2013 to Homer Simpson, 2013. And the same thing for 2014. (upbeat music) Just like in chapter 3.8, where we had the dollar difference from calculation. Now we have the percentage difference from calculation. So what this is, it calculates the percentage difference of one item from another item. So in our example, we’re gonna get the percentage difference of one month to previous month. And then we’re gonna get the percentage difference from one year’s a month to its corresponding previous year’s month. Now let’s click in our Pivot Table. And in our sales, we grab the sales and drop it into where the values area. From the dropdown arrow we choose value field settings and under show values as tab, we choose the percentage difference from calculation. And then we have the base field as sales month and then the base item as a previous. So this reads as percentage difference from the previous sales month. And let’s change the name to percentage diff. from previous month. And press okay. And we can format the numbers. We’re going on to custom and choosing in here. And then we’ll just put in a percentage writing of this. So if it’s a positive number, it’ll be in black, if it’s a negative number, it’ll be in red. And press okay. So we have the percentage of difference from the previous month which means that there was a 12% increment from January, 2012 to February, 2012. And then in March, we had a 10% drop from its previous month. Now let’s put in our new calculation. Dropping our sales value there, and then we can choose the percentage difference from. And now we’re gonna calculate the percentage difference from the previous year. So we choose the financial year in our base field and our base item is previous. So this reads as percentage difference from the previous financial year. And then press okay. And in here we can conform at the numbers and because we had our formatting done before, we can go to our last option and choose that. So this says that in January, 2013, we had a 30% increase from January, 2012. And then in February, 2013, we had a 5% increase from February, 2012, and then so on. Okay, let’s go on to our next example. So we want to calculate the percentage difference from the sales of Homer Simpson. So to do that, we’ll grab our sales and drop it into our values area, which is value field settings, show values as, and then percentage difference from, and we have salesperson as our base field, and then we’re comparing our sales just to Homer Simpson. And then press okay. And then we can format the numbers again. We go to custom, all the way through the end, we have a previous selection. So what it says here is that Ian Wright has 1% more sales than Homer Simpson in 2012, John Michaloudis had 3% drop in sales compared to Homer Simpson and Michael Jackson had 6% drop in sales compared to Homer Simpson. And the same thing is analyzed in 2013 and also in 2014. (upbeat music) The running total in calculation displays the value for successive items in the base field as a running total. So what that means is it will show you your year to date values. So what it’ll do is it’ll sum January and February and put it in here. Then it’ll sum the February year to date total with March and then put it into the next column. And then it’ll sum the March year to date amount with April and then all the way to the bottom where it’ll end up having the total amount of four 2012, which is $10.3 million. So let’s go and put in this calculation. We grab our sales and drop it into our values area. In the dropdown arrow we choose a value field settings, and under show values as, we choose the running total in. Now we have to choose the base field. And because we are doing the running total in for the months, we keep it selected as sales month. And then we can change the name here to the year to date and then press okay. So in our Pivot Table, we have January as 771,000. Now February is a 1.6 million, which is the sum of Jan and Feb. As you can see there, 1.63 million. In March, we have 2.4 million, which is the sum of January, February, and March, 2.4 million, and so on and so on. And so in December, we’re gonna end up with 10.3 million, which is our total for 2012. Now in 2013, again, it starts from January. It adds February, and then it adds March and April and so on to end up at 11 million, which is a total for 2013. And the same thing happens in 2014. Now this calculation is fantastic to have, because it shows you your annual sales on any given month. (upbeat music) In chapter 3.10, we had the running total in, and now we have the percentage of running total in. We each calculate the values as a percentage for successive items in their base field that are displayed as a running total. So here, we’re gonna get our year to date percentage. So we’re gonna see here the proportion of the January sales to 2012. And then we’re gonna move on to see the February year to date sales as a proportion to its total 2012 sales. Then we’re gonna see the March year to date sales as a proportion to its total of 2012. And then so on until we reach 100% in December. Now to add this calculation, we click on our Pivot Table and then we’ll grab our sales and drop it into our values area. From the dropdown arrow, we choose value field settings. And then under show values as, we choose the running total in percentage. And in the base field, we have to choose the sales month because it’s the field where we going to get our running total in from. Then we’ll press okay. So all we’ve got now is January, which is 7% of the 2012 sales of 10.3 million. And in February it shows here the February year to date sales as a portion of 2012. And in March, we have the March year to date proportion of 2012 sales. And then it goes on and it increments each month until we reach 100%. So we can see here that in June, for the first six months, we had achieved a 48% of our total 2012 sales. Now if move on to 2013, the same thing happens. So we have our January proportion on 2013, then it adds the February sales to give us the February year to date sales proportion on 2013. And then so on until we reach 100%. So we can see that in June for the first six months, we achieved about 51% of the total 2013 sales. And in 2014, the same thing happened. And as you can see, you can do a lot of great analysis to see how your sales are tracking on a year to date basis. And you can also compare it to the previous year’s running total in percentages. (upbeat music) The rank smallest to largest circulation displays a rank of selected values in a specific field, listing the smallest item in the field as one, and each larger value with a higher rank value. Now in our Pivot Table, we have our salespeople in our row labels and our dates on the column labels. So what we’re gonna get is a number one value for the lowest sales in 2012, and a number four value for the highest sales in 2012. And the same thing will happen in 2013 and 2014. So to do this, let’s grab our sales and drop it into our values area. From the dropdown arrow, we choose the value field settings and show values as. In the dropdown arrow, we’ve go all the way down and choose the rank smallest to largest option. And in the base field, we’re gonna choose which field we want to rank. Now we want to rank the salespeople. So we choose the salesperson and in the custom name, we can change the name to rank small to large. And then press okay. So we get here number one being the lowest value of 2.4 million. And then the second lowest is 2.5 million. The third lowest is 2.6 million and the largest is 2.67 million for Ian wright. Now if we go to 2013, we have a ranking for that year as well. And 2014, we have a ranking just for that particular year as well. So you can quickly see here that Michael Jackson in each of the three years has the lowest rank. And you can go and find out why his sales are the lowest amongst his peers. (upbeat music) The rank largest to smallest displays a rank of selected values in a specific field, listing the largest item in the field as one and each smaller value with a higher rank value. In our Pivot Table, we have our months in our row labels and our years in our column labels. And what we’re gonna get is a ranking value in each of the years, and where one will be the highest sales and 12 being the lowest sales because we have 12 months. So to do this, let’s go into our Pivot Table field list. We’ll grab our sales and drop it into our values area. From the dropdown arrow, we choose value field settings, and then under show values as, we go to the dropdown arrow and all the way down and choose rank largest to smallest. And in our base field, we have to choose which field we’re going to rank. Now we have our months in a row labels, so we’re gonna rank our sales month. And finally let’s change the custom name to rank large to small, and press okay. Okay, so we have in 2012, number one being July with $1.05 million and the lowest being January at $771,000. So you can quickly see which items are ranked highest and which items are ranked lowest. Now in 2013, we can see that December had the highest sales and November had lowest sales. And in 2014, we can see that January had the largest sales and August had the lowest sales. You can see there’s a big variance in each of the years. There’s no consistency in the value. So you can make some quick analysis with these numbers of rank largest to smallest. (upbeat music) The index calculation shows us the relative importance of a cell within a column. So in our example, we have our products on the row labels and our regions on the column labels. So the index will show us how important a product is to its region. The higher the number, the more important that product is to that region. And to show you an example, let’s grab our Pivot Table by clicking in the top left-hand corner and pressing Control + C in your keyboard. And then in here we can right-click and paste everything in there. So let’s go on to our Pivot Table field list and grab our sales and drop it into our values area. From the dropdown arrow, we go to value field settings and choose show values as, and in the dropdown box, we’ll go all the way to the end and choose index. And we can change the name to index. And press okay. So now let’s get rid of the sum of sales, just so we can have the index values. Now, finally, right-click and format the numbers, and we can put in two decimal places and press okay. So now we have our index on the bottom and our sales on the top. So for the bottles, you can see that Americas has the highest amount compared to its other regions. So what that means is that if there was a price change in the bottles product, then Americas will have the biggest effect because they have the higher index amount. Now we can see this, that Americas has the largest sales all across the region and also in its column grand total. So it calculates it based on the row total and grand total. And also the grand total which we have in the bottom right-hand corner. Now let’s calculate this. We have the calculation here of how the index is calculated. So let’s grab the value in cells. In our example, we choose the American’s bottles. So press plus, and we can reference Americas and then multiply by the grand total of grand total. So 32 million there. And press enter. So we have our amount there. Now next let’s grab our grand row total. Grand total here and multiply it by the grand column total, which is the 7.9 and press okay. And finally, L4 divided by L6, which gives us 1.1 which you can see there. And the same calculation happens for each of the other values within the regions and products, and they’re all depicted here. And the grand total will obviously be one. So we’ll see for ice cubes that the African region has the most important value. In soft drinks, we have Europe and in tonic we have Asia. So any price change in those products, then the biggest effect will be in the regions which have the higher index. (upbeat music) Now there are a few ways to get the show values as dialog box. In our tutorials we’ve using the Pivot Table field list and going from the dropdown box and value field settings and show values as. And the other way is once you’re in the Pivot Table. So anywhere in here, you can just right-click and choose show values as, and you can choose one of the calculations here. Now let’s choose percentage of grand total. And you can see that changes for all the cells. Now, the other way is to go on to the options tab in the ribbon, and the calculations you have the show value as, so you can change it from there. And finally, you can go out into the field settings and you can make your change from in here. So you got a few different ways where you can show values as option in the Pivot Tables. (upbeat music) In chapter 8, we created a P&L where we used calculated items to see the difference between the revenue and the COGS, which gave us the gross profit. And then also the difference between the gross profit and the expenses that gave us the calculated items called operating profit. Now, what we want to do is use the P&L types to determine what percentage of revenue they have. Now under row labels dropdown box, we have the P&L type chosen there, and we have our different P&L types. And we want to see what percentage of revenue is associated with COGS, gross profit, expenses and operating profit. Now let’s cancel to get out of that. To do this, we click in our Pivot Table. And then from the sum of actual dollars, we choose the value field settings. And then under show value as, from the dropdown arrow here, we choose the percentage of option there. Now for the base field, we’ll need the P&L type, and the base item will be revenue because we’re gonna show you the values as a percentage of the revenue for each P&L type. Now let’s press okay. Now the items within the P&L type will not get a percentage allocation, and that’s fine. We can see that in each of the totals, we have our percentages in there. Now to get rid of this, all we gotta do is just click on the minus button and we’ll get rid of that, and we can do the same thing for the revenue. So now we have a quick snapshot that shows that for example, in 2012, COGS is 2.5% of revenue. Gross profit is 97.4% of revenue. And if we add gross profit and COGS that will give us 100%, as you can see in our total there, which is correct. And then expenses accounts for nearly 36% of the revenue and the operating profit is that 61.58% in 2012. Now you can see the same calculations are done for 2013 and 2014. So this is a quick way to show your margins for your P&L. (upbeat music) In our data set, we’ve added another column called status. And in here we have the actual and the plan status stages. So for each transaction, we have an actual, and also a plan. Now we have the order dates here, and these can be also transaction dates, or they can be sale dates. But what we’re interested in is the actual and plan. So what we’re gonna do now is create a Pivot Table where we show the actual versus the plan for our products. And then we’re gonna create a variance report to see whether we have met our plan or not. Now to do this, let’s go to our pivot here. And in the Pivot Table here, we’re gonna add in the following items. On the row labels, we’re gonna add in the financial year and the products. In the column label, we’re gonna put in the status. So as you can see, we have the actual and plan status. And in the values area, we’re gonna put in there our sales. So grab that and drop it in there. Now let’s go in here and just change the number format, we’re going to value field settings and then choosing a number format, and we’ll do a number with 1000 Separator and no decimal points, and then press okay twice. And in here we can just center it like this. So we have the actual and plan for our products for 2012, 2013 and 2014. And now we’re gonna add in another column here to get the variance between the actual and plan. And also we’re gonna add another column that’s gonna show you the percentage variance. So to do this, let’s click back into our Pivot Table and grab the sales and drop it again to the values area. From the dropdown box, we choose the value field settings. And under show values as, we choose the difference from. Now, the base field is gonna be the status because we wanna see the difference between actual and plan. And the base item is gonna be the plan. So it’s gonna be the difference from the plan. Now let’s press okay. And as you can see, we have the difference here. And let’s make a few cosmetic changes. Let’s go back in here in our value field settings. We can change the name. Instead of instead of sum of sales 2, we can change it to dollar variance. And then number format, we can go into number separator, no decimals and we choose the red font for the negatives and press okay, and then okay. And next thing is let’s drop in our sales so we can get the percentage difference from the actual versus the plan. Drop it in there, dropdown box value field settings, show values as, dropdown box percentage difference from. The base field again will be status and the difference from with the plan. So we get the percentage difference from the plan. Let’s change the name in here and call it percentage variance. And the number format we can go to custom. And then let’s choose in here one of these. Now to make it a percentage, just go next to the semi colon and press the percentage. And then for the red, it’ll be at the end a percentage. So if it’s red, it’ll be negative percentage, and if it’s positive, it’ll show in a black color. Press okay, and then okay. Now finally, we have the plan here. Now the difference between the plan and the plan is zero. So that’s why we get no value there, but we can get rid of that. We just click in there, right-click and hide. The same thing for column G right-click and hide. Now, finally, we can go back into our Pivot Table and then right-click and show the field list. Now we can also drop in some more fields in here. Let’s drop in our sales region into the row labels. And as they’re been included in there, we can see that our calculation has also picked up the sales region. So you can add in as many fields as you want. The calculations are gonna extend to those fields as well. So there you have a quick report where you can see the difference between the actual versus the plan on a dollar basis and also on a percentage basis. (upbeat music) In our example here, we have our order date in our row labels. And then as you can see in our Pivot Table, if we scroll down all the way, we have lots of order dates ranging from 2012, 2013 and 2014. So it goes all the way up to row 259. Now say we want to group these dates, we can do that. What we gotta you do is just click anywhere in the Pivot Table. Right-click and choose group. And we’ll get the grouping dialog box. Now in the first part, in the top part, we have the starting at date, which is automatically added in, which is our first date. The 3rd of the 1st, 2012. And ending date is the 1st of the 1st, 2015. In here by we can group by seconds, minutes, hours, days, months, quarters, and years. What we’re gonna choose is days. Now let’s click on month so we can uncheck that. So we have checked on days and now we get the number of days here. We get the scroll box and we can choose the number of days to group by, and let’s group it by seven days or a week, and then we’ll press okay. So we can see here that our information is grouped by seven days, starting from the 3rd of the 1st and going all the way down to the 1st of the 1st, 2015. We can drop in our sales and then what it will do is group those sales that fall between each of the ranges. So for example, the 3rd of January, 2012 to the 9th of January, 2012, it will sum up the sales that fall between those ranges. And we’ll do the same thing for all the grouped dates. So let’s grab our sales and drop it into our values area. You can see there, we have our sales. And a scroll all the way down. And you can see that as well. Okay. Now we can also drop in the sales again. Instead of using sum of sales, by choosing the dropdown box, we’ll go to value field settings, and we can count. So we can see the number of transactions that happen between those group dates, and press okay. So we have a different transaction as well. So now you can go in and do some meaningful analysis with your data. (upbeat music) We have our order date in our row labels and now we want to group by months. To do that, we click anywhere in our Pivot Table. Right-click and choose the group option. And we’ll get our grouping dialog box. Now we need to choose months, which is already selected. We know that because it’s in blue. If we click again, that means it’s deselected. So let’s click on that again to activate it and press okay. So we have the 12 different months where our orders have been grouped into, and we can analyze the sales that relate to those different months. Now we grab our sales and drop it into our values area. Now we can see the different sales that pertain to each month. And just make a note that our data ranges from 2012 to 2014. So that’s three years of data that’s grouped into each month. So if you send this report to your boss, then you’re gonna make a note that this information includes three years of data. So it’s not just one year. And to avoid confusion, you can just right-click again, in the row labels, you choose group. Now we can also select the year. So you just click on the years. Now it’s in blue. So now months, and the years are selected and press okay. So we can see here, that’s broken down into each year. So when you send this report to your boss, then you won’t have any issues. (upbeat music) Now, say that I want to group our order dates by quarters and years, well, we can easily do that. In our row labels, we have our order date. So let’s go on into our Pivot Table. And right-click and choose group. We get our grouping dialog box. Now in the starting and ending dates, we can leave that as selected automatically. In by, we’re gonna choose quarters and years. So quarters, years. And unselect months. So let’s press okay. And we can see that the quarters and years are depicted in our Pivot Table. Now on the right-hand side, make a note that the years has been added in our Pivot Table field list in here. So what that means is that a new field has been created in the pivot cache called years. Now this has not been added into the original data set. So if we go in here, we’re not gonna see a field list called years. Now, all we can do is grab the sales and drop it into our values area to analyze the different sales that occurred in the order dates that have been grouped by quarters and years. Now, the years field that has been newly created. We can actually move that if you want, from row labels to the column labels, just by dragging and dropping. And you can see, we can analyze the information in a different view. (upbeat music) We actually group by sales ranges, and then get our sum of sales that belong in our ranges that we depict. And also we can get the number of transactions that belong to the ranges that we choose. So to do this, we’ll grab our sales and we’ll drop it into our row labels. So we have all of our sales that have occurred starting from $10,014, all the way to our maximum sales, which was 99,878. So it can go up again. Now in our Pivot Table, we right-click and choose group, and we’ll get to the grouping dialog box. The starting being the minimum value that we see there, and the ending being the maximum value that we saw before. The by means the amount that we’ll want to group our sales by. Now, we have 10,000 in there. So let’s leave it as that and press okay. As you can see, our sales are grouped by $10,000 increments all the way down there. And now we can do some further analysis. So let’s grab our sales and drop it into our values area. And from in here, we can choose the sum of and press okay. So what it says here is that between the sales ranges of 10,014 and 20,013, we had total sales of $1,011,401. Now we can check that we can just double-click in there and we can see our sales ranges in there are between what we’ve chosen before, from 10,000 all the way to the 20,000 amount. Now press Control + Z, and go back. Further, we can see the number of transactions that occurred between each of the sales groups. We can grab the sales again and drop it into our values area and we get the count of sales. So we had 67 transactions between our sales ranges, 10,014 to 20,013. And then 57 transactions between our sales ranges, 20,014 and 30,013 and so on. So we have our total number of transactions being 576 and our total sales being $32,064,332. Now, if you want to round these groups, then you can just right-click again, go to grouping. Now, instead of starting at 10,014, we can start at 10,000 and we can end at, we can say 100,000 and the increments we can leave at 10,000 and press okay. So we have our groupings, which look a little bit better. And then our sales and our number of transactions. (upbeat music) We can actually group our data by text fields. In our row labels we have our sales region. So say that we want to create some new regions. Now we want West, including Americas, East, including Asia and Central, including Africa and Europe. So let’s start off with the central. Let’s click on Africa and then hold the Control button in our keyboard and choose Europe. So we have Africa and Europe and want to name that into our new group or into our new region called central. Right-click and choose group. So Africa and Europe are included into group one. Now we can actually change the name of group one. We can call that Central. Americas, we can call that West. And Asia, we can rename that to East. So we have renamed our regions. Now on the right-hand side you’ll notice that we have a new field list that’s been created called sales regions 2. This is created in our pivot cache and not in our original data set. Now let’s rename this by clicking on the dropdown arrow, go to field settings and so sales region two, we can call it new regions. And press okay. So let’s change there. Now, all we can do, we can also drag this newly created group from the row labels to the column labels, just like this. And on the top here, we can see that our newly created region called central includes Africa and Europe, which is correct. Our West region includes Americas and our East region includes Asia. (upbeat music) So we’ve added a new column in our data source called time of sale, where it shows us the time that each sale was made throughout the day. And the format is in a 24-hour time format. And what we want to do is find out at which time of the day we have the most sales and which time of the day we have the least sales. So let’s go on to our Pivot Table. And what we need to do is grab the time of sale field and drop it into our row labels. So you can see, we have our different times that the sales were made. And now what we need to do is right-click in our Pivot Table, choose group, and we get the grouping dialog box with the starting time and the ending time being the minimum and the maximum time in our data source. And what we need to do is choose hours, we select months and press okay. So now we have different hours grouped, and finally we’ll need to grab our sales and drop it into our values area. So we can see now that the sales that we’ve made throughout the different times of the day. So during 1:00 a.m. we had 1.1 million of sales. During the 9:00 a.m. we had 4.1 million of sales and so on. So you can see here that at 11:00 p.m. that’s where we have our most of sales. (upbeat music) Now with grouping, there are a couple of things to note. If you have numerical data fields, then all you need to do is just click on one of the cells and then right-click and press group. And you can group like that. Another way is to go to the options tab and you have under group, your group and ungroup options. So you can group from there. And the third way is to go to the group field. And what this says is you can only group numerical data fields, and you can also group from there. Now, if we put in there text for example, sales month, and we try to click and right-click in one cell and try to group, we’ll get an error message. It cannot group that selection, press okay. You need at least two items selected to activate the grouping in the text field. So now we can group and we can start grouping from there. Now to ungroup we go to select the group heading, right-click, and then ungroup. Or we could do the same thing from the options tab and the ungroup selection there. So let’s group again, right-click group. And by pressing Control + Z on your keyboard, you can ungroup. (upbeat music) So we want to analyze our sales on a bi-annual basis. So we want to see the first half of the year, and also the second half of the year. Now we can group this. We can click in our Pivot Table and select January to June, right-click and group. So we have group one and we can call that first half. And then to group the second half, we just click on our items there July to December, right-click and group again, and we have the name group two. We can change that to call it second half. So now we’ve created our two groups. And on the right here, we have our new field called sales month two, and that’s in the pivot cache. So we can get rid of the sales month in there. So we’ve got the first half and second half. Now let’s put it in our sales, in our values area to see our results. And also what we can do now is put in our financial year and drop it into our row labels. And we can see our results from 2012 to 2014 on a bi-annual basis. And you can also do this if you had customer names. For example, if you had over 100 customers and you wanted to group them into groups of customer names, starting from A to K and also from L to Z. So you can have two groups of customers and you can analyze their sales over the years. (upbeat music) When you’re grouping dates, it automatically takes the first date in your source data and groups starting from that date. Now that date could be a Tuesday, it could be a Sunday, could be anything. But say you want to actually start on a Monday. Now we can change that when we go into our grouping selection. So first of all, we need to find out what our first date is. So we have the 3rd of the 1st which is our first date. Now by doing the formula weekday, weekday, it returns a number from one to seven, which identifies the day of the week of a date. Now, number one is Sunday. So let’s choose the 3rd or the 1st. So if one’s a Sunday, two is a Monday, three is a Tuesday. So we can find out that three is a Tuesday. Another way to find out what day fell on the 3rd of January, we can actually go into our calendar and click in 2012. And in there we can choose the 3rd of January, 2012, which was a Tuesday. So we wanna group on a date starting on Monday. So let’s do this, which is the second. Right-click anywhere in your Pivot Table and choose group. Now in the grouping dialog box, we have this automatically starting at the first date, but we’re gonna change this, we’re gonna override it. I want to pull up the second. Okay. So we want the grouping to start on a Monday. And we want to group it by days, and then we can put in there seven. So a whole week. And press, okay. So that’s a good tip to know if you want to group dates starting on a Monday. (upbeat music) If you want to isolate dates and do further analysis for your reporting or ordering purposes, then you can certainly group those dates depending on which ranges you’re looking for. So let’s do an example, click in that Pivot Table, right-click and group. So we have our data from 2012 all the way to the end of 2014, and say we want to just look at the first six months of 2013. So we’re gonna have the starting day being the 1st of the 1st, 2013 and the end date being the 30th of June, 2013. And then we want to group by months and then press okay. So you can see now that anything before the 1st of the 1st, 2013 is grouped into one amount here, the 10.3 million, and anything after the 30th of June, 2013 is grouped into another amount here, which shows 16.6 million. And then you have the six months isolated in there. You can do your analysis by double-clicking and seeing your transactions from there, and then press Control + Z and delete to go back. Or you can, if you want, click on any transaction after 30th of June, 2013, double-click on that, and that will give you all the transactions that occurred after that date. Control + Z to go back. So you have a lot of flexibility when you’re grouping dates in a Pivot Table. (upbeat music) In Excel, you can group by a calendar year and also a calendar quarter. Say you want to group by a fiscal year or a fiscal quarter. Now that’s a little bit difficult and you need to create some formulas and put that in your data source. And from there, you can create your grouping in your Pivot Table. Now a fiscal year, for example, in Australia, starts in July and ends in June. In other countries, it starts in October and it ends in September. And you can also have situations where the fiscal year start in April and ends in March. So I have an example here of some dates from July all the way to June. So this is a typical fiscal year that starts July ends in June. So what we need to do is do a formula where it gives us the year, and then it adds onto that a one if the month is equal to, or more than seven. And if it’s less than seven, then it will return a zero amount for the month. So this is one example to show this. In here, we can do an equal or a plus sign, and let’s put in year and let’s get our example date there and put in brackets. So that’ll give us the amount 2012. And then let’s add in here, in brackets, month and choose the same date and what we’re saying here, if it’s bigger than or equal to seven, close brackets, then it’ll give us a amount of one. So 2012 plus one is 2013. So any dates from July to December will give us a 2013 value, which means that the fiscal year 2013. If we drag all the way down, it’ll be 2013 all the way to December. So our fiscal year is 2013. Now, once we drag into January, well, our fiscal year is at 2013 because it’s counting 2013 and then it’s adding a zero because it doesn’t meet the criteria of equal to, or bigger than seven. And let’s drag all the way down here. So we have our fiscal year of 2013, which is correct for a July to June calendar. And now we can do the same thing for the fiscal quarter. So in here, we’re gonna use the choose and month functions. So what we’re gonna say here is it’s gonna return us a value for the month. So for 1st of July, 2012, it will return us a value of seventh. So what it means here to choose from these amounts here, that we’ve depicted, it’ll choose the seventh value. So one, two, three, four, five, six, seven. So the seventh value is a one. So that means quarter one. So that’s how this formula works. So let’s put it in here. So choose the month number from our date here, close brackets, and then return the value from our predetermined values that we’ve entered here for a July to June fiscal year. So this number three means that January is three, February three, March three, April is four, May is four, June is four, July is one, August is one, September is one, October is two, November is two, December is two. So the seventh value in here is a one. So it’ll return us a one. And then we can just drag all the way down and we can see we have our fiscal quarters in here. So now we can grab this formula here. Control + Copy, and then go into our data table where we’ve put in another column called the fiscal year, and we can paste it in here and then we can move the cell references to the order date and then press enter. And it automatically fills all the way down, and it gives us our fiscal years. Okay, let’s go back and grab our formula in here instead of writing it again. And let’s go to our data table, our fiscal quarter. Control + V and then let’s reference it to the order and again, enter. So it returns our values. So let’s update our Pivot Table and then do the grouping based on the fiscal years and quarters. So first we need to refresh the Pivot Table. So I can right-click in there and press refresh, which will give us our fiscal years and fiscal quarters. Let’s grab them and put them in a row labels and let’s put them in our row labels again, our fiscal quarters. And our sales we can drop into the values area. So now you can see, we have our fiscal years and our fiscal quarter. So a new year was created 2015 and the Q1 and Q2 quarters there. So this is a great tool to use if you’re not using a calendar year for your accounting or company purposes. Now, what I’ve done also is I’ve created a fiscal index where I’ve got the July to June fiscal years and October to September fiscal years, with the different formulas in there for you to copy and paste into your workbooks. And also for April, I’ve done the same thing. I’ve changed the formulas. So you had the different formulas to use, depending on what fiscal year your company is using. (upbeat music) Let’s try and group our order dates by right-clicking and pressing group. Well, we get an error message, cannot group that selection. Now, when you get that it means that your data source has some error values in your dates. So you may have some N/A values in there when you imported the data, or you may have some dates that are not entered in correctly. For example, you may have month 13, or you may have a date number 31 in February. Now we can check that. We can go into our data table and into our order there, we can select everything and press Control + G, which is the go-to special. Or you can go under find and select and go to special from there. Now let’s select constant, and we want to find out any errors or any text. So if we have any dates with 31st of February, then that reads it as a text. Let’s only select texts and errors and press okay. So it’s made the selection, we cannot see it, but it’s in there. Well, now we’re scrolling down, we can see that. Now let’s highlight that in yellow. And it’s also highlighted our text up there. That’s fine. Now let’s filter by color. So it gives us all our texts or our error values. So in here we can make our changes highlight all these. Again, we can go to Control + G, Go To Special and visible cells only. And if they all have the same order dates, we can just put in 28th of the 2nd, 2012, hold down the Control key and press enter and that will fill in the selection. And then for the N/A, if that’s an error, then you can delete everything or you can go back and find out what the date is. And now let’s for our purpose, we can just put in 14th of the 2nd, 2012. Now we can go back to our Pivot Table. What we need to do first is unselect the order date. And then what we need to do is refresh our Pivot Table So right-click, refresh, so that updates the pivot cache with the new information. And then we need to put back in the order date into our row labels and from in there, right-click and group. So now we can do our grouping. (upbeat music) Okay, I want you to group our order dates into weeks, and then I want to do another Pivot Table and then group to months and quarters. So let’s group these into weeks of seven and press okay. So we have that. So what I wanna do now is go to options and select entire Pivot Table, Control + Copy, and in here, Control + V to paste it. And now what I wanna do is group these into months and quarters and press okay. Well, see what happens. The first Pivot Table gets updated as well. That’s because we’re using one pivot cache. Now that’s annoying, but there is a work around. Let’s press Control + Z to go back. What I need to do is grab this and then cut it and paste it into another workbook. Let’s go to file, new, blank workbook and then in here, right-click and paste. So in here, I can group it into the way that I want, into months and quarters, and then I can select everything, Control + X. I can go down into my book where I was previously and in here, right-click and paste. So now we have two separate pivot caches, and we can group each individual Pivot Table independently. So if I go in here and say group again by months, quarters and years, well, that happens. And then this doesn’t change. Now there’s another way we can do this. We can go to our data table. And what we need to do is bring up the old pivot wizard by pressing Alt + D + P. And then what we need to do is press next. And then that chooses our whole table. And then that’s fine, press next. And then we want to put this Pivot Table into our new worksheet and press finish. So in here, let’s put our order date and then let’s put our sales and then we can group this by days and put seven and press okay. Now let’s go back to our data source and then press ALT + D + P again to create another pivot cache, and then press next. It selects that, press next. Okay, now we get a message here says your new report will use less memory if you’re base on your existing report, which was created from the same source data. Do you want your new report to be based on the same data as our existing report? Well, no, we don’t want that, we want a new pivot cache. So we press no here. If you click, no, the two reports will be separate. That’s what we want. Press no and go into our existing worksheet, sheet one, and we can place it there and press finish. So in here we can do the order date and sales, and then we can group, right-click in there and group by months, quarters and years. So there you have it. Two ways where you can group Pivot Tables coming from the same data source independently. (upbeat music) We’ve grouped our sales here by increments of 10,000. And we have our sum of sales here that show the results per group. And so we take this out and then we’ll wanna drop in the sales again. What happens, we get a count of sales. That’s because once you group sales, then it reads that as text. So it automatically shows us a count of sales. To fix this, all we gotta do is right-click and ungroup the sales. And then if we drop in our sales, once again, then we get sum of sales. (upbeat music) We’ve got our order dates here, and we want to group these. So right-click anywhere in there and press group, and then we choose days of seven and press okay. So this is a grouped by seven days, but as you can see here, there’s data missing. So from the 16th of the 1st, it goes to the 24th of the 1st. Now we wanna show all the group dates. Even if they don’t have any transactions in there. So let’s right-click in there once again and go to field settings, and under layout and print, let’s choose the show items with no data and press okay. So it shows all the weeks here, even if they don’t have any information in there. Now, finally, we can go to the options tab, and option and for empty cells show zero, and press okay. (upbeat music) We have our P&L report that we created in chapter eight using calculated items. What we do there is get the difference between the revenue and COGS to give us the calculated item called the gross profit, and then get the difference between the gross profit and the expenses to give us the calculated item called operating profit. And here we have the P&Ls for 2012, 2013 and 2014 with our sales here. And now what we’re gonna do here is drop in our months into our column labels and then group those to get the quarterly reports. And from there, get the difference between the previous quarter. And let’s get our month and drop it into our column labels. And let’s escape from there. So we have our months on there. Now to group these into quarters, just go to highlight the months that you want to put into quarters and then right-click and group. And where it says here, group one, we can actually change that and call that quarter one. The same thing for April, May and June. Right-click, group, and call it quarter two, and depending on which part of the world you are, each quarter will be different. Now in Australia, the Q1 starts in July, but in America, it starts in January. Now, let’s continue here, right-click, group and call it quarter three. And then finally let’s put in there quarter four. Okay, so we’ve done that. Now, let’s right-click and show the field list. As you can see here, though, we have the month two field that’s been added here, which shows our grouped months. Now let’s click in the dropdown arrow and choose field setting, and let’s change the name here. Instead of month two, let’s call it quarter and press okay. So you see that’s changed there, and also in our Pivot Table field list. Okay, now we want to drop in our actual sales into the values area and do a calculation to get the difference from the previous quarter. Now, if we grab the sales and drop into the values area, we’ll get this warning here. It says multiple data fields of the same field are not supported when a Pivot Table report has calculated items. So because we have calculated items here for gross profit and operating profit, we cannot drag it in there, but there’s a workaround for that. Let’s get out of these. Now, what we can do is click in here, go to the options and select entire Pivot Table, press Control + Copy in your keyboard. And down here, let’s paste it by pressing Control + V. Okay, so what we can do now is just group these into the quarter, just by clicking into the minus box there. Or a quick way is to go to the options once we have selected that area, and go to the minimize entire field. Now let’s highlight this and double-click between the columns just to center them, and then we can press the center twice there. Okay. So we have our quarters. Now, what we can do is right-click to show our field list again. And now from in here, from the dropdown box, we’ll go to value field settings and show values as, we choose the difference from. Now, the base field will be the newly created quarter field, and the base item will be previous. So we’re showing the difference from the previous quarter. And finally, in the custom name, let’s call it variance per quarter, and then the number format we can just keep it as currency and the negative font there and press okay. And now, okay. And we can see here that we have the variance. Obviously Q1 will be zero because there’s no previous quarter to compare it to. And we have the Q2 difference from Q1, the Q3 difference from Q2 and the Q4 difference from Q3. Now we can just go up here and we can see and compare this to the top chart there. Okay. Let’s click in there, options and we can just minimize that. Okay, so we have the actual values there, and we also have the differences at the bottom. So that’s a quick work around when you have calculated items within your Pivot Table. Now I’ll show you another example where we’re gonna include the variances between the quarters. So to do that, we’re gonna use a Pivot Table that doesn’t have a calculated item in there. So let’s go to our new workbook here. Okay, so in here we don’t have the calculated item for the gross profit and operating profit. So to drop in the variance, just get the actual dollars again and then dropdown box, we can go again and choose the difference from. The base field will be the quarter and base item will be previous. So the difference from the previous quarter, and then in here, we’re gonna pull variance per quarter and then number format, we can just put in the currency and we’ll use the dollar and the negative red font, and press okay, and then, okay. Let’s close down the field list and we can see in here, let us make this a little bit better to see. Okay, so the first variable we don’t have. So we can get rid of that. Click on the column C, right-click and hide. And here you can see the variance per each quarter, the Q2 versus the Q1 variance, the Q3 versus Q2 variance, and the Q4 versus the Q3 variance. So with a grouping and show values as calculation, you can do some pretty good analytical Pivot Tables for your clients. (upbeat music) We have our data set here with the bank balance date and the actual bank balance for each date. Now we have each transactional date up until all the way, 2014, 31st of the 12th. So let’s go back up again here. And what I want to do is we want to show the minimum and maximum bank balances for each month in each particular year. Now let’s go to our Pivot Table here and click in our Pivot Table. Now to do this, we have to grab our bank balance date and put it into our row labels. And from in here, just choose any of the items in there and right-click and press group. And we’re gonna group it into the months and years. Now, the starting and ending point is automatically entered in there, and we’ll just leave it like that, and we’ll press okay. So we have our months and years for 2012, 2013 and 2014. As you can see here in the row labels, the years field has been created now that we’ve grouped our bank balance dates. And also it’s been created here in the field list. The next step is to drop the bank balance into the values and then get the minimum and the maximum amounts. So grab the bank balance, drop in to the values. From the dropdown arrow, choose the value field settings, and in the summarize of the values by, we choose the minimum. And in here, we can just leave out minimum or bank balance. That’s fine. And the number format we can go to number, and we can just put a separator and use the negative red font there, and press okay. Now, we’ll do the same thing for the maximum. So we go to the bank balance, drop into the values area, dropdown arrow, value field settings, and do the maximum this time round. And number format, again, you choose the same, and press okay, and then okay. So you can see that for January, 2012, the minimum bank balance for the whole month was at minus 8,306, and the maximum bank balance during the month of January reached to 9,662. Now let’s go to our data table just to confirm that. And from the dropdown arrow, we can choose in here only 2012, January and press okay. And from in here, we can see that the minimum amount was 8,306, and the maximum amount was 9,662. Go back in here, that matches. Now let’s get out of the Pivot Table field list. Another thing that we can do is put in a graph in there. So we can see how the movements have tracked over the months and the years. Now, click in the Pivot Table, go to options and choose pivot chart, and just put in a line chart in here and press okay. Now let’s expand this to make it a little bit bigger. Now from in here, right-click and let’s hide all field buttons on chart because we don’t want that ’cause it clogs up the screen. And in here we can change the color. Right-click, and then choose the red in here, and from in here, right-click and we can choose a dark blue color there. So we can see here that the minimum bank balance for each of the months throughout 2012 and 2014 is around 10,000. So it doesn’t go below the 10,000 mark and also the maximum bank balance for the years was trending about the 10,000 mark. So in this situation, your bank overdraft limit will be around the 10,000 mark. But as you can see, there’s not much margin that you can play with. So by grouping the transactional dates and also showing the values by a minimum and maximum, you can do some in-depth reporting and graphical representation of your data. And it’s not only limited to bank balances, this can also be a situation where you have sales, unit sold, or the amount of time you took to repair a product. (upbeat music) There are few ways where you can sort your Pivot Table. One of them is to go to your Pivot Table field list. And in here you just click and you get the dropdown arrow and you have your sort options there. The other way is to go to the options tab in the ribbon and under sort and filter, you have your sorting from there, A to Z or smallest to largest, Z to A, largest to smallest. And then you have your more sort options in there. And another way is within the Pivot Table, right-click, and you have your sorting there, and you can also go into your values and then you could sort from there as well. So let’s use the ribbon to sort. So we want to sort by largest to smallest. Now, when you create a Pivot Table, it automatically puts the row labels into alphabetical order. So say you want to put it from Z to A, we can click there and all the values change. And A to Z, it goes back to where it was. Now, if we want to change the values, you gotta click in the values area there, and then say, we want smallest to largest, we click A to Z. If we wanna see largest to smallest, we’re click Z to A, and their respective items change as well. Now, if we want to do the same thing for the sub-totals, we gotta click in the sub-totals area and we can show smallest to largest and then largest to smallest. (upbeat music) If want to sort an item row from left to right then we can certainly do this. For example, tonic, we have our values from 2012 to 2014, and we want to show the highest value first, and then on the right, going on to the lowest value. Now to do this, you’ve gotta click into the values area, right-click and sort. Choose more sort options, and we want to show the largest to smallest. And then in the sort direction it’s left, right. So in our summary, it says sought financial year by sum of sales in descending order using values in this row, tonic and press okay. And we’ll see that tonic has the highest value. And then on the right, it goes all the way to the lowest value and the years change there as well. And also the other items have been moved accordingly based on the 2013 totals. So you can certainly sort from left to right, as well as top to bottom. (upbeat music) There are a few ways where you can sort manually in a Pivot Table. One of them is to click in your row labels and on the border, you get your four pointy arrow and then click your mouse and you can move it up or down and you can see the bar there, so you can move it all the way up like that. So that’s one way. Another way is that you can actually write in the items that are in the row label. So say we wanna move tonic from the bottom to the top, well, we just write in TO and then it knows that we’re gonna type in tonic, and then press enter. So it moves tonic to the top and the same thing in here. Anywhere, we can put in there, you’re gonna say okay soft, SOF and then it automatically puts it in there. Now, if you make a mistake in there instead of putting ice and then press and delete and enter, it’ll override the item that you had there. So just to make sure you don’t make that mistake. Press Control + Z to go back, and finally we can right-click in the item, and then we have the move option there. So we’re gonna move bottles. The beginning up down, or to the end. And it just depends on which position it’s at. We can make those moves. So if we go to bottles, right-click. Obviously we can only move that down or to the end. So there’s a few different ways where you can manually move around your Pivot Table item list. (upbeat music) We have our data on the left here sorted alphabetically, but sometimes you want to create a custom list. You want to have, for example, Americas first and second, you may want to put in Europe, Asia then Africa. So you wanna set up a list where every time you refresh your Pivot Table, then Americas is first all the time. Now we can do this. First, let’s create our list, the way we want to see it every time we update our Pivot Table. So we want Americas, let’s copy and put it in here. And then let’s put in Europe and Asia and then Africa. Okay, so that’s the format where we’ll want to see our Pivot Table each time we sort it from A to Z. Now what we need to do to activate this is we need to go to file in our ribbon, go under options on the left hand side, in the Excel options dialog box on the left-hand side, we choose advanced, and then we scroll all the way down and under general, there’s an edit custom lists option there. Now we’ll click on that and now we can create our new list. Let’s go into this box here so we can choose our newly created custom list. Highlight, and then press import. So you can see there, it’s been imported. Now you can also see that the custom list that have been created by Excel for the dates and the months and we have our custom list here. All we need to do now is press okay. And then again, okay twice. To activate this, we’ll need to refresh our Pivot Table. So right-click anywhere in our Pivot Table, refresh, and you can see that Americas is first, Europe is second, Asia is third and Africa is last. Now, if this wasn’t in that order, you can right-click sort A to Z, and it’ll put into that order. If your custom list doesn’t work, when you refresh and then sort from A to Z, then you need to go to another place to activate it. Right-click, sort and more sort options. And then on the bottom left-hand corner, click again, more sort options. And if your custom list didn’t work, that means that this was unchecked. Okay. So make sure that the autosort is always checked. So next time you refresh, then your custom list will be as per the way that you created it. So you can create many lists for regions, for products, for salespeople, whatever you like. It’s a great way to get a custom list on your Pivot Tables, where you can analyze as per your company’s preferences. (upbeat music) We’ve added a new column here called managers where we’ll put in a manager’s name. For example, Jan, April, Adam and Scott. Now, Jan is a name as well as a month. It’s short for Janine, for example, April as well is a woman’s name and a nice one at it. So when we put this in our Pivot Table, it’ll sort by month names because it will think that the managers’ names are months because of Jan and April. Now let’s have a look at this. Let’s go to out Pivot Table. We can right-click and refresh. Now the managers, or we can drop it into a row labels. As you can see there, Jan is first, then April, then you get Adam and then you get Scott. So it’s not in the correct order. Now to override this, you gotta right-click in the Pivot Table, go on to Pivot Table options and under totals and filters, the last option under sorting says use custom lists when sorting. And then we’re gotta uncheck that. And then press okay. And as you can see, that has been updated. So we’ll have Adam first, April second, Jan third, and Scott last on our list. (upbeat music) Now we have our regions and months in our row labels and our sales in our values area. Now, what we want you to do is sort the sales from highest to lowest, and then sort the regions alphabetically. And to do this, we click in our sales, right-click and sort largest to smallest. And we have the largest to smallest values for Africa, for Asia, for Europe and for Americas. And now we want to put the regions into alphabetical order. We can right-click. So there’s two ways to do this. We can actually sort from A to Z, or we can go through the more sort options, and under the ascending, A to Z, we can choose the sales region and press okay. So we have Africa, Americas, Asia, and Europe in alphabetical order. And we also have these sales in descending order as well. (upbeat music) We have our products on our row labels here, and I want to add in a new product and then refresh it and see where it goes on our Pivot Table. So let’s go in to our data source and add a new product called cider. So we need to add this in our table. Let’s go to the end of the table by pressing Control + Down. And let’s click out of here. And from the corner we can just drag and add a row. Let’s highlight the row and press Control + D to copy down or whatever is directly above. Now, what we need to do is we’ll keep the same information. The only thing we’re gonna change is the product. So from tonic to cider and press enter. Let’s go to our Pivot Table, right-click and refresh. And as you can see, cider has been added to the end of the list. Now we need to update that. To do this, all we’re gotta do is just right-click anywhere in the Pivot Table, sort and sort A to Z, and then we have our product list sorted alphabetically. (upbeat music) Now we know that our Pivot Table is sorted by the arrow pointing down in our filter here. Now we can clear that by going to more sort options, and then selecting the manual option there. You will press, okay. Then the sort has been cleared. (upbeat music) We have our months going across the column in the Pivot Table. And we can actually sort by the grand total. If we click in there and right-click, choose sort and then sort largest to smallest. (upbeat music) In that Pivot Table on the left in the row labels, we have the order dates and we have our sum of sales in the values area. Now the order dates range from 2012, all the way down to 2014. So we have three years of data in there. Now we can filter that data. If we go to the row labels dropdown arrow, and then under date filters, we have all these filters here. Now the date filters option is only available when your row labels or column labels have dates in there. So let’s have a look at the different filters that we have. We have the equals, before, after and between. So let’s choose between. And we get this a dialog box and we can choose a date here by clicking the calendar and today being the 5th of March. So we can go back and say December 1st to today, and then press okay. So you can see everything has been filtered there for our selection. Now we can clear that or click in there and press the clear filter from order day. Now the next day filter, we’ve got some virtual filters here, for example, tomorrow, today, yesterday, next week, this week, last week, next month, this month, last month, next quarter, this quarter, last quarter, next year, this year and last year. And these are virtual filters. So what that means is when you put that filter and you open your Excel workbook next week, then those filters will get updated based on the date that you open your Excel workbook. So it’s a live filter. And let’s click on tomorrow and have a look if there’s anything in there. Well, there’s nothing in there in our selection, and that’s okay. That’s normal, it can happen. Now if I open this file in a month’s time, and then I choose tomorrow, then I may have an order date there. So let’s go back there and we can choose today, well, I have no order date values for today. And today is the 5th of March and we can go to date filters for yesterday. And again, I don’t have any order dates there as well. Now, if I come back there in a couple of week’s time and I’ll do the same filter, then I may have an order date in there. So don’t freak out if you don’t have any values in there. Okay, let’s have a look at next week. So next week I have to order dates there. And another thing that you can do here is instead of order dates, there can actually be due dates when the customer is going to pay you. So you can have this filter, and then every week you can just open this workbook and the Pivot Table will get refreshed and then it’ll have the next week’s dates. So that’s a great advantage of having these virtual filters. Another thing we need to point out is that the weeks in Excel start from Sunday to Saturday. So if we ever look here in our calendar. So next week, we’ll start on Sunday, the 9th of March and finish the 15th of March. So as we can see here, the 9th of March, that’s correct. So it includes the 09th of March into the next week’s order dates. Let’s go to another one. Let’s go have a look at this week. We just have one order date there. Let’s go to last week and we have a few order dates there. If you go to next month, this month, last month, next quarter, this quarter, and last quarter. Now, obviously this quarter ending in March while last quarter will start in October and in December. And let’s go to some more date filters. We can have a look at this year. So it has all our values there for 2014. And then also go back to last year and have a look, all the order dates for last year. So I have all these order dates down there. Now another option here he is year to date. So only show us the order dates that have started from the 1st of January, 2014, up until today’s date, which is the 5th of March, 2014. So you can see there, this is the year to date. And then another option we have here is all dates in this period. So what this means is it’ll get all the order dates, they were like Q1 for our data set. Our data set being 2012, 2013 and 2014. You can see that, all Q1 for 2012, for 2013 and 2014. Now the same thing for the other quarters can also go for the months. So the take or the February order dates for 2012, 2013 and 2014. Now we have the custom filter. So if we click on there from this drop box, we can choose the different filters equals, does not equal, is before, is before equal to, is after, is after equal to, is between, or is not between. So you can choose one of these in here and you can apply different filter that you like and press okay. And it will come up there. So you have an array of filters which you can use, and you do your analysis. And the great features about these is that we do a virtual day filter that the next time you open your workbook, then your data gets updated automatically based on that given date. And you can do some great reporting like due dates for payments, and also for project management, you can have your due date for your different milestones. So go ahead and spend some time on this, it’s a great feature. (upbeat music) In our Pivot Table, we have our sales months in our row labels and our sales in our values area. Now we filter by labels, which means that we can filter by any text. So as our sales months, our texts then we can filter by that. Now you can also drop in there products if you like, you can also put in there countries. And also if you had employee names, you can also apply labels to filter. So to filter by labels, we click in our row labels and we get the label filters there. And we have these 14 different filters. So let’s choose equals. Now, if you’re gonna choose this option, then you gotta make sure that the full name is entered in there. You can’t just put in there a letter or a couple of letters. So we’re gonna put in there, it equals January and press okay, and we’ll get that filter there. And you can clear by pressing this clear filter there. Let’s go to the next one, does not equal. We can put it does not equal July and get the rest of the items there. Now we can go to begins with. Now in here, you can put in a single letter so we can say it begins with A, and press okay. And we’ll get the months of April and August. Or we can say it does not begin with A, and we get the rest of the months there. We can say, ends with and put in their year and press okay. And it’ll give us the months that end in the year. So we’ve got September, October, November and December. Now, once again, we can go, it does not end with, and put the year and we get the other months. And finally we can say contains. Now in here, you can put in there letters as well. So let’s enter the letter E and press okay. And it’ll give us all the months that contain the letter E. And does not contain E, and then will give us the rest of the months. So there’s plenty of combinations there that you can do. And it’s not only limited to months, you can apply to products, countries, employee names, whatever text fields. (upbeat music) If you have a column field that has a numerical and alphabetical sequence, then you can filter that by labels. Now, in our example, we have item numbers with three numbers followed by three letters. Now that can actually be a product number or a serial number, or it can even be number plates. Now let’s go to our pivot and we have our item number here on our row labels and our sales in our values area. Now let’s press on our dropdown arrow and then choose label filters. And we can filter by greater than. And in here we can put in an amount, for example, 110AAA, and we’ll get all the values that are bigger than that. And you see there. You go all the way down. Okay. Now we can clear the filter by pressing clear filter from item numbers. Now we can activate the label filter once again, by going greater than or equal to. And in here we can put 110ZZZ and press okay. So it includes the 110ZZZ. You can say, less than 110AAA and press okay. And we have all those there. And when we say less than or equal to 110ZZZ and press okay. So it includes the 110ZZZ item in there. And finally we have the, between, and not between filters. So we’ll say between, let’s say 104 and 107 without putting any letters. So if it’s 104, it include 104A, AA, ABC all the way to the top. And then if we say 107, well, it’s only gonna include 107, it’s not gonna include 107A or anything above that. So let’s put in there 104 to 107 and you’ll see that. And there you have the results. And not between, well, let’s put in there once again, 104 and 107 and we get the rest of the results. So there were certainly a few filters there that you can use when you have fields that include numerical and alphabetical sequences. (upbeat music) In our Pivot Table, we have our order dates on the row labels going all the way down. And then we have our sum of sales in our values area. Now we can filter by values simply by going into the row labels dropdown arrow, and then choosing value filters. And in here you have nine different ways that you can filter your values by. We have equals, does not equal, greater than, greater than or equal to, less than, less than or equal to, between, not between and top 10. Now let’s choose the equals. In this filter, you will use it when you want to drill down and find only one value. Putting 24,640, you can press okay. So here we get two different order dates that have the sum of sales that equals to 24,640. Now let’s go on to another value filter. We can simply go in here and choose it does not equal to. Now you will wanna use this when you don’t want to include a certain sale amount. So you can put in here does not equal to 24,640 and press okay. So to give you all the other amounts that do not include 24,640. So again, let’s go to our next value filter. And we have the greater than. Now in here, you wanna focus on a certain sales level. For example, if you want to look at the sum of sales that are more than $500,000. So let’s put in there $500,000 and press okay. And what you’re gonna get now are all the sum of sales that are above the $500,000 mark. Now, if you want to drill down and see what makes up these sales, then you can just double-click in there and you get a whole list of the amounts that make up those sales. Now to go back and press Control + Z and delete, and you go back to your Pivot Table. Now you can also do the greater than or equal to if you want to make it equal to that amount, and also be greater than. Now, we can go on to our next filter which is less than, and click on that. And again, in here, you wanna focus on a certain sales level. So once again, let’s put in our example, of less than $500,000 and press okay. And we’ll get all these different sales values that are less than 500,000. Now go back to our values filter, and we can also put in that less than or equal to amount. The other filter that we have there is the between filter. Now in here, you want to drill down on a certain range of values. So you can say between 100,000 and 200,000 and press okay. And you have all these sum of sales that are between that range. Let’s go back and choose not between. And again, let’s put in 100,000 and 200,000. So it’s not gonna include any values from 100 to 200,000. So what it will include is anything less than 100,000 and anything more than 200,000, and press okay. And you have all these values there. So there are a few filters there that you can use where you can drill down and analyze your financial data in a quick and easy way. (upbeat music) In our data set, we’ve added a new column called the channel partners. And in here we have 125 different channel partners. Now, all we’ve done is we’ve gone to our Pivot Table and refreshed, and we’re putting the channel partners in our row labels and our sales in our values area. And what we wanna do now is get our top 10 channel partners so we can see, which are the best performing. Now, what we have to do is click on the dropdown in the row labels and choose the value filters. And the last option is top 10, click on that. And you get this dialog box that comes up that says, show top. Now you can also choose the bottom if you would like, but we’ll do the top 10 for now. And then in here, it gives us a default number which is 10, but you can go down or you can go up and you can also manually put in there the numbers, but we’ll choose top 10 for now. And then we’re gonna analyze by items now, and we’re gonna use the sum of sales. So that’s how we’re gonna choose and then press okay. And now we get the top 10 channel partners from our data set, and finally, we can also sort this from highest to lowest, just click anywhere in the sum of sales, right-click, sort largest to smallest, choose that. And we see that ABC Telecom is the best performing channel partner. And then you have the other nine best performing channel partners from 2012 to 2014. Now you can also do this analysis if you had lots of customers or if you had lots of salespeople or lots of products. So it’s not only limited to channel partners. There’s many different ways where you can use the top or bottom items filter. (upbeat music) The top or bottom percent filter gives us a list based on a percentage of items that make up the sum of sales. Now, in our Pivot Table, we have our channel partners here, which is a new column that we’ve added in. And we have our sum of sales. Now, what we need to do is go to the row labels dropdown arrow and choose our value filters. And then the last option, top 10, we choose the top 10%. Okay. And then instead of 10, we’re gonna choose the 25%. We can scroll up or down, or we can write in there manually. Let’s press okay. And we get our list here all the way down there. And we get our grand total as well. Now we can sort these from highest to lowest, click anywhere in the values, right-click and then sort largest to smallest, and we have that there. So now we have our list of channel partners that make up at least the top 25% of sales. We can go and see the bottom 25% list by going on to the value filters, top 10, and show bottom. And then press okay. And we have our lists there. And we can sort from smallest to highest. Sort from smallest to highest. And with this analysis, you can drill down to your best and the worst performing channel partners, customers, salespeople, or products, and take the appropriate action needed. (upbeat music) The top or bottom sum filter will give us the channel partners that make up a certain amount of sales. For example, we’re gonna get the top channel partners that account for $2 million of sales. Now to do this, we click in our row labels filter and choose the value filters and top 10. And in here instead of 10, we put in 2 million and then from the drop-down box, we choose sum. and press okay. So now we have the top channel partners that account for 2 million of sales. And we can also sort these from highest to lowest. Right-click, choose sort, and sort largest to smallest. Conversely, we can choose the bottom channel partners that account for 2 million of sales. Let’s go in the filter and choose top 10 again. And from show, we use bottom, and press okay. And here we have our list of the bottom performing channel partners that account for 2 million of sales. And we can sort these from smallest to highest. Right-click in the values, sort smallest to largest. This analysis can also be done on customers, on products, on item numbers, on any given metrics that your company is looking for. (upbeat music) A report filter is used if you want to show a high level summary with multiple combinations of fields. In our Pivot Table, we have put in the salesperson, customer products, sales region, and sales month in our report filter. And you can see in our Pivot Table, it’s shown up here on the top left-hand corner. Now we can choose the dropdown and select one item and press okay. You can see here, Homer Simpson is selected, or we can go to another one, to products and select another item, soft drinks. And we can go to sales month and select January. Now our results are shown in here with our grand total. So it’s a good way where you can drill down and analyze certain specific items within your data. Now to go back, you just click in there and choose all, or you can press Control + Z if you like, and it’ll go back to where it was before. Now, we can also select multiple items and click down on our filter there and choose from the bottom left hand corner, select multiple items. So that activates it. And now we can select and deselect the all button, okay. When it’s not selected or we can choose individual items like this and press okay. Let’s go to products and again, select multiple items and you can also deselect and keep the active items selected that way. Now press okay. And in sales month, we can also choose a couple of months. Say Jan, Feb and March, and then press okay. And we have our results down here. Now let’s press Control + Z to go back. Okay. Another thing that we can do is the use the search box up here, but first of all, to activate the search box for all the items here, we gotta select multiple items. So say, we wanna put in O. So any items that have the letter O will be selected. And let’s add this in there. Okay. Next one, to the products, select multiple fields, and then we can choose in there. IC, you see IC as ice cubes in tonic the letters IC. And let’s choose that. And then sales month, again, activate the multiple items, or we can choose ER, and it gives us the month that end in ER, and then press okay. Now to add more items in our selection, what we can do is go into a report filter and start typing here, J, and you get the option here to add current selection to the filter that’s already there before with the ER. So what we can do is if we choose this box, then January, June, and July will be added to the month that ends with ER, and press okay. And then let’s check that. And we can see Jan, June, July has been added with September, October, November, December. And this is a very powerful feature to have. (upbeat music) Excel is smart enough, and if 90% of your fields are texts, then you’ll get a label filter. If 90% of your fields are dates, then you get a date filter. And if 90% of your fields are values, then you get a value filter. Now, a quick way to activate the filter is to go to your Pivot Table field list. And then you get these hover box. And from the dropdown arrow, you can choose your label filters, value filters, and search box filters. And then you can click on your channel partners, and also from in here, you can choose your filters. Another way is to go into your Pivot Table, right-click anywhere in there, and then go to filter. And then you’ve got your three filters there. You got your top 10 filter, you’ve got your label filters and value filters. Now, if you click in your label filters, you’ll get the 14 different options there. And then if you click on the value filters, then you’ll get your eight different options there. And the third way is to choose your row labels. And from in there, you can choose your label filters and value filters. Now, if your row labels don’t have the drop-down error, then you can go to options and the field headers would be off so you just need to select that. So there are a few ways of you can activate your filters. (upbeat music) We can quickly select items by going on to the Pivot Table and then with a mouse highlighting your selection, right-clicking and in the filter option, choose, keep only selected items. So January to June has been selected and we can see this by going into the row labels filter that January to June are selected there. Now we can press Control + Z to go back. And now we can also hide our selection by going onto the filter and choosing hide selected items. So now only July to December are shown as you can see there as well. So it’s a quick way where you can select and keep or hide your items. (upbeat music) A text wildcard allows us to filter by many different combinations. An asterisk will return any series of characters before or after the asterisk. A question mark or return text that contains only one variable. Let’s go to our Pivot Table filter in our row label and choose a label filters, choose begin to with. So in here, what we’re gonna do is put begins with GLO and asterisk. So anything that comes after the letters, GLO, will be included in our filter. So let’s press okay. And you can see we get Globex Corporation, we get Globo Gym American Corporation and we’ll get Globo-Chem. And you can see here in blue, we have the GLO and the asterisk includes all these letters after GLO. Let’s go back and clear this filter. And we can go in and use another label filter that contains, so anything before the word tech will be included because we’ve put an asterisk before the word tech. Press okay. And we’ll get Initech and Primatech. And you can see here from our example. Now let’s go to another label filter. And we can put equals, and now we’re gonna put asterisks Inc and asterisk. So that means that it includes the word Inc. Asterisks Inc asterisks, and press okay. And we get here our results. And you can see there, everything in blue has been included. So any items that have the word Inc are shown in here. Now, let’s go on to another filter and put in contains. And now we’re gonna use the question mark filter. So in here, we’re gonna say, A?C. So the question mark means any one variable. So it could be ABC, it could be ARC, or it could be A, a space and C. So the question mark means any variable, and press okay. And we’ll get out results here. In blue here we get ABC Telecom. We get Monarch Playing Card Company because it has the ARC, R being the variable, and Sombra Corporation, the space between A and C is the question mark, and Spade and Archer, well, the R is there question mark. So you get different combinations based on the question mark. Now, also you can do this in the search box. So in the search box, for example, let’s type in INC. And in here we have the results that include the word INC, and put an asterisk. Then anything that begins with INC will be included. So you can also do this in the search box. (upbeat music) We can also filter by a multiple fields. In our row labels, we have the sales region and products. So if we go to our Pivot Table from the filter dropdown, we have the select field option there, and we can choose sales region or products. Now let’s choose sales region. And then in the value filters, we’re gonna put in there greater than 8.1 million. So cool, okay. And then press okay. So we only have Asia and Africa because the sub-totals are greater than 8.1 million. Now we can do another filter for our products and say values that are greater than 2,100,000. And we get the items that are bigger than 2.1 million. So you can do two filters when you have multiple fields in your row labels. (upbeat music) Now we’re gonna apply multiple filters in our Pivot Table. Let’s choose the filter button here. And for sales month, we’re going to use a label filter, anything that contains ER, and press okay. So we’ll get all the months that end in ER. Now, what we’re gonna do is apply a values filter for any values that are bigger than 800,000. We choose the sales month and let’s choose value filters greater than 800,000. Okay, so we get anything that’s greater than 800,000, but we also want the sales month filter to include ER, and if we hover over our row labels, we see that our filter is only for sum of sales, which are greater than 800,000. And you have a multiple filter, we need to go into our options. So right-click anywhere in the Pivot Table and choose Pivot Table options. And under the totals and filters tab and the filters, we have the allow multiple filters per field. Now we need to check that and press okay. Now let’s go back to our filter, sales months, label filter, contains ER, and press okay. So now we get all the months that contain ER and are greater than 800,000. And if we hover over there, we can see that we have the multiple filters, sales months contains ER, and value filters, sales months, sum of sales is greater than 800,000. So if you ever gonna do multiple filters, then make sure that you activate that option under the Pivot Table options. (upbeat music) How about sum of sales in our Pivot Table here? Now, so that we want to include the average of sales. Now we can do that, and we can also filter by that. Now let’s our sales and drop it into our values area and from the dropdown arrow, which choose value field settings. And then we choose the average. And we can rename this to average and press okay. So we have the average of sales here. Now we can actually go and filter that. We can go to value filters then for example, we can choose greater than. Now in the show items, we have sum of sales, but in the dropdown box, we can actually choose the average so we can filter by the average, and in there we can put is greater than, and let’s put in an amount, greater than 55,000 and press okay. And we have our average filtered by that amount. (upbeat music) How could I manually filter here for the products? And I wanna show you how to add new items into this manual filter. Now let’s have a look at what’s in here. What I have are the bottles and tonic selected and the rest is not selected. So if we go to our data table, what I’m gonna do here is just copy and add a new item in there. And I wanna change the products from tonic, I wanna change it to cider. Okay. Now we’ll go back and refresh the Pivot Table and then we’ll see what happens. It doesn’t get updated in our Pivot Table, but what it does is cider is included in our filter list. So what we actually do is activate a setting within the Pivot Table, right-click and go to field settings. And in the filter, it says in here include new items in a manual filter. So we actually tick that box and press okay. So let’s go back and let’s add in another product and see what happens. Control + Copy, and paste in there. Instead of cider, let’s put in a new product called beer. And we’ll go back and refresh the Pivot Table. And we’ll see what happens now. Right-click, refresh, beer has been included in there. And also if you have a look at the filter list, beer has been ticked there. So now we’ve added a new item in a manual filter. Now last one we’re gonna do is bring beer on top, right-click and we can sort from A to Z and we have it there. So it’s a good trick to know if you want to include new items in a manual filter. (upbeat music) When you have multiple filters like we have here, it’s hard work to clear them all. For example, we’ve got a lot of filters in there, okay. Say we want to clear them with a click or a couple of clicks. Well, we’ll have to go in there and press all, okay., and then go in there and press all, okay. So it takes time. That’s not the quickest way. Let’s press Control + Z to go back. Now one way is to click in our Pivot Table and go to the options tab and choose clear, and press clear filters. But there’s another way, a quicker way. Let’s press Control + Z to go back to where we were with all of our filters. Now in our quick access toolbar, we can add in a clear filter button. Now let’s right-click in there and choose customize quick access toolbar. And in here we have the commands. Now the default setting is popular commands. Let’s click on the dropdown button and we can go all the way down to the data tab, choose that. And then we have the clear filter button there. We click on that and we’ll press add, and then we’ll press okay. And you can see it’s been added here. So now with a simple click, we clear all of our filters. Now this also works in your Excel tables. So a great tool to have when you’re working with filters in a Pivot Table or in an Excel table. (upbeat music) In the column labels over here, there’s no way that you could put in there a filter. Now if you highlight here, press filter, it doesn’t give you the option, but I’ll show you a quick work around. Click outside the Pivot Table and then press Control + Shift + L, and then automatically it adds in there a filter. So you can filter individual column items by going in there. Number filters, then you’ve got all these different options. (upbeat music) We have our P&L here shown in a Pivot Table, that shows the revenue, COGS and expenses for 2012, 2013 and 2014. And we want to show the top five expenses for each of the years. To do that, in the row labels dropdown box, we choose the P&L type and let’s choose only expenses. So unselect all and choose expenses. Now press okay. So we have the three years of expenses there. And the next thing I want to do is see the top five values for each of these items. So once again, click back into our filter. From the select field the dropdown box, we choose the item and from value filters, we choose top 10. And instead of top 10, let’s change that to the top five. And we’ll keep these to the items and actual, and press okay. So we have our top five items there. Now, finally, we click in our Pivot Table. So it gets sorted from highest to lowest, right-click, choose sort, and sort largest to smallest. So they’re all sorted there from largest to smallest. Now, finally, we can go to our Pivot Table tools tab and see a different layout. And just to show you how it looks, let’s choose the outline form. So in the outline form, we’ll have the year in one column, the P&L type in a second column, the item in a third column and the actual dollars in a fourth column. And in here, you can see the actual filters. So you can choose that. And you can see that we’ve chosen the expenses. And in the item, you can see that we have the value filter in the top five items. And also you can see that it’s sorted from Z to A. Now, another good thing with the outline form is that you can see each of the field headings in here. So the layout depends on your personal preferences. And as you can see from this analysis by filtering and sorting, we can get the top five expenses in your P&L. (upbeat music) We have all of our channel partners and we have 123 records. Now, we want to find out the top 25% of channel partners and list them. So what it is is 25% on 123 gives us around 30 records. We wanna find out the top channel partners. Let’s go down to our records by going Control + Down, and we’ll see our grand total is around 33 million and let’s go up. Now, the first thing we need to do here is right-click and then sort from large to smallest. Let’s go to a row labels, value filters and top 10, and let’s go to 25% of sum of the values and press okay. So let’s see how many records we get here. We get 21, which we put here earlier, and it doesn’t equate to the 30 or so mark we have there. So what this does is it gives us a top channel partners, that makeup 25% of sales. So we saw before that 33 million of total sales. So 25% of that is about 8.3 mil. Next one is let’s go in there and value filters top 10, instead of percent, let’s got to items. So in here let’s count that. So what it does is it gives us the 25. So it gives us 25 items and it doesn’t equate to the 30 mark that we’re looking for. Now, I’ll show you a workaround to get to our problem here. Okay, let’s go in here and clear the filter. Now, a work around to this is to press Control + Shift + L while you’re next to the Pivot Table. And then be tricks the Pivot Table to include a filter as you can see there. Let’s press Control + Z to go back, and then another way is to go to data and press filter. Okay, so from in here, we can go to number of filters, top 10, change it to 25, from the dropdown box, choose percent and press okay. So now if we count all this, we can see that we have 30 transactions. So we get our top 25% of channel partners. (upbeat music) In our Pivot Table, we have our sales month and products in our report filter. And we have some multiple items in there selected January, February, and March, but we don’t know which months are selected if we look at it from this view here. It says multiple items, but it could be any item from January to December. Now this was a real problem in earlier versions of Excel, but in Excel 2010, there’s a new feature. It’s called course license slicers. Slicers are large buttons that shows you what has been selected in your filters, or you can call them visual filters. Now let’s insert a slicer. We have to click inside our Pivot Table and go into the Pivot Table’s tools tab under the options, and in here, we click on insert slicer, and insert slicer. And we’ll get the insert slicers dialog box. And in here, we have all the field lists. So whatever’s in here is also included in the slicers. And we can select any one of them. Now we can select the ones that already active here, or the ones that are not, and let’s let the ones that are active. Sales month and products. And then we can also select sales region and financial year. And finally we’ll select the one that’s not part of our Pivot Table, and that is salesperson, and press okay. And now we have our five different slicers. So let’s arrange these slicers in our workbook. Just grab them and put them anywhere in there with your mouse. Okay. And the products we can bring down here. What we can do is just from the bottom, we can bring it all the way up and like this. Okay. So now we can see that the sales months in May have the three months selected as we said before, and also in our slicer sales month, we can see which months are selected. So now we get a view that’s not available in the report filter. So it gets rid of the multiple items problem there. And we can see that we have Jan, Feb, March, they’re highlighted in blue, and whatever is not highlighted that means it’s not selected. What we can do is from the top right hand corner, we can clear the filter and the Pivot Table updates automatically, and as well as the report filter. And now we can choose a slicer that’s not part of the Pivot Table filter. And then we can choose Homer Simpson and that gets updated automatically. Let’s choose each one of them. Now in here, it means that in the sales region that they’re available in Americas. And because they’re grayed out here, Europe, Asia, and Africa, there are no values. We can check Americas. And let’s clear the filters from here and go back. Now we can select multiple items by holding the Control key. For example, if we want Americas, we chose Americas, hold down the Control key, you choose Europe and choose Asia, and we get our Pivot Table updated accordingly. Now let’s clear that. If we want to choose six months, then hold on January, press the shift key, and then go all the way down to June. And that highlights there automatically as well. Slicers are a great feature, they’re new in Excel 2010, and they give us some visual filters that we never had before. (upbeat music) And let’s resize our slicers. We can actually click in the slicer and we can resize it with our mouse up or down. Now, if we go too much up, then we get the scroll bar. So we just make sure that that’s not there. And we’ll do the same thing here. And also for salesperson, we can also scroll inwards if we like, Control + Z to go back. And now we can move this up here just to make that a bit neater and this one up here. And then finally we can get them months all the way to the bottom there. Okay. So we can just resize as we see fit there. Let’s click out of the slicers. Now, when we click in any one of the slicers, we’ll get this slicer tools option. And we get this option here, which is similar to the one in the Pivot Table. So once you click in the Pivot Table, you get the Pivot Table tools tab. So you get the options and design. And if we click in a slicer, we’ll get the slicer tools option. And we have all these different options here. Now we have one that’s called slicer styles. Click down there, we have our light version and our dark version. Now we don’t have as many styles as we have in the Pivot Tables, but that’s okay these are good enough. And another thing that we don’t see is a live preview when we scroll over this. So we have to actually scroll and choose and then go back in, which is a bit annoying. Now, another thing you can do is if you hold on the Control key and choose all your slicers like that, you can actually go back to your slicer styles and choose one, and they all get updated automatically. You can choose from in there as well, Go to the light, and then you can choose from in there. There’s a few different options where you can work with. (upbeat music) There are 14 different styles under the slicer styles, and you may not like one of them. That’s okay. You can create a new slice of style by choosing the new slice of style option. And then you get a dialog box in here. Now you can rename this to John’s Wicked Slicer. then you have the different slicer elements in here, which relate to the different parts of the slicer. Now, once you make a change, you get up preview in here. And to make a change, you just gotta click in that format area. So for the whole slicer, we’re gonna put in a field of this color. You can also put in a border, if you like, or a font. Now the font will apply for the item in here. So we just press okay. And you see you get a live preview. Next, we’ll go to header and then format. For the header, we’ll fill it in with this color here. And the font will make it into a white font and press okay. Selected item with no data. Here we want to create a slicer where the effect is of a button. So to do this, we go to fill and then fill effects and let’s choose a gray color here. And then on the shading styles, we can use the star here, but you have the different star, so you can choose your sample here. Okay, so if we choose that we get the sample, but we wanna choose this pattern here and press okay. And then press okay. And you can see it over there. Selected item with no data. Here we just want to make it flat gray, and press okay. Unselected item with data, the same thing here. Unselected item with no data, here we’re just gonna make it into a white color and press okay. And the hover is whenever you hover over the slicers, you get the different color. So we can choose the same hover color for each of these four different hover options. So we go to the format. We can go to fill effects and then in here, we can choose this red and we can choose that hover effect. And we’ll go and do the same thing for the rest. You can see here on the right-hand side of the preview, we get the hover options and now we can press okay. Now, if we want to make this a default slicer, then we can click that. So any new slicer that we insert, then this is gonna be our default style. Now press okay. Now to activate it, you just gotta click inside that styles and then you go to custom style. So you’ve gotta click on that. So here we have our slicer with our button looking effect. And if we hover over there, you can see the red hover color. If we choose an item, then everything else that has a value is in gray. And if we anything that doesn’t have a value, is in white. So there it is there. Some pretty cool effects that you can do. And if you wanna go back and modify it, you can just right-click and modify, and you can make the changes there. You can also right-click and duplicate, and you can make some further changes and keep the changes that you make and you can rename it to whatever you like. Another thing you can do is you can delete it. You can also set as default. You can also add it to the gallery, to your quick access toolbar. And another thing that we can do is that if we have a current slicer that we like, and we just wanna make some slight modifications, then all we do is right-click in there and choose duplicate. And in here we can rename it to whatever we like. Name it John’s Wicked Slicer 2. And then here we can make the changes. For example, we can put in a whole slicer, format, we can put in a dark background if we like here. And then our border, we can make it into a dash and apply it there. And the fonts, we can change the fonts here. Instead of black, we can make them gray and bold. We can also make it a little bit bigger, 12 and press okay and okay. And to apply it, we just click from in here, or you can open it and click there. So now we have an extension of one of our current styles. Now, finally, if we go to a slicer elements in here, I’ve explained briefly what the different elements are. And if you make changes, then what part of the slicer will change? So this is a great tool to have when you’re formatting your slicers. (upbeat music) Now we can copy a newly created style that we’ve made previously into a new workbook. Now this is our new workbook here. And if you click on there, you can see the options. We have no custom styles. Now let’s go back to our workbook from chapter 7.3. And in there, we have our custom slicer which we’re created. Now we can move that onto the new workbook and then apply that custom slicer into all the slicers within that workbook. And to do that, we’ll just select the custom slicer Control + Copy, and let’s go back to a new workbook. And in here we just press Control + V. So now you can see that the custom slicer is in this workbook. All we’re gonna do now is click on the old slicer and press Control + A to select all and then choose the custom style. Escape, and now we have the custom style here. Now, this slicer doesn’t work in here. So what we’re gonna do is just highlight it and delete it with our keyboard. So now we can use the new custom style into a new workbook. (upbeat music) Apart from slicer styles, slicers also have settings. Now to activate it, you can go into your slicer tools option once you click in one of the slicers, and then on the far left-hand side, you can choose slicer settings. And in here you have your slicer settings dialog box. That’s one way, just cancel over there. The second way is just right-click in one of the slicers and the last option is slicer settings. So in here we have a few settings. First, we have the source names. That’s the sales region that comes from the data tables. That’s the field name. The second one is name to use in formula. And here you can use this slicer when you’re using cube formulas. And the name you can name this to whatever you like, something different, just something to distinguish one of your slicers. So I could rename this to John’s Slicer 1, and if I press okay, and then I click in the slicer, you’ll see here on the far left that John’s Slicer 1 is activated. So it’s in the name box there. Now right-click, again, go back to slicer settings. And then here we have the header. So the header is over here, where you see sales region, financial year and so forth. And you can uncheck that. If you uncheck that, then the header goes. Right-click to go back in. Now you can display the header, but you can also rename it to whatever you like. Instead of sales region, we can name it sales continent, and press okay. You can see that’s changed. Now, your data table has not changed. It’s only the slicer that has changed. So if you click in here where you had sales region up here, now that is not gonna change. It’s only the slicer. So it’s only for cosmetic purposes. Let’s right-click and bring it up again. Now we can also sort it here. We can sort it from ascending from A to Z or Z to A. If you click there and press okay, you can see that sorted. Now, right-click in there. You can also sort it from in here. Sort of A to Z or Z to A. Let’s go back to our settings. We have the option here to use a custom list when sorting. Now we’ve used the customer list in previous chapters and we can activate this. Let’s press okay and A to Z. And we’ll see, the custom list has been sorted accordingly. And we created a custom list to have Americas first, Europe second, Asia third and Africa fourth. We can check that to go into our files and options. And in advanced, we go all the way down and then edit custom lists. And here we previously created a custom list. So when we’re sort it A to Z, then Americas will be first, Europe second, Asia third, Africa fourth. If it’s Z to A well, it will be the other way around. Press okay to exit. And then we also have a few other check boxes here that you can check or uncheck. Now this says here, visual indicate items with no data, show items with no data last, and show items deleted from the data source. So you can leave them on. Depends on what you like. I usually leave them on. And let’s press okay. Let’s click in one of the slicers and press Control + A to activate all the slicers. Now, if we right-click and bring the settings again, look, we can’t change the names, which is fair enough. But we can get rid of the header for every one of them in one go, or we can rename the caption to call it cool slicers. And if you do that, then every slicer heading will be the same. Now, right-click to go back in there. We can also sort them all from A to Z in one go, just like that. And then also you have the custom list and also the check boxes if you want to show or not show some datas. So there’s a few settings there that you can play with and you have the flexibility to chop and change your slicers. (upbeat music) With a slicer, you can resize it to make it to your own liking. Now, mainly you can click in a slicer, and then from in here you can re-size it whichever way you like, as big or as small as you’d like. Another way is to right-click and choose size and properties. And in here you get your dialog box size and properties, and you have here the size option first, and you’ve got the height. So you can make your changes there and you get the live update and the width and the scale, you have the height as well and the width. You can lock the aspect ratio. So if you change one thing, all of them change accordingly. Now we can also see the position and the layout. So we can move left or right. Up or down. You can disable it as well from there. Another thing you can do is add columns. Now you got one column here going all the way down, but you can increase that to two, three or four, as many as you like. Imagine you had a lot of information there, putting it in two, three or four columns is much better visually and aesthetically. This works well when you’re using months. Now the button height as well can be adjusted, and the width as well. In properties, you can move and size with cells. You can move, but don’t size with cells or you don’t move or size with cells. You can also print object and lock it in there, and press okay. Now, another way that you resize is once you click in the slicer, under slicer tools and options, on the right-hand side you have the size, and the width, and you have the height. And also from here, you got the columns you can change. By pressing Control + A, you can select all of the slicers, and then escape to unselect. In here we have two columns, now let’s bring it back to one. So they can all be the same. Now by pressing Control + A, we can increase the columns for all of the slicers. Press escape. Now let’s press Control + A again. And in here we can align the slicers. We can align it to the middle just so they can be in order. Another thing you can do is when you got Control + A, you can move it around to wherever you like. (upbeat music) We have our Pivot Table, which has the financial year and sales region in the row labels, and the sum of sales in the values area. And now we’re gonna insert a slicer. So we’ll go to the Pivot Table tools, options tab, and choose insert slicer. And here we are gonna choose the quarters. So sales quarter, and press okay. And we can resize it and then move it up here. So we have our slicer for our Pivot Table, number one here. So we’re going to insert our new Pivot Table now. So let’s go to our data set, and in there we can choose insert Pivot Table and let’s put it into our existing worksheet and we can move it in here and press okay. And now we’re gonna put the salesperson in the row labels, the sales month in the row labels, and the sales in the values area. And we’ll get out of that. And we have our second Pivot Table. Now this Pivot Table is called Pivot Table number four. And this Pivot Table here is called Pivot Table1. And we can change this to Pivot Table number two, just for our example. Now let’s insert a slicer for our Pivot Table number two. And let’s choose the products. Slicer, and put it in there. So let’s resize it. Okay, so if we choose that, then our Pivot Table number two on the right-hand side gets updated accordingly. Now, what we want to do is connect these two slicers. So Pivot Table number one and Pivot Table number two, change accordingly. So if I choose Q1, then both Pivot Tables change based on that selection. And to do that, we need to select Pivot Table connections. One way is to go into the options tab and choose Pivot Table connections here on the left. Or another way, you just right-click in there, and halfway down, we have Pivot Table connections and we get this pop-up box that comes up. So what we’re saying is that this slicer that we created is connected to Pivot Table number two on the right hand side, and that’s right. Now we want to activate it and connect it to Pivot Table number one on the left, and press okay. Now we wanna do the same thing for the first Pivot Table slicer. It’s connected to Pivot Table number one on the left, and we want to check it so it can be connected to the Pivot Table number two on the right, and press okay. So now if we choose Q1, then both Pivot Tables change accordingly. Q2, Q3, if we choose the products, then as you see both Pivot Tables change accordingly. So you can have multiple Pivot Tables, multiple slicers, and you can connect them all together and with the press of a button that will all be in sync and talking to each other. (upbeat music) I will show you a few different ways on how you can filter a slicer. The first way is to mouse click on individual entries. Like this. The second way is to hold down your Control key. Once you select one item, hold down the Control key, so you can select multiple items. The third way is to select one item and then hold down the Shift key and then choose the last item you want to select and let go of the Shift key. Now this comes handy when you have a list of items that are over 50 and you just want to select half of them. And my favorite is click on the first filter, and while the mouse is still being pressed, scroll down all the way, just like that. And again, scroll all the way up, all the way down. And then by holding the Control key, you can de-select items. So there’s a few different ways on how you can filter a slicer. (upbeat music) I’m gonna show you how you can use one slicer to control two Pivot Tables without having to activate the Pivot Table connections. First of all, we need to click in our first Pivot Table on the left and select it by going select entire Pivot Table, then Control + Copy from the keyboard. And in here we’ll press Control + V. So we paste it in here. Now what we’re gonna do is we’re gonna take out the financial year and the sales region and include in here the salesperson and the sales quarter, just like this. Now that we have the two Pivot Tables, they’re using the same pivot cache. So if I click January, then they both change automatically. And if I select the first quarter, then the second quarter, and the third quarter and the fourth quarter. Now we can see this by going onto our Pivot Table connections, and the slicer is connected to both Pivot Tables. So there’s a quick way where you can use one slicer for two Pivot Tables without having to activate the Pivot Table connections. (upbeat music) If you wanna send this report out to someone else and you don’t want them to touch the Pivot Table, but allow them to use slicers, then you can do that. To do this we need to select one slicer, press Control + A to select all of them, right-click and choose size and properties. Under properties you’ve gotta uncheck the locked box and press close. And now we need to go into the review tab in the ribbon and choose protect sheet. Now in here, we’re gonna select the first option. The select unlock cells. We have to keep them activated, so we can be able to select the unlocked slicers. And then one more box that you tick is the use Pivot Table reports. And we can put in here a password to protect that, or we can just press okay, and it’ll protect without a password. Just like this. Now let’s escape so we can unselect all the slicers. Now I’m clicking in the Pivot Table and nothing’s happening. So the whole workbook is protected. But if I go on the slicers, I can actually select them just like this. (upbeat music) I’m gonna show you a cool way where you can use slicers and then have interactive employee photos show up. So here’s our slicer. If we choose Homer Simpson, comes up. Ian Wright, myself here, and Michael Jackson. Now there’s a few steps that want need to go through. And once you go through those steps, it’s pretty easy to understand. Now, what I’ve used here is the camera tool to take a photo. And I’ve linked that photo by putting a named range called show employee picture. Now that name range has an offset function in it. Now the offset function is here. It says, start here. Now I’ve named that range. And I’ve also named the range number of cells down. So for an offset function, we have the first part which is where do we start? So it has a starting point and I’ve called a start here. So I’ve called it here on the left cell, A15, start here. The second part of the offset function is how many rows down do we go? And I’ve named this number of cells down. Now I have named cell A9 number of cells down. So as I change this, then it goes down accordingly. So one row down, three rows down, four rows down, two rows down. So by linking this picture with the offset function, we can go grab these pictures that we have here. And it brings them back into this photograph that was snapped by the camera tool. So let’s go to the how to, and I’ll explain how it’s done. First of all, we need to create our table. So let’s get our table here with our number and employee names. So we can Control + Copy and Control + Paste in there. So we have our table here and double-click there. So the first thing we can do is insert a Pivot Table. So let’s grab our data and go to insert and Pivot Table, and we’ll put it into our existing worksheet. Now let’s pull that all the way down here, because once we insert a Pivot Table, we get all these area here and it’s gonna overlap. So we’ve got a bit of space here. Now what we’ll need to do now is to drop in the number field into the row labels. And that’s all we need to do. We’re not gonna put here anything else. So we’ve created our Pivot Table. Just one thing, right-click in here and remove the grand total. Okay, so we have the Pivot Table here and we’re gonna press Control + X to move it here and press Control + V. Okay. So we have our Pivot Table here. Now, one thing we need to do now is name the range. So we’re gonna make a selection, for example, number two and number three. So this cell here, D10, we have to name it because we’re gonna use that for the number of rows to go down in our offset formula. So to name the range, we’re gonna name a number of cells down. All we need to do is go in out main box in there and name it number of cells down. And we’ll put an underscore as well because in our previous example, in the interactive employees, we used this named range. So just to distinguish that we’ll put another underscore. And press enter. So now we have that named. Next, we have to insert a slicer. To do that, we click in our Pivot Table and go to options, insert slicer, and now we choose the employees. So we have the employees’ names there. Now, if we select all we have all of them there. So let’s put our employee names up there, just for now we’ll pack it up there. So the next step is to define our name for our starting position because of the first argument in the offset function is our starting position. So we’re gonna start over here and we’re gonna call this, start here as a defined name. So in there, we’re gonna call it a start here. Now we’ll use that name in our previous example. So we just put the underscore again just to distinguish it. So we call it, start here. The next step is to make these four rows here high enough, so we can include our pictures. So I’ve made them about 100 and you can adjust it to whatever you like. And also you can make them as wide as you like as well. Step number six is to insert the pictures. Now you can insert pictures by bone going into insert, and picture, and you have them all there. Now let’s cancel out of there. What I can do is just go back and grab these pictures. So Control + Copy, and Control + V. So make sure that it sitting there. So we’ve inserted our pictures. Step number seven, we need to define the name for the formula that will drive the pictures. So now we’re gonna put in there the offset function. To do that, we’ll go to our name manager and press new. We’re gonna call that function that will get our pictures. Now you gotta make sure that there are no spaces in there for that to work. And this refers to, well, we’re gonna put in there, our offset function. So we’re gonna say offset, where is their starting point? And we’ve made our starting point, start here. So we’re gonna put in there start here with the underscore, then comma, how many rows down? We’ve named that in there, number of cells down. So number of cells down and underscore. And the next argument is how many columns do we go right or left? And we’ll put in zero and then a comma and then close brackets and press okay. So we’ve defined our range there. Step number eight is to take a camera shot of a blank space, large enough to fit our picture. So we can take a shot over here, but I’ll show you an example. What you can do is just take a shot of a picture like this or space like this with your camera tool. Now, if you don’t have the camera activated, you can activate it by going into file, options and quick access toolbar. Now from the dropdown box, we choose all commands, click in there and press C to go down to the camera tool. And then you can just press add in that. Now I’ve already added it. Press okay, and it gets added in here. So we’ve selected a range here and let’s take a photo. So we’ve taken the photo and now we need to put it somewhere. Where do we wanna put it? We can put it in there. Just click anywhere. So we have our background. Now, finally, we need to reference this blank photograph to our offset named range. So we’ve defined our offset function with a name. So if you put out fun, it would give you the name tag there and then press tab and press enter. So now what it does is the offset function starts here, it goes a number of cells down, one. So it goes down here and it returns back whatever’s in there into our camera shot. Now, if we choose Ian Wright, it goes down three rows from our starting position. So it goes one, two, three. So in here, it’s looking in there and just taking whatever’s in there and returning it back in there. So that’s how it works. Now, finally, we need to format the photo here and just put in a background like this. And now you can use your slicer to bring up all the different pictures and you’ll be as happy as Homer. (upbeat music) In chapter 8.15, we created a P&L by using calculated items. And now we’re gonna add in some slicers where we can control the years and the months for the P&L. After that, we’re gonna drop in the plan numbers and then do a comparison between the actual and the plan numbers. Now let’s click in our Pivot Table and go to the options and choose insert slicer. And we’re gonna insert the months and the year fields. So we have the year field here and let’s just reduce the size here so we can drop it into the top left-hand corner, just like that. Now, instead of having a column heading called year, that’s right-click and get rid of that, let’s choose a slicer settings. And from in here under header, uncheck the display header option and press okay. Now let’s just drag it up a bit and it can fit in there. Okay, perfectly. Next thing is to get the months. And again, right-click, slicer settings, uncheck display header, and from in here on the top options tab, we’re gonna add in some columns. So we’re gonna have four different columns, and then let’s just resize this a bit so we can see it and we can just drop it in here as well. Okay, now the next thing that we can do is highlight the first slicer, press Control and with a mouse, select the other slicer, and then we can just change in the colors from in here. So now we have the different slicers, let’s check 2012, and you see the number changes there, and then we can choose Jan, Feb, March, whatever month that we want, and then the P&L gets updated accordingly. We can do the same thing for 2013 and 2014. Now the next step is to add in another Pivot Table with the plan numbers. So let’s highlight the Pivot Table, press Control + Copy. And in here we can just press Control + V and we’ve copied the same Pivot Table, but we can actually change this around. So instead of sum of actuals, we can get rid of that and let’s drop into the plan numbers in there, just like that. Now, instead of having the field and items listed here, we can just highlight this column and right-click, and press hide. So we can hide that. And we can just reduce this a little bit further in there. So now we can use the slicers to change the actual and the plan, just like that. Finally, we wanna add in a variance. So we wanna see the difference between the actual and the plan. In here, let’s just reduce this. And from in there, we’re gonna choose the revenue. Now we GETPIVOTDATA, so let’s escape out of that. Now to fix this, just click anywhere in the Pivot Table, go to options, and from the options dropdown box unselect the GETPIVOTDATA. Okay, now let’s go back in there and let’s do equals or plus. The revenue of the actual minus the revenue of the plan, and press okay. We can get this and drag it all the way down. And we have our values there. And in here we can put in the header called variance. We can click in there and from the format painter use the same formatting in there and the same thing in here. So now as we choose the different months, we get the actual, the plan and the variance. (upbeat music) We have our actual numbers for the year, 2014, and we want to create three different scenarios for 2015, 16, and 17. We wanna create a base case, a best case and a worst case. Now in our data set here, we have our actual values for 2014 hollered here in purple. Now all we’ve done is we’ve copied these values here and we’ve put in this scenario for base, best and worst case. So we’ll just copy and paste the values, and our idea is just to change the name from actual to base, to best, and then to worst, because when we do our Pivot Table and we create the three different scenarios, we want the 2014 actual numbers to be shown all the time, because we’re gonna do a variance analysis. Now, what I’ve done here at the bottom here is putting their 2015 values. So I’ve done the three different scenarios, worst, base and best. So I put in different colors just to distinguish them. And then in here, what I’ve actually done is I’ve put in a formula that relates back to the 2014 actual values. And I said, the worst case will be 95% of that. So I’ve done the same thing for each of the months. Now for the base case, I said that it’s gonna be about 5% increase on 2014. And then for the best case, I say, it’s gonna be about 20% increase 2014. Now I’ve done the same thing for 2016, but I’ve changed the values there. I said that 2016, the worst case will be the same as 2014. It’s base case will be about a 10% increase. And then its best case will be about 25% increase. And the same thing for 2017, I said, it’s gonna be a 5% increase on 2014 for its worst case, 25% increase for its base case, and then a 50% increase for its best case. Okay, so what I’ve done is I’ve gone through the Pivot Table in here, and what we have to do now is drop in our sales month into the row labels, our financial year into the column labels, and then our sales into the values area. And let’s just double-click in there to make it even, and then just put it into the center and we can just make it a little bit bigger like that. So we have our values here, but what we can do now is drop in our slicer. So go to options, insert slicer, and let’s drop in this scenario slicer and press okay. Now let’s make a couple changes to this. Let’s make it into four columns and then we’ll just drag it across like that. And then right-click in there in slicer settings, and let’s get rid of the display header, ’cause we don’t have to save that. And let’s just put it like that and put it on the top there. So we’ll have all our scenarios here. So if you choose the actual case, then we just see the actual numbers for 2014. If you choose the base case, because we had the numbers in 2014 in base case as well, we can see that 2014 shown there and we’ve got it 2015 to 2017 base case scenarios, but we’ve got the best case and the worst case. So finally what we’re gonna do is it drop in a value calculation to see the difference between the 2014 numbers. So click in the Pivot Table, grab the sales, drop into the values area. From the dropdown box, choose value field settings, show values as. From the dropdown box, we choose the percentage difference from. Now, the base field is gonna be the financial year and the base item will be 2014. So we’re gonna show the values as the percentage difference from 2014 financial year. Now the custom name we’ll just change that to percentage variance from 2014, and then in the number format, the custom, let’s just choose this format here and before the semicolon, let’s put in that percentage and the same thing there, let’s put in a percentage and press okay, and then okay there. Let’s just reduce this a bit. So we see the worst case scenario for 2015 is minus 5% on 2014, 2016 will be even, and 2017 is a 5% increase. If we go to our best case scenario, we see the different increases there. We have our best case scenario as well, and we can see the changes. (upbeat music) A calculated field is a newly created data field. This is created when you make a calculation with your existing fields. So in essence, you’re adding a virtual column to your data set. And to create a calculated field, you gotta click anywhere in your Pivot Table, and then in the options tab under the calculations group in the field items and set dropdown, choose a calculated field, which is the first option and you get your insert calculated field dialog box. Now in the fields here, you have all the fields that are in your Pivot Table field list. Okay, so you can choose any one of them. Now on the top, we have the name and this we can change to customize it. So what we’re gonna do now is get our cost of goods sold, which is our costs divided by our sales. Now the name, let’s change it to cost of goods sold or short, COGS. Now in the formula, you have the zero there. You gotta get rid of this. Backspace to delete it. Now the next step is, choose your field. So to do that, we’ll get our costs. We can click once and press insert field. And now we can use the mathematical science that we use in Excel. So we can use divide. We can also use the minus, plus, multiplication, we can use percentage, we can use to the power of, and also smaller than, bigger than or equals to. We’re gonna use the divide. So cost divided by sales. Now let’s find our sales and we can press insert field or double-click, and then we can add this. So it’s added in our list here. And then we can press okay. Now when we press okay, you’ll see that a new column will be created, and also COGS will be added into our field list as a virtual field. Press okay. So COG is added there and also in here in our values. Now, one thing we need to do is to right-click in here and number format, because it’s a percentage, we need to use the percentage and press okay. So just to format it there. So we have our cost of goods sold there. And finally, we can go into our values area and change the name from sum of COGS to COGS. Now click on the dropdown box and choose the value field settings. And in here we can get rid of this. Now, what I usually do is put in an asterisks there, just so I can distinguish that it’s a calculated field. Because if not, then you may confuse, you may think that this COGS might be a summarized value, or it could be a calculation. So it’s always good to put some kind of sign beforehand just to distinguish it and to show us that it is a calculated field. Now let’s press okay. And we have our COGS in there. So what we can do now is when we filter our Pivot Table, then this calculated field changes as well. Now if I put in there the sales month in there, then that will change as well. If I take out the financial year in there, we have our COGS which gets recalculated. So it’s embedded into the pivot cache just like a grand total. (upbeat music) Now, we can use any existing calculated field to create a new calculation within our calculated field. And to do this, let’s click in our Pivot Table and go to the options tab and under calculations, choose fields, items and sets, and choose calculated fields. What we want to do is calculate our sales margins. So the calculation will be one minus COGS. First of all, let’s change the name and call it sales margin. And in our formula, you get rid of the zero. And then put in one minus. And here we’re gonna choose COGS. So our previously created calculated field is included in our field as well as our field list. So let’s double-click on COGS and press okay. So we get our sales margin there. Now we need to format the numbers into percentages, right-click and press number format, and percentage, and this put one decimal place just to activate the percentage symbol. Finally, we’re gonna put in an asterisk to our sales margin just to distinguish it, so that we know it is a calculated field. To do that, click in our dropdown arrow, and choose a value field settings. In here, we get rid of sum of sales. And if we get rid of these and press okay, we’ll get an error message, that the Pivot Table field name already exists. Well, that’s correct because it exists in our field list down here because we created that in our calculated field. So we’ll need to distinguish it. Now we can put in a space and that will work because Excel recognizes space as a character, but instead of a space, because we want to distinguish this calculation as being a calculated field, then we’ll just put in an asterisk, and then press okay. So we have the sales margin there, which is our calculated field, just like our COGS. And up here, we have our sales margin and our COGS. So we’ve used one calculated field to create a second calculated field. (upbeat music) If you made a mistake whilst creating a calculated field, then you can go back and edit it. Now to do that, you click anywhere in the Pivot Table and choose the options tab and then fields, items, and sets, and calculated field. In here from the dropdown box, you’ve got your calculated fields. Now we can choose our sales margin. We can modify or delete. If we press delete, then it’ll delete the calculated field from our Pivot Table and our pivot cache. Now let’s press that just to see, and press okay. So you can see that it’s gone from there. And sales margin is also gone from our pivot cache and our values area there. If you press Control + Z, you can’t go back. You have to go and recreate it. So once you delete it, make sure that you’re certain that you don’t want the calculated field before you proceed. Now to modify our calculated field, we can choose calculated fields. And from our dropdown box, we choose our COGS. Now, first of all, we gotta press the modified button. So in here we can make our changes. So instead of costs divided by sales, we can say, for example, one minus costs, and then we can press okay. And you can see here the change we’ve made. Now one minus cost, it means nothing. I’m just showing an example that you can go there and modify it. We can go back and change that. Once again, COGS, modify, instead of one minus cost, it’ll be cost divided by sales, and then press okay. So the changes we made and the calculated field also remains in our Pivot Table field list and our values area. (upbeat music) Within a calculated field, we can use any Excel functions like a sum, an if, an or, an and, or an average as an example, as long as I don’t reference external cells. Now, let’s create an if statement. Click in our Pivot Table and go to options and fields, items, and sets, and calculated field. Now in the name, we’re gonna change that. So what we want to see are rebate given if our sales are more than 700,000. So if our sales are more than 700,000, then we’re gonna give a rebate of 3%. So the name will be rebates given, and the formula, we’ll get rid of zero. Now we’ll start typing in the if statement just like we would in our Excel workbook. Now, one thing in here is when you’re typing in an Excel function, you don’t get the help bar. So you gotta make sure that you know what each step within a function needs to be. So within and if function, the first step is our argument. So if sales are more than 700,000, then we have to give a 3% rebate on sales. So would be sales times 3%. If not, then zero rebate, close brackets and press okay. So you can see there, we have our rebates given for anything over 700,000, anything less than 700,000 is zero. Now just make a note that we have to get rid of the sub-totals and the grand totals, because what’s happening is that when you’re doing a calculated field, that it’s also calculating each sub-total. Now this is not correct because our sub-total for January is 23,000. That’s the only a rebate that was given. But here we’re getting 81,000. So make a note of that when you’re doing calculated fields, and you have an if statement where you can get zero values, then you gotta make sure that the sub-total is turned off. So to do that, we just go into the design, sub-totals, do not show sub-totals, and then grand totals, off for rows and columns. One final step is to rename our rebates given in our values area. From the dropdown arrow, choose value field settings, because we want to distinguish our calculated field. Then we just put in there an asterisk, and then press okay. So we have our rebates given. So it’s that easy to create a calculated field with an Excel function. (upbeat music) A calculated item is a virtual data item, created by using a row label or a column label item. So calculations will be based on the items in the months row label and also the years in the columns labels. Now, when we did the calculated fields, we used the field list to do our calculations, but now we’re gonna use the items within the field list. So let’s click anywhere in our row label or column label. So if we go to options and field items and sets and choose calculated item, we’ll get our dialog box. Now on the left-hand side, we have the fields and on the right-hand side, we have the items. So we’re gonna use our items to create a formula. Now, what we wanna do is create a bonus scheme. So for the first half of the year, we give a 10% bonus. And for the second half of the year, we give another 10% bonus. So our formula name will be H1 Bonus, and then in the formula, we get rid of zero. And we’re gonna put 10% times, now in here we can put any mathematical equations that we will normally use in an Excel function. So we can use the times, the plus, the minus, the power, less than, more than and equals to. In our example, we’ll use the times. So 10% times and a bracket. So the first half of the year, it’ll be January plus February, plus March, plus April, plus May, plus June, close bracket and we’re gonna add this. Okay, so we’ve added this in there. Now we again create a new formula for H2. So we can override this, that’s fine. So let’s get rid of the content in there. And what we need to do is choose a sales month. Now it gets added in here. Now that’s fine. If you press okay, it’s not gonna work because we’re in calculated items and it can only take in the items. So let’s get rid of this. And let’s put in our months from July to December. July plus August, plus September, plus October, plus November, plus December. Now, you’ll see here that our calculation that we did before is included in items within the sales month. And we can use this later on to make further calculated items. Okay, so we’ve done our H2 Bonus and press add. And we’ll see, it’s gonna get added in the bottom of our row labels. Press add, and then okay. So we have our H1 Bonus which is 10% of the first half of the year. Now we see our sum there is 5,011,116. So our bonus will be 10% of that, which is here, which is correct. And from July to December, our sum is 5.3 million and we have the same there. And it calculates it for each year as well. Now the grand total, make sure that that’s where you stop, because if you add this, it adds the H1 Bonus and the H2 Bonus as well into the grand total. Now that’s a shortcoming of calculated items. So we have to delete the grand totals or any sub-totals that you may have. So to do that, go to the design, grand totals off for rows and columns. (upbeat music) We can use an existing calculated item within their new calculation. What we wanna do is get our H1 Bonus and see what our average is for the six months. So it’ll be the H1 Bonus divided by six and the same thing for the H2 Bonus. And to do this, let’s click in our row labels, and go to the options tab and choose the field items and sets and the calculated items. In the name, we’re gonna call it average H1 Bonus. In the formula, get rid of zero. And we’re gonna choose the H1 Bonus. I wanna divide it by six, and then we can add this. Next we’re gonna get the average H2 Bonus. We can just override these and get rid of this first, and let’s go back to our sales month. Okay. And get rid of sales month. Now, let’s choose our H2 Bonus, insert item, and divide it by six. And we can add this and press okay. So we have our average H1 Bonus, which is 101,000, and our H2 Bonus 89,000 for 2012. For 2013, we have the same values. And 2014, we have the calculated item as well. So you can use previously created calculated items and you use them in your new calculations. (upbeat music) There’s a couple of ways to edit a calculated item. First of all, let’s click in our row label, go to options and fields, items, and sets, and calculated items. From the dropdown box, let’s choose the average H2 Bonus. Now in here, if you want to delete it, you can just press delete, and press okay. Now that’s gone forever. So before you deleted anything, make sure that you really wanna delete it. If not, you gotta go back and recreate the calculated item. Now, if you wanna modify a calculated item, just go back and choose calculated item. And for a dropdown arrow, choose average H1 Bonus. Now we can make changes to the formula here. That’s fine. We change that to eight or 12 or anything like that, but if we make any changes to the name, for example, we change that one letter, then it adds whatever we’re making here as a new calculated item. So if you wanna modify a calculated item, you can only modify whatever is in the formula. So let’s go back and press S. So for example, instead of six, we can change it to 12 and modify and press okay. And you see that changes there. Okay. Another way where we can make a change is within the Pivot Table. Now the formula is there. So we can go back and change that to six and press enter. What happens is it only changes that for that here. So you need to go and change it for each subsequent year. You can also change the name there. Instead of average H1 Bonus, you can call that average bonus. And if we go back to our calculated item, then you see the name there has changed as well. It can be a little bit tricky when you’re modifying within a calculated item. So just make sure you take care before you make any changes. (upbeat music) We can also use Excel functions to calculate an item, as long as they don’t reference any external cells. So you can use functions like sum, if, or, and, average, and so on. Now to do this, let’s click in our row label and go to options and fields, items, and sets and calculated items. So what we’re gonna do here is get the average for 2012, 2013 and 2014. So in our name, we can call that average. And in our formula, we can go back, get rid of the zero. Let’s put in average, open brackets and put in January, February, March, April, May, June, July, August, September, October, November, and December and close bracket, and we can just press okay. And then we’ll get out average here for each year. And we can check this. Let’s highlight Jan to December and in our status bar. We have our metric set. Now, if you don’t wanna have this just right-click, and you can choose here, the average count, numerical count, minimum, maximum or sum to activate it. Now we can see that our average is 865. If we go back 865. So the same thing for 2013 and 2014. (upbeat music) We’ve been using calculated items in our row labels. We’re gonna also use them in our column labels. So to activate that we can just click anywhere in the column labels and then go to the options tab, fields, items, and sets and choose calculated item. Now in here, we can create our formula. So what we’re gonna do is get the variance between 2014 and 2013, and also 2014 and 2012. So put in here variance 14 versus 13, and get rid of the zero and the formula will be 2014 minus 2013. And let’s add this. And let’s do another one. Variance 14 versus 12, and in here financial year. Okay, let’s get rid of financial year and choose 2014 minus 2012, add, okay. So we have our newly created calculated items that give the difference in our column items. And it’s important that we name them as we have, because if we filter, for example, take away 2012, then we’ll know what these values relate to. And to go back, we just filter off. Another thing is that we can put him in there sales regions, add it in there, and that calculated item will also calculate in there. Also we can go to design and add in our sub-totals to the top of the group. And again, we have our calculated item working there as well. And you can also do this if you had actuals versus budget instead of years. It just depends on what items you have within your data source. And if you put them across the column labels, well, you can do your calculated items there. (upbeat music) There are a couple of limitations when you’re using calculated items. One of them is if you have the average sales here, like we do average of sales in our values. And also you can see there, we’ve summarized it by the average. And say, we want to go into our row label and calculated item from there, we get a warning that averages, standard deviations, and variances are not supported when a pivot has calculated items. So that’s one short form. Now, if you had a calculated item in here already, and you wanted to add in there an average standard deviation or a variance, then that also could not be done. Let’s go to our next shortcoming here, grouped items. We have group sales here. Now let’s go into our field items and try to put in that calculated item. Again, we get a warning that we cannot do this because the Pivot Table report field is grouped. Now, if we had a calculated item in there and wanted to group anything with a calculated item in there, then that also will not work. And finally, when you’re in a row label here, you can only do a calculated item for the actual row label that you’re in. So with selected products, you can go and create a calculated item for salesperson. To do that, you gotta click in salesperson and then go to fields, items and sets, and choose calculated item. If you wanna do it for products, you gotta click in products and then choose calculated items. (upbeat music) I’m gonna create a couple of calculated items. One for the row labels and one for the column labels. And then I’ll show you how we can use the solve order to get around a problem that can occur. So, first of all, let’s do a calculated item for our month, click in the row labels there and go to the options and fields, items, and sets and choose calculated item. And our formula will be the December sales divided by all of the year sales. So we want to see the weight of sales in December. So let’s change the name to December portion percentage. And in here, we’re gonna choose December and then we’re gonna divide it by the sum of all the months. Close bracket and press okay. Just to make this a bit bigger and in here. So we’ll go to the home tab and then we just put in a percentage in there and we just put a decimal place if you like. And next let’s sum the different regions that we have. So we’re gonna sum Americas and Africa into West and Europe and Asia into East. So to do this, we just gotta click anywhere in that column label and go to the options in the fields, items and sets, choose calculated item. In here, we’re gonna call first formula East, and we’re gonna choose Europe plus Asia and we’ll add. The next formula will be West. And in here we’re gonna choose Americas and Africa, and press okay. So finally we change this around. So Americas and Africa we can put together along with West. And then Europe and Asia are together and the totals are there. Okay. Now let’s just format this a bit. Okay. And in here, we’ll put up a bold for the West and for the East, we can bold that. So we can see our results. And we have a problem here in that the calculation that’s down here is not the same calculation that’s in the December portion. It’s giving us a wrong calculation. So we can fix this. Let’s go to the options and fields, items and sets, and choose solve order. Now in here in solve order, it says, if the value in a pivot cell is affected by two or more calculated items, the value is determined by the last formula in the solve order. So we have two different calculated items. So what it’s doing, it’s taking the last calculation that we did, the West, which is Americas plus Africa. So it’s taking that calculation to calculate this. We don’t want that. Now we’re gonna move the December portion percentage to the end so it can take effect. Now to do that we click and then move it down and press close. And you can see the percentages have changed. And also you can see there that the formula has changed, and in there the formula has changed. So can you use a solve order if you have two or more calculated items that are clashing. (upbeat music) Every time you create a calculated item or a calculated field, then the formulas that you use are listed. Now to check that you just click anywhere in the Pivot Table, go to options, fields, items, and sets, and then choose a list of formulas. Now, in here, we have our calculated item formula for the December portion. Also we have the calculated item for our column labels. Choose that, and we can see the East formula equals Europe plus Asia. The West formula equals Americas plus Africa, and with December portion percentage, equals December divided by the sum of the whole year. And they’re listed in order of one, two, three. So the December portion is the last solve order, and that takes precedence when there are two or more calculated items that clash. So this is a good way to see what calculated items or calculated fields that you have in your Pivot Table. (upbeat music) Now we have our calculated field here, which we created earlier. Now we’re gonna remove this temporarily. If you can see here on the right-hand side, on the Pivot Table field list, we have the COGS calculated field in our pivot cache. We can just uncheck and remove it. And then we can go and do some adjustments to our Pivot Table. For example, we can take out the sales region and sales month, and we just bring in here the quarters. And if you want to bring in the COGS again, then we can bring it in there. And the only thing is that we just need to format this into a percentage, press percent and press okay. So you can temporarily check or uncheck the calculated fields. (upbeat music) The order of operations is a rule used to clarify which procedures should be performed first in a given mathematical expression. The calculations in a Pivot Table also follow this order of operations. For example, we have our table here called order operations listed by first to last. So the bracket take precedent, then the percentages, then be exponents, then we have the division and multiplication come next. Now these are equal in precedence. Addition and subtraction, come next. Now these are also equal in precedence. And then we have the comparisons. Now let’s go to our example up here, just to have a look. We have the formula two plus four times five. So in here, the multiplication has a higher order than the addition. So this will get calculated first. So the four times five will get calculated first. So four times five is 20, and then it’ll add the two because the addition comes after the multiplication in the order so we have 22. Now in the next example, we have put brackets between two and four. So obviously the bracket which come first in the order of operations take precedent. So it will calculate two plus four first, which is six, and then it’ll multiply it. So six times five is 30. Now this order of operations is also used in Excel and in your calculated items and fields. So when you’re making your formula, just make sure that to look at this order of operations, if your formula is not working properly. (upbeat music) In this chapter, we’re gonna create a P&L where we show the revenue, COGS, gross profit, expenses, and then get our operating profit over the 12 months. And what we’re gonna do is add in a trend line by inserting some sparklines. And also we’re gonna put in a slicer to see the different years. Now, we’re gonna include calculated items in here and the calculated items are the gross profit. So the calculation will be revenue minus COGS. And then the second calculated item is down here, which is operating profit, which will be the calculation, gross profit minus expenses. So we have our data in here and we have our months going down on the month column. We have our different years. We have a different P&L types, separated COGS, expenses and revenues, and they’re separated into the different items. So we have different expense items as you can see in a normal business. And we have the actual values and the plan of values. So this is a typical P&L that you find in most businesses. Now, from in here, we can create a Pivot Table. We go to insert, and Pivot Table, and we’ll put it into a new worksheet, and press okay. In the row labels, we’re gonna drop in the P&L type. And then we can drop in the item at the bottom. And then on the column labels, we’ll put in our months and in the values area, we’ll put in the actual dollars. And let’s close this, and we have our P&L taking shape. Now let’s just make a few design changes. We can choose this Pivot Table design, got to view and get rid of the gridlines, but we can reduce this to about 80%. Now, the grand total, we don’t want that. We can just click on grand total, right-click, and then remove grand total. So we have our P&L here. Now let’s click on COGS, and we can actually bring the revenue up there by just typing in revenue. REV, and you’ll see, it gives us the revenue option. And then press tab. So it automatically moves the revenue from the bottom to the top. We have our COGS, and that’s fine. Let’s minimize that. And now we have the expenses there. So what we’re gonna do now is get the gross profit. So let’s click anywhere in our P&L type item. And then go to the options and fields, items, and sets. And in here, which choose calculated item. Now, the calculated item we’re gonna do is gonna be called gross profit. So it’s gonna be revenue minus COGS. So the name is gross profit. And the formula we just click there, and backspace to get rid of zero. And then we’re gonna get the revenue. Double-click, the minus sign, and then double-click on COGS. And then we’ll press okay. And you can see it’s added it down here, gross profit. Now it’s calculated all the different items that belong in the revenue, but we don’t want that. So what we’re gonna do is the actual values are within the sub-totals in here. So let’s minimize gross profit and let’s go up here. And then we can just click on there and grab it and just put in there. Now let’s right-click and to show the field list. And from the values area, let’s just format the numbers. So we’re gonna put in there a comma. Let’s choose number format, and then number, no decimal places and use 1000 Separator, and put a negative red font there. Okay. So we’ve entered our first calculated item called gross profit. Now we’re gonna add in our second calculated item, and it’s gonna be called operating profit, and it’s gonna be the calculation of gross profit minus expenses. So firstly, we have to put in our cursor in one of the items within the field name called P&L type. And anyway, here in the blue area, we can choose and then go to options, fields, items and sets, calculated item. Now from the dropdown you see we have the gross profit, but we wanna create a new calculated item, and we wanna call it operating profit. In the formula, let’s get rid of the zero. And then in the items we have the gross profit, which was the calculated item that we created earlier. Let’s double-click there and then press minus and then double-click in expenses and then press okay. And we’ll see we have the different calculations for the operating profit. Now in our operating profit here, we have the expenses being deducted from the gross profit amount. Okay. So now let’s go to the operating profit. Now we don’t actually need these numbers here, they don’t mean anything to us. We just need the sub-total there. So let’s minimize operating profit and then go all the way up. Now, one thing is, let’s get rid of the grand total there. We can go to design, grand totals, and off for rows and columns. Now let’s select the months there and right-click, and column width let’s choose 12. Now in here, we’re gonna put in our trend. So we’re gonna put in some sparklines to see our months and how they’re trending. So let’s type in trend and we can click there and format the painter and just bring it in there. Now, one thing let’s make this centered, okay. And we can just the format there. Okay, so now let’s go into insert and sparklines. Let’s choose a column for our sub-totals. The data range will be January to December. Press enter and then press okay. So we have the sparkline, let’s make this a little bit bigger. Now let’s choose a different color. We just get a light color there and then under the marker color for the high points, we want a red. So we wanna see the highest points. So we’ll see here that our fifth month was the highest point. Now what we’re gonna do is press Control + Copy and highlight this area, hold on the Control key, and then highlight the operating profit. Let go of the Control key, and now I just press Control + V. And it fills in these sparklines for the respective sub-totals. Now we’re gonna put in a sparkline in here. So go into insert and let’s put a line, data range, January to December, press enter, and then okay. Now once again, the color will go blue color and that high point we’ll make it red. And again, Control + Copy, select that, hold the Control key down, and then select the other range. Let go of everything, now Control + V. So we have entered the different sparklines there. Now, last thing we wanna do is put in a slicer on the top here so we can tell the years. So click in your Pivot Table, options, insert slicer, let’s choose a year and press okay. So from in here, we can actually now this is selected, choose the columns two, three, and then we can just make it a little bit bigger, and right-click in there and then slicer settings, let’s get rid of the display header, and press okay, and we can bring that like that. And let’s put it in the corner there. Okay. So we have our P&L here with our sparkline trends, and our years here. So if we choose a year, 2012, the numbers change, the sparklines change, the same for 2013 and the same for 2014. And I think your boss would be pretty proud of the final product. (upbeat music) in this chapter we wanna create a variance report for our sales regions and products over the different quarters. And we’ve used the calculated fields to calculate our variance. So what we’ve done is we’ve got the actual versus the plan. Now you can see that in yellow for each of the quarters and also for the total on the right-hand side there. And with our slicer, we can actually change the months and our calculated fields change as well. So let’s go over to our data table and I’ll explain to you how we can set this variance report up. So here we are in our data source. We have the customer, product, salesperson, sales region, as we had before, the order date. And here we have the actual and plan. And we’re gonna use these fields here to calculate our calculated field. So we’re gonna say the actual minus the plan will give us our new calculated field. Now let’s click anywhere in our data table and go to insert, and Pivot Table. And we’ll go in and put it into a new worksheet and press okay. Now the row labels, we’re gonna put in the sales region and the products. On the sales value, we’re gonna put in the actual and the plan. And in their column labels, we’re gonna put in there the sales month. And let’s grab the sales month and just bring it on top there on the column labels. Now this view, we’re gonna see the actual and then the plan. And then we’re gonna add the calculated field in the next column down here. It’s gonna say actual minus the plan and will give us the variance. So let’s close in here and do some cosmetic changes. And we’ll go to view and get rid of the gridlines. And then let’s minimize this. Let’s go all the way down like that, like that just for now. And we can make the changes later. ‘Cause another way in our Pivot Table, we can just go to the options and choose the fields, items and sets, and then choose a calculated field. Now in here the name, we’re gonna call it actual versus plan. Actual versus plan. And the formula, let’s get rid of the zero, and we’re gonna double-click on the actual field, put the minus, and then double-click on the plan field, and then press okay. So you can see there the sum of actual versus plan has been added for each of the months. We go right across there. You can see that’s been added there. Now, let’s click and right-click on show field list. Now the sum of actual versus plan, the calculated field has been added into the values area. Now let’s choose a drop-down, go to value field settings. And instead of calling it sum of actual versus plan, let’s get rid of this, and let’s put in an asterisk. Just to distinguish this that it is a calculated field. And then just press okay. Let’s go to select entire Pivot Table, then select values and then press Control + 1 to bring up the format cells dialog box. And in the number, let’s just format the number, get rid of decimal places, the 1000 Separator and the red and negative font and press okay. You see that changes that for everything there. Now what we wanna do is a group our months into quarters. So let’s highlight the months that we wanna group, right-click click in there and press group. Now the default name, Group 1 is shown, but we can overwrite that by just typing in Q1 in the keyboard and pressing enter. Let’s do the same thing for the other months. Let’s grab April, May and June, right-click, group and call it Q2. Let’s grab July, August, September, and call it Q3. And then finally, October, November and December, right-click, group and call it Q4. Let’s just make this a little bit neater. Okay. Let’s pull up on the left. ‘Cause now that everything’s grouped, we can just right-click and expand, collapse, collapse entire field. So it collapses all the fields and we have the actual versus plan for each of the quarters now. So let’s highlight the actual versus plan. Hold the Control key down on your keyboard, and let’s just select the calculated field. And then in the font, let’s put in a yellow font, just to distinguish it. Now, if we hover over the actual versus plan calculated field, we get a little black arrow. Now press the mouse, and then it highlights everything. Press Control + 1, and we get the format cells in the border. We can put in there a black or a blue border. Let’s put in a blue one. And then on the right-hand side, just to show where the actual versus plan finishes. In the column labels and the row labels, we don’t want that. Let’s go to options and then get rid of the field headers. Now, finally, we’re gonna put in a slicer just to see the different years. So let’s make a bit of space in there to put in the slicer. Click around in the Pivot Table, go to options, insert slicer, and let’s grab the sales here. So financial year and press okay. Now right-click in there, go to slicer settings and click in there just to get rid of the display header and press okay. Now let’s move this like that. And then the columns let’s make it into three columns there. And we can move it over there and we can change. So with a slicer, we choose 2012, the actual versus plan calculated field which changes for each quarter and the total. 2013, the same thing, and 2014 as well. So here’s a quick variance report created by using a calculated field for your actual versus plan fields. (upbeat music) With chats, you can roughly see your data and can easily see trends within your data. Now in a Pivot Table, you can insert pivot charts. Now this is a visual way to see your Pivot Table data. A pivot chart is an extension of your Pivot Table. So as you’re making changes to your Pivot Table, then your chart also gets changed. So let’s insert a pivot chart. Well, first, we have to click in our Pivot Table and in our Pivot Table tools tab in our ribbon, we choose the options and on the right-hand side under tools, we have pivot chart, and then we choose there. Now we get our insert chart dialog box, and we have the different charts on the left. Now let’s insert a simple column chart and press okay. So now we have our chart in here. And note that the X-axis has the sales region. So all the row labels are always in the X-axis. And then the Y-axis, we have our years and our values. If we wanna move around the sales regions to the column labels, we can do that. And you’ll see that our pivot chart will also change. So let’s get the sales region from the row labels to the column labels, and then the financial year down to the row labels. As you can see now in the X-axis we have our financial year and on the Y-axis, we are showing our regions. And you’ll also note that when you’re using a pivot chart, that the names change here. So instead of row labels, we have axis fields categories. Instead of column labels, we have legend fields series. Another thing that you will notice is that we’ll get our filters in our pivot chart. So we can actually filter from in here. So we can choose the financial year just to include two years, and that gets changed, as well as our Pivot Table. So they’re both connected. So this pivot chart is an extension of the Pivot Table. Now we can make the changes from the Pivot Table and select all and pivot chart gets changed as well. Sales regions, we can just choose one. This gets amended and so does our Pivot Table. We can also go back to our Pivot Table and make the changes there. Now these report filters within our chart takes up space. So I like to get rid of them. Now, just hover over one of the report filters and right-click, and then choose the hide all field buttons on chart. So now we’re just showing our chart. Now we can use our Pivot Table to control the filters, and change our chart. Go back and select all. So this pivot charts give us the power to visually see our data within our Pivot Table. (upbeat music) Now, if we click on our pivot chart, we get the pivot chart tools on the ribbon here. And we have the design layout format and analyze. Now let’s click on analyze. In here, we can see the field buttons. So we can show all or we can hide it all. We’ll choose whichever ones we want to see. We also have the option to see our field list. We can clear all or clear all filters from here. We can also refresh the data and we can insert slicers. Let’s insert a slicer. Now we’ve covered slicers in our chapter seven. Okay, so let’s go and choose our sales quarter. And then we can also choose our salesperson and press okay. So we’ll have our two slicers added in here. And we can just move them a bit like this. Okay, so as we choose the salesperson, then the chart and the Pivot Table gets filtered automatically. Now the same thing for the sales quarters. If you wanna say Q1, Q2, Q3, and Q4. So the slicers, it gives us a visual way to see our filters that we have selected. Now we can also click in our Pivot Table and choose options and insert slicer, and from in here we can choose our financial year and press okay. And now we can choose 2011, 2013 and 2014. So there’s a couple ways to insert a slicer. And once you insert them, they’re all connected to the pivot chart and also the Pivot Table. (upbeat music) If you click in your pivot chart, you get the pivot chart tools tab. And we have analyze, format, layout and design. Now under the design, we have a few different options here. First of all, we can change the chart type if we click in there. We can choose any of these charts to change them to. Let’s choose pie chart and press okay. And you see that that has changed. We can go back, choose aligned and then that changes as well. Let’s choose an XY scatter and press okay. Now we’ll get a warning that we can not use an XY scatter, bubble or stock chart type with a pivot chart. So that’s the only limitation to choosing a chart, is there’ll be cannot choose these three charts. Press okay, and we can go back. Now we have some more information here. We can switch the row column. So we have the years in our row labels and our regions in our column labels. And we can switch that around by pressing this. As you can see, the Pivot Table has changed and so has our pivot chart. You can press it again to switch it back. Now in the chart layout, in the dropdown arrow here, you have 11 different layouts to choose. We either have the chart title, the axes titles, the legend, and the data labels in different formats. So you can pick and choose from in here, whichever format you like. And some of them work well, others not, but you have the option to have a look. Okay. Another thing that we can do is choose a different chart style. So from these dropdown arrow, you have the multi-colors here. You have the gray look and let’s move that over here. So you can look at the different colors. Now we can choose in there. This is a 3D look. Of course you can choose these different styles here, just depending on what you’re trying to achieve. Personal preferences. I like this style here. And finally, on the far right-hand side, we have the location where we can move the chart. So if you click on there, you have the option to move the chart, it says, choose where you want the chart to be placed. We can create a new sheet or we can move it within one of our existing sheets. Now the pivot is a pivot sheet here, and our data table is a data table sheet there. We can move it to a new sheet and then press okay, and then move it into a brand new sheet and it’s called the chart 5. Now in here, if you go to your Pivot Table and you choose a quarter and you go back, then this changes accordingly. Now we can go back to our analyze and put in our field buttons from in here, and then we can choose our filters from in here. If you wanna move it back, go back to the design, move chart, object in, pivot where we were before. And it moves it back in here. (upbeat music) When we click in our pivot chart under pivot chart tools, we have our layout tab. Now in here, we have the different labels, axes, background, and analysis that we can choose. Now for labels, we have the chart title. The first option is none. Then we can center it overlay title, and then we can center above chat. Under the axes titles, first of all, the primary horizontal axis, which is on the bottom of the chart, we can choose the title below the axis, or we can have none. We can also choose more options in here where we can format it. Go to the vertical axis on the left-hand side of the pivot chart, we can have the rotated view, the vertical title and the horizontal title. And once again, we can go to more primary options down here. In the legend, we can turn it off. We can show it on the right, at the top, left, at the bottom of the chart, we can overlay it at the right, or we can overlay it at the left. And we can choose more options here where we can format it. And the data labels, we can switch them off. We can center them, inside end, inside base and outside end. And more options there. On the data table, we can show data table at the bottom, we can show with legend keys. More options down there. On the axes, the horizontal axis, which is the bottom. We can have none, we can show left to right, we can show axis without labeling, we can show right to left axis. The vertical axis, we can have none, we can show default axis, show axis in thousands. We can show axis in millions, in billions, and show axis with log scale. Let’s go back here and set it up to the left to right and default axis. In the gridlines, we can have minor gridlines, major and minor gridlines. In the vertical gridlines, we can have major gridlines, minor gridlines, and major and minor gridlines. In the plot area, we can have none, we can show the plot area. We also have more plot area options. Now, in here in the analysis, you can choose a trend line. So we can put in that linear trend line, and it gives us the option of which region to choose. Let’s choose Americas, and we’ll get the trend line there. You can have an exponential trend line, a linear forecast trend line, and the two period moving average. In error bars, we can have error bars with standard error. We can have error bars with percentage, and also with a standard deviation. And finally, the chart name, chart 1, we can change it to our own name, regional chart and press okay. You can see this changes here and also in the name box, our chart changes there. So there’s a few different ways where you can lay out your chart to make it look more appealing and have information stand out so people can analyze it quickly. (upbeat music) Now to format our pivot chart, we just have to click in there and we’ll get the pivot chart tools tab. And then we choose the format tab. On the far left hand side, we have the dropdown box where we can choose which part of the pivot chart we can format. So first of all is a chart area. And in here we can use a different shape fils. Okay. So what I’ll do now is I just put in a slight background, like this. We can also change the text from in here. What I’ll use is a slight gray. So you have all these options here where you can change a text in the shape fill and also the different colors from in there. Borders and fields from in there. Okay. It’s got a different variety of options that you can choose. Now, let’s go through our next area, which is the horizontal category axis. Now you see the border there. Okay. So I wanna put in there a text fill to make it a little bit darker. Okay. Now the legend we can put in there a shape fill, like that. The plot area. Now we’re gonna use the same shape fill as we have for our whole area. Okay. Next is our vertical value axis. And in there we can change the way that the text font is. We can put up a little bit darker, just like that. Now the vertical value axis major gridlines, now these are the gridlines here, I usually like to have them a little bit lighter in the background. So you don’t see them that much, and you can choose these different styles. You’re gonna have them as dark as you want so they can stand out. But I like to have them a little bit lighter. So the shape outline, with a white background, which will look nice as well, or you can put a slight gray background. Next is the series Americas. Now in here, you can actually change the color of the column chart. On the shape fill, we can choose different colors, or we can go to the gradient and choose different gradient variations. And you see the live preview. Okay. If you go to more gradients, then you can choose from in here some different options. Now you can do the same thing for Europe, Asia, and Africa. Okay. Now let’s go back to the chat area and the show outline. Let’s put a border in there. So I wanna put a dark border like this. Go back in, the weight, I wanna make it a little bit thicker. I did like that. We’ll go back in. You can actually put dashes if you like. Now, back in here under more lines, under the cap type, I wanna make that round and then round here. So we’ll get the round edges okay. And then around corners. And you can make it thicker like this. Usually have it about five points, and then close. Now there’s another way where you can change your graph. If you click in there and press Control + 1 from your keyboard, it actually brings up the dialog box. So you can change it from in here. You can put in the fills, border color, border style, shadows, glow and soft edges, 3-D format, the size properties and alternative texts. So you’ve got a few options there. Now you can actually click where you want to change, and this dialog box changes as well. So the solid line, we can go back and put in a white line and we change. Let’s click on our axis. So it brings in the format axis. So in here we have the minimum and maximum points that we can choose. Now, if we keep it an order, you’ll be at auto, but say, we want to change it to 1.6 million. So the maximum amount, let’s fix that. Instead of 1.8, let’s put a 1.6 and we’ll see what happens. You see that, it changes like that. So you can have it fixed, or you can have it auto. If it’s a one off graph, you can fix it. But if it gets updated automatically, then keep it at auto. You can also have the major tick marks outside, inside, across. Now these are the marks in here. The same thing, if you click on the bottom there, you’ve got the cross you can choose, or you got the minor tick mark you can have inside. No, you can’t see it there. But if we go in here in the minor tick mark, let’s make it inside, you can see that there. Now if we want to go to our graph, we can choose there and make our color changes, or we can go here on our axis or our labels there. So you can use this option as well. So it’s important to spend some time to make your graph more attractive, because you never know who’s gonna end up looking at it. The more appealing it is, the better it looks on you. (upbeat music) Pivot charts have come a long way since Excel 2007. In 2010, we have more formatting options. First of all, you don’t lose the formatting when the Pivot Table changes. And then you also have the option to your slicers as your filters. Now, one thing you can do is insert XY scatter, Bubble chart, or stock charts from your Pivot Table. But there’s a work around. What we can do is reference the cells outside the Pivot Table. Now to do this, make sure that when you’re in the Pivot Table under options and the dropdown box, if you generate GETPIVOTDATA, it’s switched off just like this. There’s no tick option there. So let’s go outside our Pivot Table and press plus or equals, and then choose row labels. Then grab the row labels, drag all the way down, and then drag it all the way across. So we have that in there. Now, what you can do is Control + Copy if you like, and then right-click and paste the values so you can hard copy them, or you can just keep it like this. So it can be linked to the Pivot Table. Now, what we can do is go to insert and scatter chart from in there. So now we have our scatter chart inserted. So if we go to our Pivot Table here and we filter by regions, our pivot chart changes accordingly and as well, we just want to choose a few other months we can, and that changes as well. We can go back and select all. So this workaround works well if you want to use XY scatter charts, bubble charts, or stock charts. (upbeat music) In chapter 9.5, we created this chart here. And now I wanna save this chart as a template and then use it next time I create a pivot chart. So I don’t have to go again through all the steps to create this beautiful looking chart. So, first of all what we need to do is save this chart as a template, click on the chat and go to design. On the far left hand side, there’s a button here called save as template. Now it brings us to this extension, which is Microsoft, templates, charts. We have to save it in there so we can access it later on. Now, let’s name this to cool column chart. You can name this to whatever you like and press save. Okay, so now let’s go back to our Pivot Table and insert a pivot chart. Like this you can put a column and press okay, and move it up here. Now, what we need to do is go to the change chart type and under templates we have our previously saved template. If you hover over there, you see the name cool column chart and press okay. And it changes it accordingly. It also works on other charts. So instead of a column chart, we can change it to a pie chart and press okay. And it keeps those formats in there as well. (upbeat music) If you click on your pivot chart and then right-click, you have these options here that you can choose. So you can refresh the data. You can cut and paste the pivot chart somewhere else. Now you can use the font there. You can also change the chart type from in here. So you can choose different charts. Another thing you can do is select the data. So it brings up the data here and you can switch the row and column from in there. So you have the Americas now on the x-axis and if you go again, you have the years on the x-axis. Press okay. Right-click again, you can move the chart to a new sheet or to a existing workbook. You can also format the chat area from in here. So you have the option there and you can click anywhere in your chart to change the area that you can format. And another way to format, is to go to format and format selection, and from there you can make changes or you can choose which part you want to make the changes. (upbeat music) We’re gonna set a chart title, and then link that to one of our Pivot Table cells. So every time we filter, then the chart changes as well. So let’s go to our layout and then choose chart title and put it above the chart. And we’ll have the chart title there. We can actually go into a formula box and press equals and then choose the filter there and press okay. So now when we go and choose Q1, it changes to Q1. When we choose Q2, it changes to Q2. Now the only thing is if we have multiple values, it’ll show us multiple items. And then if we put it all, it’ll show as all. But it works well if you wanna show each quarter and take a snapshot and send it over to your manager to have a look at it. (upbeat music) There’s a couple of ways that you can copy a chart. You can click in the current chart and press Control + Copy from your keyboard and then click anywhere else in your workbook and press Control + V. Control + Z to go back. Another way is to click in your pivot chart and then hold the Control key while your mouse is selecting the chart and then move across like this and let go of your mouse. And now let go of your Control key. And you’ve copied the chart in there. And now you can go to design and change the chart type. You can change it to a pie chart. (upbeat music) There’s a quick way to insert a pivot chart. All you need to do is click in your Pivot Table and press the F11 key on your keyboard. And it puts the pivot chart into a new worksheet called chart number three. And from in here, you can make your changes and also your Pivot Table changes accordingly. And if you go back, you can see the changes that you’ve made there. We’re back in our Pivot Table. If we click in here and we’ll press ALT + F1, create a pivot chart on the same page. (upbeat music) we can create a pivot chart directly from our data source. All we need to do is click in our data source and go to the insert tab. Now from the Pivot Table, dropdown arrow, we choose pivot chart, and then we select to put into a new worksheet and press okay. Now we have our empty Pivot Table and pivot chart. And now we can start creating our pivot chart. Now let’s drop in our X-axis into our row labels. Let’s drop in our Y-axis into our column labels, and let’s drop in our values into our values area. So now we’ve created our Pivot Table, as well as our pivot chart all in one go. (upbeat music) You can take the pivot chart and email it to one of your colleagues or your managers and click in your pivot chart and press Control + Copy from your keyboard. And then go to your email Outlook, or whatever email that you’re using, and in your new message, you can just press Control + V and then it gets inserted in there and you can send it to your boss for review. Now let’s get rid of that. Another way you can do it is go into your insert and screenshot and then go to screen clippings. Now, if you choose that, it’ll go to your previous screen. So we’re using the Excel screen, and then from in here, you can actually take a snapshot like this. And then that gets embedded into your email body. And from in here, you can format it whichever way you like, and then email it from there. (upbeat music) We can copy and paste a pivot chart into a PowerPoint presentation, and then make the changes back into the Excel sheet. And then from there, update the PowerPoint. Now to do this, just click in your pivot chart, press Control + Copy. Let’s go into our open presentation and right-click, and then choose the keep source formatting and the link data, and press okay. So in here you can make different changes if you like, let’s go back and close our file here. So what we can also do is edit the data. So next time you open this and you wanna edit the data, you can just press that and it opens up the information. So from in here, we can actually make our choices instead of Q3, we can choose Q2. You can see that changes automatically and also we can change the way this looks, so we can move financial year there and sales regions there. And that changes as well. Or we can put in there some products, and then our pivot chart changes in our PowerPoint presentation. So we can save this, get rid of it. And then we have the updated chart in there for our presentation. (upbeat music) There are a couple of ways to print your pivot chart. If you have your Pivot Table and your pivot chart in one worksheet, and then you can just click in your pivot chart and go to the file, and print. Now in here, you can see that we have the view on our right-hand side. Under settings, we have pre selected chart. So it’ll print this little chart and we can press print and you can print it to your printer or if you choose PDF, you can actually save it as a PDF format. Let’s press print and I’ll show you here, and press okay. And we just reduce this and we’ll see it’s printed into PDF, and you can save it or email it to whoever you like as a PDF format. And let’s get out of this. Now, another way you can print the pivot chart is if you click in your Pivot Table and press F11, then it creates a another chart or to a separate worksheet. Now, when you’re in here, you can go to file, and press print, and you can see here now, the view is a little bit bigger than before. So it’s much better using this format. And from in here, you can print to your printer or to a PDF document. (upbeat music) Sparklines are new in Excel 2010, and what they are are small graphical representations of each data row. So to insert, we’re got to click outside our Pivot Table and go to insert, and sparklines. Now it asks us here our data range. So let’s select the first row and then location is F5. That’s fine, press okay. And now we can just drag it all the way down. So you see there, our graphical presentation for each of our rows, we have our troughs and peaks. If we click in there, we can actually change it to a column chart, and then we can do a light color there. And if we go to the market color, we can actually highlight the high point. You just make it a little bit darker so you can see the high points there. Now we can also, if we choose Q1, you’ll only collect Q1 data. Q2, and then choose all. We’ll see all the data. So it gives us a quick snapshot of our troughs and peaks without having to insert a pivot chart. (upbeat music) There are few tips to follow when making a nice pivot chart. First of all, make sure that you have a title here. What I’ve done is I’ve linked the title to a reference cell here. And what I’ve said is it equals the report filter. So 2012 and I put the and sign and then in brackets I put my title in there. Okay, so if we change these to 2013, then that gets changed automatically. So always have a title in there. And another thing we need to do is sort the pivot chart in descending order or ascending order. But I like descending order because you see the best performer first. So to do that, you go onto your pivot chart, right-click, sort largest to smallest. So we have the largest to smallest there. And the next one is to make sure that we start at zero. Now, this starting point is at 2.4 million. Now we can see here that it seems that Europe is twice the size of Americas, but that’s not the case because the value for Europe is 2.6 million and the value for Americas is 2.5 million. And to fix this problem, you click in your axis, press Control + 1, and then the minimum amount, the fixed change to zero and press okay. And finally, instead of having numbers in your axis, we can actually get rid of them and put some and data labels. Now to insert data labels, just click in your graphs and make sure they’re all selected, right-click and add data labels. So we’ve added the amounts there. Now let’s click on the data labels. We can actually click twice to edit one, or we can click out and go back into edit all of them. Press Control + 1, and in here we can move them wherever we want but let’s put them on the top there. We can also choose the category name there, and we’ll leave it as is. Now we can click on access there and press delete to get rid of that, and also in our gridlines, click and delete. And now we can just sort, right-click and sort largest to smallest. And then when you click in here and we can just make that a little bit darker. And always try to keep your graphs simple. And this is more when you’re working with pivot charts. (upbeat music) What we’ve done here is created three different charts. And with our slicers, we can actually choose which chart to show based on a named range formula that we used here. And then we can also use slicers to change the data if you need the chart chosen. Now, this is a similar concept to chapter 7.11 for the interactive employee photos with slicers. Now, instead of inserting photos, we’re gonna insert pivot charts. So I can go on to the how to section and explain how it’s done. Now first of all, we have to create a table. So number one, two, three, and the charts we’ve named regional sales, orders received, and top five channels. So second is to create a Pivot Table. So we can highlight this and insert a Pivot Table. And let’s put into our existing worksheet just out here on the right. And we’ll want to put in there the row labels tow equal numbers. So grab the numbers of the row labels. And let’s get rid of the grand total just to here. So now that we’re moved to the pivot table here, we need to name the first row, number of cells down. So this will tell us if it’s selection number one, it’ll move one row down. If it’s selection, number two, it’ll move two rows down. If it’s selection number three, it will move three rows down. So to name the range, we need to go into our name box in there and call it number of cells down. And let’s put an underscore and press enter. So if click out of there and click back in, we’ll see that named range. So the next step now is to insert a slicer. To do this we’ll go to the options, insert slicer, and choose a chart. So we have the three different charts. So what we need to do next is to define a name for the starting position. So this is our starting position, and we’re gonna name it, start here. Let’s call it, start here and underscore, okay. The next step is to make this row 230 high. So let’s grab the three different rows that we’re gonna put in our charts, make the height at 230. So the pivot charts can fit in there perfectly. Number six is to insert the pivot charts. So all we can do is go back in here and grab the charts that we made before. So all these charts are from in here. Okay. So we can grab these and copy them instead of redoing it again. Control + Copy, and then we’ll can put them in here. Control + V and escape. Okay, so they’re in here and we just gotta make sure that they are within the boundaries. Okay. So we may need to just adjust that a little bit. Move this there and this in here. Okay. So this should be fine now. So step number seven is define the name for the formula that would drive the pictures. So in here, we need to go to the formula and name manager, and we’re gonna name this, show chart. So let’s go to the new and call it show_chart and underscore. And this will refer to this function here. It will be offset. And then we’re saying, where’s our starting position? Well, we named the range previously and we said it was start here. So we can put in the start here. The next argument is how many cells down? But we’ve named the range, number of cells down, and that was named in the Pivot Table. So we can type that in. Number of cells down, and then the next argument is how many columns to the left or right? Well, we’ll put in the zero and then comma and close bracket and press okay. And then close. So we’ve named that. Next is to copy the pivot chart and paste the picture link. So to copy the pivot chart all we need to do is just go in our cell here and press Control + Copy. Go up here, click in there. We’ve made this a 230 as well. So as big as those, so we’ll go right-click and choose here, link the picture. So we’ll paste in the linked picture from our first chart. Now we could grab any of the three, but we just use the first chart for now. Now the next step is to reference the picture to our offset and named the range. So all we need to do is grab this show chart define name, which we did before and link it to the chart here. So we can actually link named ranges to pictures. So we can say, show, and when we put that, we’ll get the options here so we can double-click the second one and press enter. Okay, so now it’s working, and let’s go to number 10. Is to insert the slicer from the pivot chart and connect them. Okay, so first of all, let’s grab our first slicer and we can move it up here, and we just to make sure it’s working properly. Orders received, regional sales, top five channels. So that’s correct. Now we can go in and grab the slicers that we have here. So these slicers were created from in here, by going on to options and insert slicers. Sales region, the financial year and the salesperson, and press okay. Hold down the Control key, Control + X, and we’ll go in here and press Control + V, escape, okay. So we have our slicers in here. So grab the slicers and put them in there. And all we need to do is connect these slicers to our Pivot Tables. Okay, we can put it like this for now. So right-click Pivot Table connections, and they’re all connected. Just to make sure they’re all connected, right-click, Pivot Table connections all connected. Okay, they’re all connected. So these slicers here are connected to the pivot charts and this slicer here changes the chat type. So if we click 2012, that gets changed. If we click by salesperson that gets changed, and by sales region. Based on what we’ve learned in this chapter, if we put everything together, we can make some interactive charts here, which are very powerful and you can start making some dashboards. So have some fun and let me know what you think about them. (upbeat music) With a pivot chart, you can not create an XY scatter, but I will show you how to do this via a workaround using the index function to get our sum of sales and our sum of costs. And then with a slicer create an option where we select sum of sales and then the graph changes to that. And then also select the cost. And then the graph changes to reflect the cost information. Now first of all what you do is create another Pivot Table, which includes sales and cost in there. And I’ve numbered them one and two. So let’s select that and go to insert, and Pivot Table. Then we’ll go to an existing worksheet, and we can put it in here and press okay. So I’m gonna drop into the field in the row labels and the number in the values area. And what I’ll do now is from in here, go to insert slicer and insert the field name in there. So we have created our slicer, and let’s bring it up here. Now, all we need to do is create an index function where we get the sales information or the cost information, depending on the column that we choose. So if it’s column one, it’ll be sales, if it’s column two, it’ll be cost. So let’s press index, and then the array is gonna be in here, the sales and costs. Press F4 to lock the area in there. The row number, we’re not gonna have a row number. Now the column number will be the link to the Pivot Table selection. So let’s move this up here and press F4 to lock it in there and enter. So now if I double-click in here and press costs, that means it’s looking at column two and returning all the values in column two, from our array. If I press sales, it’s returning all the values from column one in our array. So now we can create a scatter graph from here, just go to the insert and scatter, like this. And we just put in there. So we choose the cost. We have the cost scatter graph, which is a sales. We’ll get our sales scatter graph. (upbeat music) In this chapter we’re gonna create a P&L Pivot Table report with graphs. Now we have our Pivot Table here that we created in our chapter eight. And what we’ve done here was eventually put in some pivot charts for the expenses at the bottom here. And you can see the month going across from left to right. And then we have another pivot chart for the revenues going from left to right. And then we’ve added in our slicers in there for the years. So each time we change the slicer, so let’s choose to 2013, the pivot chart will change and so will the Pivot Table here. So press that, you see that changes, and then 2014, that changes as well. So it gives us a nice graphical representation of where our revenues and expenses are for each of the months. Now let’s go to our data source and I’ll show you how you can create these. So this is our Pivot Table that we created in chapter eight. And now all you need to do is just right-click in there and go to expand collapse, and collapse entire field, because we don’t wanna see every little detail there. Okay. Now let’s go to the well data source. And in here we have our accounting P&L report. Let’s create a Pivot Table, go to insert, and Pivot Table, and let’s go to a new worksheet. Now in the row labels, we’re gonna add in the month. In the column labels, we’re gonna add in the P&L type and the item and the values we’re gonna add in the actual in there. And in the column labels, we only wanna see the expenses. So from the dropdown arrow, let’s choose only the expenses and press okay. Let’s minimize this a little bit. So now that we have our Pivot Table, we can create our pivot chart because we know that anything in the row labels will be in the X-axis. So we’ll go on the bottom, and anything on the column label will be on the Y-axis. So let’s go to options and pivot chart. And in here, we’re gonna create a stack column chart and press okay. So here is our chart here and now let’s right-click in the filters there and go to hide all field buttons on chart. And then let’s just make this a little bit bigger. So we have our chart in there. Now let’s format this a little bit better. Click on the Y-axis and from the home button, we can just make that gray, press Control + 1, and the number, let’s just put in there a separator with zero decimal places. Now click in the gridlines there and press Control + 1 again. And the line color will be a solid line, but you’ll just go a light gray. Now in the months here and choose from in here, just a blue color there. Now let’s go on the pivot chart tools and let’s choose in here the layout and gridlines, primary vertical gridlines. And let’s put in some major gridlines there, so we can separate the months. So in other words, click on our pivot chart, press Control + X, and let’s go back to our pivot. And down here let’s press Control + V. Okay, so we’re gonna add that in. So we have our expense graph there and we’ll just align and so we can put in the months next to the months in there, just like that. And we’ll just probably move it into the left there. Finally, let’s get rid of the border. Press Control + 1, border color, no line. So it just is like this. Okay, so we’re happy with this. We’re gonna use the same format for the revenue pivot chart. Now click in the graph, go to design and save the template as. Now in here, it automatically takes you to the Microsoft templates and charts directory. You can name this chart to whatever you like. Let’s call it P&L Pivot Table, and press enter. Now the next step is to create a second Pivot Table for the revenue, and from there, we’re gonna create a pivot chart. So go to insert, and Pivot Table, a new worksheet. And we’re gonna drop in the months in a row labels, the P&L type and the column labels and the item in the column labels and the actuals in the value area. Just like we had before. Now, the only anything here, we want to show the revenue annually. So let’s just take the revenue like that. Let’s go to pivot chart, and let’s put in a clustered column and press okay. Now, whilst we’re in here, we can go to change chart type. And then from the templates folder, we can hover across to our P&L Pivot Table that we just saved previously, click on that and press okay. And you can see that changes accordingly. So now we can grab that, press Control + X, go to our pivot, scroll all the way up and then Control + V to include it in there. Now, one thing we gotta do is click in the months and press delete ’cause we’ve done our saving. And then we can just double-click in the home tab, just to minimize that. We can actually minimize it from in here. Just so we can have a bit more room. Now let’s move this across. So we’re gonna align that into the months. Just like we have before that. Now in here, we can add in right-click and insert, and press F4, again, just to have a bit more space. Let’s click in our Pivot Table, go to options and then insert slicer. And let’s insert that year slicer and press okay. And we can right-click slicer settings, get rid of the header. From the options tab, let’s move the columns up to three. Now from here, we can just move it like this, and we can change the color if we like. And we can put it up here, and we can just delete this so we can move it up a bit. And from in here, we can bring this up, just so it can fit into the same page. And finally, let’s right-click in our slicer and go to Pivot Table connections. And what we’ll need to do is connect the different Pivot Tables to the slicer. So by clicking the Pivot Table number two in sheet one, and also the Pivot Table number three in sheet two, we’re connecting the Pivot Tables and respective pivot charts to the slicer. Press okay. So now when we press 2012, the slicer changes, the pivot charts change and the Pivot Table changes accordingly. 2013 the same, and 2014 the same. Finally, we’ll forgot just to make this a different chart. Right-click, change the chart type, and let’s go to the first type there. It just looks a little bit neater that way. Do another test, and there we go. So here’s a great example of how you can use a Pivot Table with different pivot charts and put it all into one page and then control that with a slicer to get some graphical analytics with your Pivot Table. (upbeat music) In this chapter, we’ve created a pivot chart dashboard. We’ve done this by creating three different Pivot Tables, one for our top five channel partner, which you can see in here. And then we’ve created the pivot chart and cut and pasted it into here. The same thing for the number of sales group. We create another Pivot Table and a pivot chart. We’ve cut it out in, put it in here. And the same thing for the sales and cost per month. We have a separate Pivot Table. We create a pivot chart and then we’ve placed it in here. What we’ve also done is inserted four different slicers and we’ve connected them. And by choosing the different years the pivot charts change automatically. So you get a nice looking dashboard with lots of metrics. You can choose for different months. You can also choose the different regions. Let’s highlight everything again. And you can also choose the different sales ranges. With this dashboard, you are sure to wow your boss and get noticed. And I’ll show you how to do this in a few steps. So this is our data set that we’ve been using. And we have all the different information here for the channel partners, sales, the different regions, salesperson, and so forth. So now we’re gonna create three different Pivot Tables. And from there we’re gonna create three separate pivot charts. One for the top five channel partners, the next one for the different sales groups, and the last one for sales and costs. So let’s go to the first one and create the top five channel partners. Let’s go to insert Pivot Table and put into a new worksheet. So let’s get our channel partners and put into that row labels. We’ll get our sales and drop it into the values. So we have our Pivot Table here. Now, first of all, let’s right-click in the values and we’re sort it from largest to smallest. And from the dropdown box, let’s go to value filters and we’ll do the top five. So let’s put in there top five items and press okay. So we have our top five channel partners. Now let’s go to options and pivot chart and insert a pivot chart from in here. Let’s choose a bar and press okay. Now let’s just make some changes. Let’s get rid of these buttons by right-clicking in there. And let’s get rid of the total there. Click and press delete. Let’s got a design and let’s choose this here with a white outline. And click on the gridlines and press delete. Now let’s click on the Y-axis and go to home. And let’s put in a dark font in there. And from in here, we can delete that because we don’t want it. Now, let’s click once in your graph and right-click, and let’s add some data labels in there. Now we can color them in. Let’s put it into a blue there and then press Control + 1. In the number, let’s put in 1000 Separator and zero decimal places. In the title, just double-click in there and change the name to top five channels partners. And double-click to highlight, and let’s put it into a dark gray there. Okay, now let’s right-click in the chart and then let’s fill it in with a light gray background. And again, within the graph click on there, right-click, and once again, let’s fill it with a light gray. Now let’s click on the edges and then press Control + 1. And the border color, we do a solid line and we’ll have a white border, and the border style, we can just put in number five and let’s make round corners in here, and press okay. So you see our chart is taking shape. Now we’re gonna use this similar format for the other chart. So all we can do now to save this template, and then when we create the next pivot chart, we can apply these different formats. So we don’t have to go through all the steps again. So once you click on your chart, go to design and save template as. You get this directory here, and it goes to Microsoft templates and charts. And in here, you can save your chart. And let’s call it dashboard chart, and press save. Okay, so we’ve created our first chat. While it’s clicked, press Control + X, go to our dashboard, click anywhere in there, press Control + V. So this is our first chart in there. And let’s just put it just like that, and we can reorganize that later. So let’s go to our data table and create a second Pivot Table and pivot chart, which is gonna be sales groups. So go to insert, Pivot Table, new worksheet. In here, we’re gonna put in the sales in our row labels, and from in here right-click and press group. And once you group that into ranges starting from 10,000, all the way to 100,000. And then the increase will be 10,000, we’ll leave like that and press okay. Now again, go to sales and drop it into the values area. And because we’ve grouped the sales, we automatically get a count of sales. And leave it like that, that’s fine because that’s what we want to use. Now let’s include in there a pivot chart. Click the pivot chart, and we’re gonna use a column, and press okay. Now let’s go to the change chart type. And in our templates, let’s get the previous template that we created, which is this one here called the dashboard chart, click on that and press okay. So you see, we get the format as we had before, but now we can just right-click in there and again, change the chart type. And let’s put it into a column and press okay. So we’ve got the same format, but we have the different chart type. Now in here, just double-click and rename this to the number of sales per group. You can name it whatever you like. And let’s put that in gray. Okay let’s click on the chat, press Control + X, and go to a dashboard. Click anywhere in here, press Control + V. Or we can just bring it all the way up here. And you see now we have our second pivot chart in there. Let’s go back to our data table. And we’re gonna create a final pivot chart for sales and costs. Go to insert Pivot Table and press okay. In our row labels, we’re gonna put the financial year. and the sales month. In the values we’re gonna put in there, the sales. And then the costs. Now, we get a count of sales because before we grouped our sales. So once we group our sales, the next time we create a Pivot Table, we get a count of sales. But that’s okay. From the dropdown arrow, go to value field settings and choose sum. Let’s go to our pivot chart and insert a column chart and press okay. And let’s get rid of the buttons there. Now we’re not gonna use the same chart style as before ’cause if we do that, it’ll mess things up and it won’t look good. So let’s go back and I’ll show you how it’s done, and press okay. It just doesn’t make it nice. So let’s press Control + Z and get out of that. And now we’re just gonna manually make some updates here. So we have our sales and our cost here. I want to put our costs as a line on the secondary axis here on the right-hand side. So to do that, we’ve clicked in our sum of costs, which are in red, press Control + 1, and then plot series on, put secondary axis, and press close and then change chart type. And let’s put a line and press okay. So now we have the two charts on different axes. So the sales are in blue and they’re depicted on the left hand side axis here. So let’s put it in our blue color there to distinguish that. Like this, press Control + 1, number, and we can just put like that. Now on the right-hand side, we have our sum of costs. So let’s click on that. And then let’s put in a red color there, and again, Control + 1 and let’s format the number. Now let’s click on layout and go to axis titles. The primary vertical access, let’s choose that and we can put in there sales. We can right-click in there and just put it in a blue color. Now let’s go again to the axis titles and go to the secondary vertical axis titles just like that. And put in that cost just to distinguish them. And let’s put that in red, let’s click in there and press Control + 1, and we can move the legend to the bottom and press close. Now let’s click on our grids there, and we can delete that. Let’s click in our axis there and put in a blue color. And now let’s click in our line and press Control + 1. And the line color, let’s put it into this light red color, and then the marker options, let’s put in a circle, and the marker fill, again we just put it in like that into a light red color and press okay. Let’s go on to our layout and put in a chart title, choose above chart, then double-click in there. We’re gonna call that sales and costs per month. And double-click in there and we’ll put into a gray color. Okay, now let’s put in a gray background for our graph. Just click anywhere there, right-click and then in here, we choose a slight gray, then click within the graph. And you can press F4 and it’ll repeat the last action. So we have our graph there and now one last step is to put in a border. Click on the border, press Control + 1, the border color, we put in a white color, and the border style, we’ll make it a bit thick, number five and then put round corners and press close. So we have our chart there. And now all we gotta do is just click on that, press Control + X and Control + V, and we have it there. Or we can just resize that just to make it a little bit bigger. Okay, so now let’s just double-click in the home tab just to get a bit more space so we can see that. So we have our three different pivot charts there that we created from the three separate Pivot Tables. Now, the final thing we need to do is insert slicers and then connect them. So every time we change the slicer, the three pivot charts are in sync. So to do that, we can simply click on any chart. So let’s go analyze and insert slicer, and let’s put in there the financial year sales month, the sales region, and a sales and press okay. So we have our four different slicers there. So let’s grab the financial year and bring it up here and we’ll just make some adjustments to one. Let’s put it into three different columns and then let’s make it dark. And we can move it like this, right-click and slicer settings. Get rid of the display header. Let’s make the height for the buttons a little bit bigger. So we have one slicer there. Let’s grab our sales month. And again, right-click just to get rid of the header. And from the options, let’s put into three different columns, that shows the different quarters. And then we can just resize it in here, just like that. And then once again, let’s make the buttons a little bit bigger, and then we can put in there a dark color. The next one are the sales regions. Let’s grab it in here, get rid of the display header. And then let’s put into two different columns and resize that accordingly. And then again, let’s make this a little bit, the buttons little bit bigger. We can put in a different color if we like, just to distinguish that. And finally we have there sales. Now they’re grouped into the different ranges. Let’s get rid of the header. And then let’s put it into separate groups. Then again, resize this and we can make it a little bit bigger again. Let’s drop it into two columns just so we can see that better. Okay, all the way to the bottom there. And then the color, let’s choose that. Let’s click on the different slicers, press Control key and click on all of them just to align them. Go to align, we can say align center. Now we need to connect the slicers because if we choose one slicer, it’s only gonna change the bottom one, because that’s a chart that we chose to insert the slicer. So let’s right-click in each of the slicers and go to Pivot Table connections. And let’s pick on the empty boxes. So what we’re doing here is we’re saying that Pivot Table number three in sheet two, and Pivot Table number two in sheet one have been connected. Press okay. The same thing for all of them. If we choose 2012, the chart changes 2013, and 2014. The same thing for the months. Let’s highlight all of them like that. And then we have the different regions, and also we have the different sales ranges there as well. Now you can see there, we’ve got the different sales ranges. If we go to our first sheet, we can see the different size ranges. So as we choose that, it changes the Pivot Table accordingly. So this gets updated even though you don’t see it, it’s another sheet, it gets filtered accordingly. Let’s go back in here. Now let’s highlight everything just by holding down the mouse and selecting it all. So you can see we’ve created a pretty impressive dashboard in just a few steps. And I’m sure that with this dashboard you’re gonna get noticed. By the next round of promotions, I’m sure that your name will be mentioned. (upbeat music) In Excel 2010, you can add the new conditional formatting options like data bars, color scales and icon sets. The conditional formatting is embedded within the Pivot Table structure. So if you update and refresh the Pivot Table, then so does the conditional formatting. And to insert conditional format, you gotta click anywhere in your Pivot Table, and then from the home tab, choose conditional formatting. And let’s choose highlight cells rules. And we choose greater than. So in here we get a dialog box, and we can choose the amount to put in there. So let’s say anything greater than 600,000. Now we can format it with a light red fill, with dark red text, and you got a few other options there. Now we can also custom format. Now we get the format cells dialog box and under fill, we can choose the different color to format with. And let’s choose a red and press okay. And then, okay. Now we get this dropdown box here that says apply formatting rule to. We can choose selected cells. We can choose all cells showing sum of values. If you choose that, it’ll also highlight the sub-totals and grand totals. And the third option is all sales showing sum of sales, and also the values that are in the row and column labels. Now this third option is not gonna highlight any sub-totals or grand totals. So most of the time you’re gonna choose the third option. So we have the values there that are more than 600,000, and to make changes to this conditional format, we’ll go back into their conditional formatting option and we can choose clear rules, and from in here, clear rules from this Pivot Table, we can just click on that. Or we can go to manage rules so we can edit the rule. We can change the dollar value from in here. We can also change where the rule applies to. Let’s cancel out of there. We can create a new rule or we can actually delete a rule from in here. Let’s press okay, just to get out of there. So with conditional formatting, it gives you the option to highlight the values that will make your analysis much easier to do. (upbeat music) To highlight cell rules based on their values, you would actually click in the values within your Pivot Table. You need to go to the home tab and under conditional formatting, choose highlight cells rules. And from in here, you got four different options. Greater than, less than, between and equal to. Now, let’s choose the between option there. And we want to format the cells that are between 400,000 and 500,000. And we’ll use a light red fill with dark red text, that’s available to us. And then we press okay. Now from the dropdown arrow here, we choose the last option. So it shows us the two values that are between that range. So let’s go to conditional formatting and manage rules. So in here it says, applies to. So it applies to the sum of sales that are within the sales quarter and financial year. So if we take out the sales quarter and the financial year, then this conditional format will not work. So if you change your column and row label fields, then you’ve got to reapply the conditional formatting for those new fields. (upbeat music) We can actually highlight cell rules based on text labels. Now we have our quarters here in our row labels. Now let’s highlight all of them and then go to the home tab and conditional formatting. Highlight cell rules. Now because we’ve highlighted the text, then it gives us the option to highlight text that contains. So in here let’s highlight texts that contains Q1 and press okay. And then we can go back and highlight again, texts that contains Q3, press okay, and go back there. So it gives us the option to highlight row label or column label text items. (upbeat music) We can also highlight cell rules based on date labels. Now in our Pivot Table, we have our order date dates. We can have any dates that could relate to when a payment is due or when an invoice from a customer is meant to be paid. So we can put a conditional format that’ll show us which dates relate to a particular month. Now to do that, we need to highlight in our Pivot Table and select all the dates. Now we’ll go to the home tab and conditional formatting, highlight cells rules, and then choose a date occurring. And in here you have the option to choose the different dates. Now I wanna choose this month and we’ll want to put it in here in a green fill with dark green text, and press okay. Scroll down all the way. You can see that these three dates are due to be paid this month. And so that you open this Pivot Table on a future date, then this conditional format will be refreshed automatically and apply to your current date’s values. (upbeat music) We can use conditional formatting to highlight the top and bottom cell values. Now let’s click in our Pivot Table anywhere in our values and go to the home tab and conditional formatting, and choose a top bottom rules. And let’s start by choosing the top 10 items. And instead of the 10 items, you can actually choose a top five and then we’ll keep it with this formatting and press okay. Now from this formatting options, we select the last option. So we can see all the values except for the sub-totals and grand totals. So we have our top five items there for our three years of financial data. Let’s go back and use conditional formatting, and we can clear the rule by choosing the last option, clear rules from this Pivot Table. And then we’ll go back here and let’s create another rule. Let’s choose the top 10%. So in here we can choose a different percentage. For example, the top 25% of sales for the three years, press okay. And then from this dropdown formatting rule, let’s choose the last option. So it shows us here the top 25% values from our three years. To go back, and we can go and clear the rule. Let’s apply another rule here, above average. So in here, based on our selection, it’s gonna give us the values which are above the average and press okay. And then let’s apply it to everywhere. So what it’s done, it just calculated the average over the three years and the values which are above that average will be highlighted in red. Okay, let’s go back and clear the rules. Now we’ve got the option to do the bottom 10 items or the bottom 10% or the below average. And let’s go to the more rules in here, and let’s choose the apply rule to, let’s choose the third option once again. And in here, let’s choose the top. We can actually choose the bottom as well. So let’s choose the bottom one item for each column group. And we’re gonna format that in red and press okay. So this is a one column group and it’s highlighting the last value. That’s another column group. So is that, and so is this. So it’s showing us the bottom value based on that. Let’s go back and clear this rule. And then finally let’s go the more rules. And in here, let’s choose the third option and bottom one and each row group, and let’s format it in red and press okay and okay. So what it shows us here is that the bottom value from this group, the bottom value from the selection and the bottom value from this selection. And it does the same thing for each of the different regions. So the top and bottom rules in conditional formatting are a great feature and your data really does stand out. (upbeat music) Data bars, color scales and icon sets are new in Excel 2010. And they’re a quality feature on the conditional formatting. Now let’s highlight our Pivot Table values here and go to the home tab and conditional formatting, and then choose data bars. And here you got the option of a gradient fill in different colors. And as I’m scrolling, you can see the live preview in the Pivot Table. And you’ve got the solid fill as well. So here it highlights the values automatically by highest to lowest. Let’s go to the more rules option, and let’s apply this rule to the last option, which means all the values except the sub-totals and grand totals. And here will be only show the bar. If we press okay, you can see that the values go and we can see the bar only. And let’s go back to your conditional formatting, manage rules and choose Pivot Table two, and double-click in there just so we can make some changes. Now in here, we can actually choose lowest value. We can actually put in a number, a percent, a formula, a percentile or automatic. Now let’s put in a percent in there. And let’s put 50% and the maximum we’ll put 50%. And then we can have a solid fill or a gradient fill, we can choose a color in here. And let’s put in there a light blue. We can have a border or a solid border, and then the color of the border as well. And in the bar direction we can go left to right, and you’ll see the preview here for right to left. Just keep it in context. And you’ve got some options for negative values and axes. Let’s untick the show bar only ’cause we wanna see the values and then press okay and okay. So we’ll see the values there. So in here it’s highlighted the top 50% in a blue color and the bottom 50% in a blank background. Now let’s press Control + Z to go back. And let’s go back to conditional formatting and choose color scales. So in here you have the different scales here. And you can see automatically that the lowest value is 599 and that’s highlighted in red. Choose the second option. The lowest amount is in green and the highest is in red. And you’ve got these different options there. Now this is good for resourcing or popularity scores. And let’s go to the more rules here, and the format style can use a two color scale or a three color scale. And then once again, we can choose the lowest value. The mid point and the maximum there. And we can leave it like this. The lowest value will be in red. The mid point, the 50 percentile mark, will be in yellow and the highest value will be in green. And press okay. And we can see that there. We can press Control + Z to go back. And then finally we have the icon sets. Now these are good for when you have some budget values and you wanna see whether you’ve achieved your values or you have certain scores, or if you have a project and to indicate whether you have any risks or opportunities. So you got a lot of different ways where you can highlight the numbers. Now, under more rules we can actually choose to show the icons only instead of the numbers. And in here, we’ve got the option of the different icons to choose as we saw previously. Now under here, we can actually change our values. So it says here, give us a green when the value is more than or equal to 67%. Now we can change this percent to a number, to a formula or to a percentile. Now it says here, when it’s between 67 and 33%, then it’ll give us an orange. And when it’s less than 33%, give us a red color. So we can change the as well and even change the numbers. So we can say 50, and then when it’s 50, give us a red. So anything that’s below 50 will be a red, and let’s press okay, and you see that. And we can go back and just do one more thing under manage rules. Double-click in there and say that we had a budget. So anything that’s over 800,000, we get a green mark because our budget was 800,000 per month. So anything above 800,000 is green, anything less is red. Now we can do this by saying, first of all, number bigger than or equals to 800,000 is green. If it’s less than 800,000 and zero number, then it’s a red. So let’s press okay and okay. And quickly here, we can see that all the values that did not meet our budget are in red, and the ones that do are in green. So these data bars, color scales and icon sets are fantastic if you want to quickly show and highlight relevant numbers. And your numbers really do stand out, which makes your analysis that much easier to do. (upbeat music) In our Pivot Table we have all our sales people and we have their sales per year and per quarter. And we’ll want to give them a bonus if they’ve earned more than $700,000 of sales in one quarter. Now, first of all, we need to highlight those people so we can identify them and then we can give them a bonus. Now to do this, we can insert a conditional format, which is format cells that contain. Now from the home tab, we’ll go to conditional formatting and we can highlight cells rules that are greater than. But instead of going there, we’re gonna go to create a new rule. Now we want to apply the last rule, which means all the cells apart from the sub-totals and grand totals, and then we’ll choose the format only cells that contain. And in here, we’ll keep it at cell value and then we’ll choose here greater than or equal to. And in here, we’re gonna reference a cell. We put in here at 700,000, press enter and then format. We can choose a green color and press okay, and then okay. So automatically it shows us the salespeople that have earned more than $700,000 of sale in one quarter. I said that this metric changes, we can say anything that’s bigger than 750,000. Then the conditional formatting in the Pivot Table gets updated automatically. (upbeat music) In Pivot Table, we have our list of channel partners. And there are sales from 2012, all the way to 2014. And what we wanna do is give our top three channel partners per year an award so they can go away on a trip. Now to do this, we can actually click in our Pivot Table and go to conditional formatting. And on the top bottom rows, we can choose the top items there. But we can also go under new rules and then the apply rule to will be the last option. So show all values except grand totals or sub-totals. And then choose the format only top or bottom red values. Now we’re gonna choose the top three, and therefore all values we’re gonna change that, we wanna choose each row group. So what that means that it’ll show us a top three in each year. And it will highlight it in the color that we choose. Let’s just choose a green, and press okay, and then okay. As you can see there, we have the colored. You go all the way down. You can quickly highlight and see which were the top three channel partners for each year. And we can send them a trip and thank them for their contribution over the last few years. (upbeat music) We have our salespeople and their respective sales per year. And what we wanna do is see the salespeople that have been performing above average for three consecutive years. Now those salespeople will get a promotion. To do this, we click in our conditional formatting. We can actually choose the top bottom rules and choose above average from here, but let’s go to the new rule. Let’s choose the last option. So we can highlight the values except the grand totals and sub-totals. And from in here, we choose the format only values that are above or below average. Now let’s choose above average and then we’re gonna select the all values there. So what it’s gonna do is get the average for all the values, and then whoever is above that average will get highlighted in the color that we select. Now let’s choose a green, and press okay, and then okay here. So let’s have a look here. If we highlight everything, and on the bottom status bar, we’ll say the average is 2.672. If you don’t have this just right-click, and can you can click it into action there. So 2.672. So any sales that are more than 2.672, will get highlighted in green, and that’s evident there. So the only sales manager that has exceeded expectations has been Ian Wright. So he’ll receive a big promotion in 2015. (upbeat music) What we’re having our Pivot Table are our 2013 sales and our 2014 sales. And we’ll want to compare to say where that our 2014 sales were bigger than the previous year per month. So to do this, we’ve gotta highlight the 2014 column. Go to conditional formatting and then choose new rules. For the apply rule to, we’ll keep it to selected cells because we just want to conditionally format the selected cells. And then the rule type we choose the use a formula to determine which cells to format. Now in our formula here, we’re gonna put 2014 is bigger than 2013. If that’s true, then it’ll highlight in green. And then the next rule would be is 2014 for February, bigger than 2013 for February? If that’s true, highlight in green, if not, do not highlight. So first of all, let’s click in C3 and then we’re gonna press the F4 button three times, just so we can get rid of the absolute reference. Because we need to apply the argument for each row. So if we had the dollar signs or the absolute reference, then it’ll only have this argument here for row three and not the rest. Okay, so let’s do bigger than, and then B3 and again, press the F4 sign to get rid of the absolute reference. And then we press that and press format in green and press okay and then press okay. So can see here quickly that we have January, July, September, October and November months, that were bigger than the previous year’s totals. And let’s go back to conditional formatting to manage rules. And we can see this under the Pivot Table that the rule applies to the selection, which is correct. And the formula is C3 is bigger than B3. Because we don’t have the dollar signs or absolute reference it means that you have to go into each row and calculate that argument and return back the true or false into the 2014 column. If it’s true, it’ll give us green. If not, it’ll be blank. (upbeat music) In chapter 10.10, we selected the 2014 values there. And we said is 2014 bigger than 2013? If yes, then highlight in green, if not, then don’t highlight. Now can see this by going in to the conditional formatting under manage rules. And we can see if we double-click there, that we’ve applied the rules to these selected cells. And this is the formula, C3 is bigger than B3, and press okay. Now what we can do is actually take out the sales month and drop in some other fields. And this conditional formatting will still apply to that. Let’s have a look. Take that out and bring in customer. You see that works fine there. Send people products, salesperson, sales region, we’re can can see the sales quarters. And then the channel partners. We’ll scroll all the way down. We’ll see whether it was highlighted green, means that 2014 was bigger than 2013. So when you apply the rules to the selected cells, then you can expand the conditional formatting rule to other fields. So what it does is it gives you more flexibility to analyze with more fields. (upbeat music) We had the 2013 and 2014 sales, and the months here as well. And we want to highlight the top five sales for this. And then what we want to do is take out the sales month and drop in the customers and keep the conditional formatting alive. Now to do this, we highlight in our values there, and go to conditional formatting, new rule, and we selected the second option. All cells showing sum of sales values. So what we’re gonna do is keep the conditional formatting for the values live every time that we chop and change our fields. Now let’s put in our rule and we’re just gonna say our top five and then format. And let’s put it in that color there and press okay. So we have our sales month there and let’s take that out and put in our customer, you see that’s highlighted. Our products, our salesperson, our sales region, our sales quarter, and then our channel partners. So we scroll down, we get our top five channel partners. So if you choose the all cells showing values, then you can apply that conditional formatting to one field. You can chop and change that field. And the conditional formatting will still apply to the new field. (upbeat music) We’re gonna create a conditional format for our values here that says, highlight the top X% of values. And we’re gonna control that conditional format with some slicers. So as we choose their percentage on the slicers that the conditional format will get changed as well. Now let’s create a Pivot Table. Let’s highlight the percentage list that we created here. Go to insert, and Pivot Table and existing location, and we can just put it there for now. Now what we’re gonna do is throw in their percentage into our row labels. Our grand total, we can get rid of that. And what we’re gonna do is reference this first cell here to our conditional formatting rule. Now, what we’re gonna do is insert some slicers, go to insert, and percentage slicers, and then we can just add some more columns. And we can just put it there. Change the color. Let’s click in our Pivot Table here and go to conditional formatting, new rule. And let’s choose all sales, showing sum of sales value, and then the format our cells based on values. And let’s choose the three color scale. The loss value we’ll have a 0%. The mid point will be a 50 percentile, and the maximum will be a percentage. And we’re gonna reference this to the first cell here, and press enter. Now the color, we’re gonna change to green and red, and press okay. So now as we press 50, our sale reference is here. So it’ll show the 50% on our maximum value. And then we would go 55, 60, 65, 70, 75, 80, 85, 90, and then 95. So what is showing here is the top 95% of the values as you can see here. So the top two or three values there are highlighted in red. The midpoint is in yellow and the low point is in green. So you can do some pretty funky stuff with slicers and conditional formatting just by referencing the selection chosen by the slicer back to your conditional formatting rules. (upbeat music) We can show texts in the values area of the Pivot Table with a bit of conditional formatting magic. Now, to do this, we need to set up a couple of rules. Now, what I’ve done here is I’ve added in a new column called region code, and I’ve coded the regions as Africa being number one, Americas being number two, Asia being number three and Europe being number four. Now also each row of data relates to a unique date. So I’ve got one for every two days. I’ve got a unique transaction. Okay, what I’ve done now is I’ve gone to our Pivot Table here and I’ve included our order dates on the left-hand side and our products on the top. And then what I’ve done is I put in the max of region. So what that means is for each region I get the maximum value. So obviously the maximum value will be a one for Africa, a two for Americas, a three for Asia, and a number four for Europe. So that’s the second step there. Now third step is to do a conditional format where we’re saying that if the value equals a number one, then show me Africa. If the value equals number two, show me Americas and so on. Now to do this, we’re gonna click in our Pivot Table. So let’s start on the top left-hand corner of our values being cell B5. Go to conditional formatting, put a new rule and then select the third option here. So we can see all our values. Now let’s use a formula to determine which cells to format. So all we’re saying is B5 and let’s press F4 three times. So it’s not an absolute reference. And then we’ll say if B5 equals one, then let’s go to the format area and under number, let’s choose the custom. And in here, under type let’s get rid of that. And let’s put in brackets, if it equals one, close brackets, then Africa, and then let’s put in their general. Okay, so that’s a trick there, and press okay. Now we can also format this in terms of a fill color. So let’s put in a fill of a light color like this, and then press okay. So now you see all the number ones have changed to Africa. Let’s do the next rule, new rule. We’ll say again the same thing. If it equals to two this time, and let’s format. And in here I’ll paste what I had before and I just changed the values. So number two equals Americas. And then we’ll put in a color like this and press okay, and okay. You see that’s changed there. Let’s do the next one. So equals three will be Asia. Asia, and then we’ll fill with this. Like that. You see that, and then finally, we’ll do the rule for number four. Equals four, let’s format and let’s paste the rule. This changes number four and it’ll be Europe. And then we could fill it in with this color there. And okay, so there you go. Now we can see for each transaction that in which region it belong to for all the different products. (upbeat music) So we have our order date in our row labels and our products going across, and I’m gonna drop in our sales in there and want to get the count of the sales. So press okay there. Okay, so we have different counts there in our products and our order dates. And now we want to highlight the blank cells. So if there’s any blank cells, put that in red so they can stand out. So just click anywhere in our values. Go to conditional formatting, new rule, and then apply a rule to the all cells showing count of sales values for order dates and products. So that means it’s gonna show it for all the values except the sub-totals. Now choose the format only cells that contain. Now from the dropdown box, choose blanks, and under format, choose any color you want. Let’s choose a red here and press okay, and then press okay. So it highlights everything that doesn’t contain a value. So you can quickly see which dates don’t include any values. (upbeat music) In this chapter, we’re gonna create an accounts receivable ageing report, and it’s gonna show us when the receivables were meant to be paid and how long they’ve be an outstanding. We have our receivables due date in here, and we have the actual receivable date in the next column here. And we can create a matrix report. Simply click in the data source, go to insert Pivot Table and go to new. On the row labels, we’re gonna include the receivables due dates, on the column labels we’re gonna put in there receivable actual date. We click in the date and we’re gonna group that into the months and the year. So right-click, press group, and then choose months and years and press okay. Now, as soon as we’ve done that, a new field has been created called years. Now we do the same thing for the receivable actual date. Let’s go on out column area, right-click and group. Let’s choose years and press okay. And you can see there years 2 has been included into our field list and also in the column labels area. And let’s get out of here. And in the row labels, we have the original due date and we just wanna see 2012. So let’s just choose 2012. And in the grand total, click in there, right-click and remove grand total. And let’s get rid of the gridlines. Let’s right-click and show field list. And in the values area, we’re gonna drop in our sales. So grab the sales and drop it in there. So we have our matrix-looking the Pivot Table. So in the values area, let’s right-click and show values as percentage of row total. Let’s just the center this like that. Okay, now we have zero in there, but I wanna get rid of it. so we can get rid of those zeros by using conditional format. So let’s go to conditional formatting and go to new rules, and let’s choose the third option there. And this will apply the conditional format to the values and not the sub-totals. And then in here we choose format cells that contain, cell value equal to and in here let’s put a zero. Now, the format we’re gonna put in there a color of the white, because the background is white, it’s gonna get rid of the zeros, and press okay. So one thing is just to get rid of the grand total down here, go to design, grand totals off for rows and columns. So what it says here is that receivables that were due to be paid in February, 2012, 20% of them were paid during that month. 31% were paid in March, 4% in April, 35% in May and 8% in June. And if you select all these, you see the sum is at 100%. So we can see that the ageing is pretty bad because it lacks about three to four months. And we’ll get the same trend here all the way down for the different months. Now, what we’re gonna do is highlight the percentages that were received in the particular month. So for February receivables that were received in February, we’re gonna highlight in green. For March receivables that were actually paid in March, we’re gonna highlight in green and so forth. So we’re gonna highlight the receivables that were received on the actual due date. Now for that we’ll need to do some conditional formatting. Let’s go to the home tab and press conditional format, and create a new rule. Let’s choose the third option there, just so we can highlight all the values except the sub-totals. And then let’s use that formula to determine which cells to format. And in here, we’re gonna put a if formula. So we’re gonna say if February equals February, then highlight the values in green. So to do this let’s type in the if formula, and we’re gonna say if A7, click on there and press F4 twice, just so we can lock in column A. So if A7 equals B5, now press F4 once, just so we can lock in the row number five. So if A7 equals B5, then true or else false. Now let’s put in here on equal sign, we forgot that. Now, if this is true, then the format we’re gonna fill it in a green color there. Press okay there, and you can see all the receivables that are due within the actual due date are highlighted in green. Everything else is overdue and what’s paid on a later date. Now we’re gonna do another Pivot Table report and we wanna see the distribution of the accounts receivable over the months. So let’s highlight the Pivot Table, press Control + Copy and we’ll just go down here and press Control + V. So we have the same Pivot Table here. And let’s click anywhere in the values. Right-click and show values as. Let’s change that to include percentage of grand total. And now we’re gonna go to design, grand totals and we’ll have it on for rows and columns. And what it says here is if we highlight everything, we’re gonna get a hundred just like that. So it shows us the distribution of the age receivables over the months and years. Now finally, we can put in that heat map down here, and we can just highlight there, go to condition format, and a color scale, and let’s put in there this one here. So this is 100%. Now it says that out of the age receivables that were due in 2012, about 15% were actually received in January, 2013. And the rest, you can see the distribution in May. So conditional formatting allows you to highlight problem data, and you can take some action to improve your business. (upbeat music) We have our sales results for our regions and our products going across the years, and we have the grand total here as well. And we’re gonna put in there some conditional formatting just to show the highest and lowest sales values throughout the years and throughout the regions. So, first of all, we’re gonna put a data bar just within the values here. So to do that, just click anywhere in the values and go to conditional format and go to data bars. Let’s choose a gradient fill like that. Now we’re getting this dropdown box here, and then we’re gonna apply the formatting rule two. And this third option here means that it will only conditional format the values and not be sub-total. So click there and then we can go back to conditional formatting, manage rules and double-click just so we can change that color here. So the color, we can leave it like this and the border, let’s put in a blank border and we can get a preview here and then press okay and apply, and then press okay there. Next we’re gonna put in a three color scale on our grand total. So let’s highlight the grand total there, press Control key from the keyboard and then with the mouse, highlight the rest of the grand totals, but exclude the sub-totals. Go to conditional formatting and go to color scales, and we’ll include this second one in here. And finally, we’re gonna insert some slicers in there. So in your Pivot Table, go to options and select slicer. We’re gonna put in the financial year, the sales quarter and the sales month, and press okay. And let’s grab the financial year, right-click slicer settings and get rid of the display header. And we can just put it like this, and move it in the corner there. Now what we’re gonna do is just double-click in here, just so we can have a bit more space and then highlight the rows and insert just like that. So we have the years there. Let’s put in our sales quarter, let’s get rid of the display name again, and then we can just bring this up and then put it there. And then the sales mark, again, let’s get rid of the display header. And then from the options, we’re gonna choose the three different columns. So that means each quarter is separated. And we can just put it like this, just make it a little bit bigger. Okay. And move it up there, and there we have it. So we can click on the slicer, hold the Control key, click on all of them, go to options. And then we can choose whichever color that we want. Okay, so now that we have the slicers, if we choose one here, the conditional format applies to that year as well and it changes accordingly. If we go to Q1, the same thing. Now we can hold the mouse key and scroll down to highlight everything again. We can choose each month individually, and quickly see which are how high and low sales values. So with conditional formatting, you can put some visuals on your Pivot Table and your data does stand out. (upbeat music) GETPIVOTDATA is a formula that uses the Pivot Table to create customized reports that give the user more flexibility. It uses the Pivot Table as its engine to spit out numbers based on the user’s needs. There are certain advantages of using a GETPIVOTDATA formula. You can produce a report to your liking. So you’re not limited to the Pivot Table format. When the pivot data source changes, then all you got to do is refresh the Pivot Table and your report will update as well. You can also format your report and upon refreshing your Pivot Table, you will never lose its formatting. And finally, you can add extra columns for business metrics that are unable within a Pivot Table. There are lots of people that don’t use the GETPIVOTDATA formula. It’s because they don’t know the power that it can have. The reason is that most people will actually go outside the Pivot Table and try to do a quick sum formula, for example, 2013 plus 2014 like this. And when they try to scroll down, then they get the same number. And then they look at this formula and they’re saying, well, it’s a GETPIVOTDATA, I don’t like it, I don’t understand it, so I’m not gonna use it, which is fair enough. But I’ll show you ways where you can use GETPIVOTDATA, to enhance your reports. Let’s press Control + Z to get out of there. Now to activate the GETPIVOTDATA, you got to click in your Pivot Table, go to options and the options from the dropdown arrow choose generate GETPIVOTDATA. That’s ticked, it means it’s on. If you uncheck and you click anywhere inside your pivot data, then you get a cell reference. If you want to use, GETPIVOTDATA, make sure that it’s selected. So let’s get a number from within our Pivot Table and press enter. Now let’s go to our function in here. Just click anywhere in there and we can move this around here. Move up here. Now, if you wanna get the explanation of GETPIVOTDATA, just click on there and you get the Excel help, or you get the details about the function and what it does. Now, the data fields, these are the values that you want to return. For example, sum of sales, count or average. Now in here, it gets the sales, which is the sum of sales here. So it’s the sum of sales that we are showing. And the second argument is the actual Pivot Table. So in here you can click anywhere in the Pivot Table, but we usually click on the top left hand corner. Now the third argument, this is the field name. So we’re looking at salesperson. We have here salesperson, and we also have the quarters. So the field name is first of all the salesperson, and then within salesperson, we have the item, which is in, right. So we’ve selected cell D12, so it’s in right as a salesperson, the over to the second field, which is the financial year, which is up here. And the item within the financial year, it’s 2014 because we’ve checked in there. Finally, the third field is a sales quarters. So we have the sales quarters in the row labels then item three, we have the actual sell that we’ve chosen, relates to Q4. So it puts it in that order and you get put up to 126 different combinations there. Let’s press enter and we’ll get our value out there. And the power that comes with a good pivot data formula is with the item numbers, we can actually reference them to a cell. So instead of say, 2014, we can change it to 2013 and see what happens. The value changes to 670. This change Q4 to Q3, it changes to 624. And finally, instead of the Ian Wright, let’s put in John Michaloudis. So you get, John Michaloudis’s 2013 sales. So based on this, you can see how you can create a report in here where you can reference your items with your own custom format, your own metrics, and every time the Pivot Table gets updated, all you got to do is refresh and then your data gets updated here. And I’ll show you how to do this in the next chapters. (upbeat music) Now, we’re gonna create a custom report with the GETPIVOTDATA formula and what we’re gonna do is reference our formula to the items that we have here. So the years, 2013, 2014, the quarters, and then the regions that we have there, and we’re gonna paste the formulas into the empty boxes. We’re gonna get our totals and then our variance or Delta amounts. And then we’re gonna use this combo box to change the variance based on our selection. So, first of all, let’s go and choose Americas Q1 2013. So the equal sign or the plus to activate our formula, Americas Q1 2013, let’s click in there. Now let’s go into our Pivot Table. So it’s taking out sales data and the Pivot Table is A1, which is correct. Field number one is sales region, correct. Item number one is Americas. Now instead of having Americas there, we can actually reference it to here. Now let’s press F4 three times so we can fix the columns. Now let’s go to the next field, financial year 2013, same thing, get rid of that and let’s get the reference in there. Now let’s press F4 twice so we can fix the rows. And then we have field three and item three, get rid of that again, reference it in there and press F4 twice so we can fix the rows. Now, press enter and we get the amount of 652,159 which is there. What we’re gonna do now is drag this down to get our values and you can see that match in here. Now sometimes your formula may not work and it happens sometime when for example, you have some leading or trailing spaces. So let’s double-click in there and put in that space and press enter, we’ll get a reference. So sometimes when you’re copying and pasting texts or values, make sure that there are no leading spaces. Control + Z to go back. Okay, so let’s drag this across in there and we’ll have our values there, Control + Copy, and then Control + V. So we have our totals there and we have our variances there. So quick and simple, in a matter of minutes, we’ve created our own custom report with our own metrics and we can extend this to add some more metrics at the bottom if you like. If you had data changes, then this will get updated as well. So let’s go back to our data source and change Americas Q1 2013. Let’s change the value so we can see if it gets picked up here. So data table or in Americas, 2013 Q1. And let’s put it in our (indistinct) like a million dollars. We’ll go back. So this will get updated here when we refresh the Pivot Table, right click, refresh, and see if that automatically get updated. Now, finally, we’ve put in here our metric, which is the variance. And what I’ve done here is I’ve put in a form control from the developer tab. So I went in there and pressed insert, form control, I chose the combo box. And I place it in there. And then if I right click in there, under format control, the input range is this here. So it’s Q1, Q2, Q3, Q4, total. The cell link is there, so when Q1 is chosen, it’ll be number one, when Q2 is chosen, it’ll be number two and so forth. And then dropdown lines I’ve chosen five and 3D shading. So as we changed this, our values change. So what I’ve done is a formula in here, which is an index formula with array formula. So what I’ve said is area 2014, so the array is in here in blue, 2014, the column selection, I’ve named it range, which is number two. So in this array is choosing the second column two, because I said Q2 equals two. So you’re choosing the second column and then using the same thing in 2013, it’s choosing the second column. So the second column in 2014, minus the second column in 2013, we get our value. Now to make this work all the way down, what I did is I highlighted all the rows here and then I press Control + Shift + Enter to turn it into an array formula. You can see that we get the live results as we’re changing our selection. So call it a trick there that you can do outside the Pivot Table. And another great reason why GETPIVOTDATA is fantastic because you can add things that you normally wouldn’t be able to in your Pivot Table. (upbeat music) We can also reference dates with the GETPIVOTDATA formula. In our Pivot Table here, I’ve got our order date in our row labels, and our sum of sales in our values area. And what I’ve done is I’ve taken the date of the first order, so the order is sorted from the earliest date all the way down to the last date. So I’ve taken the first date and typed it in here, and now what we can do is type in out GETPIVOTDATA formula, and cell reference, this cell in here. So let’s press equals or plus and write in a GETPIVOT and then press the Tab key. Now the data field is gonna be sales so we need to, with the brackets, type in sales, close brackets, the Pivot Table, we can click anywhere in here. We usually click on the top left hand corner and press F4 just so we can fix that value in there. And comma. Next is the field name. So we have the order dates, as we said before. So let’s type it in order date and make sure the spelling is the same and the item number one, well, that’ll be this reference here. So all we’ve got to do is just click in there, close the parenthesis and presenter. And you see you get the value there. Now, the data that you put in here, you gotta make sure that it actually exists within your data source. If it doesn’t exist, then you’re not gonna get a value. For example, we had the third of the first and then our next transaction is on the 12th of the first. So all we can do is for example, let’s put in the 4th of January in there, you get a reference because the data doesn’t exist. Instead of giving us a zero, it gives us a reference there. So let’s put in the second valid transaction. There you go. We have the value there. Another way that you can do this is actually putting the date formula. So I’ll press Control + D just to copy what’s up there. So it’s the same formula there. Now, instead of referencing the cell here, which we did before, what we’re gonna do is put in there the date formula. so let’s type in date, D-A-T-E, press the Tab and the year, or we can type in 2012, the month is January, and put in one, and the day is 12. And then we’ll go out here and we can close the parentheses and press Enter. And we’ll get our value. So there’s a couple of ways that you can reference dates with GETPIVOTDATA, just make a note that your dates do have values, if not, then you get a REF error. (upbeat music) We can use data validation to make out GETPIVOTDATA formula interactive. What we’re gonna do is create two dropdown lists, one for the months and another one for the regions. And then incorporate those into the GETPIVOTDATA formula by way of self referencing. And then once we change the months and regions from our dropdown list, then our GETPIVOTDATA results will also change. So let’s grab our months from in here, Control + Copy, right click and paste the values. Next we’ll choose our regions. So click in Americas hold on Control key, choose Europe, and then again, hold onto Control key, choose Asia, and then hold on the Control key and choose Africa, press Control + Copy, come up here, right click and paste the values. Now what we’re gonna do is create our data validation. So in our data tab, we choose data validation. And then in the dropdown box, we choose the list and our source will be our months in here and press okay. And we’ve created our list of all the months in there. Now let’s do the same thing for region. So again, data validation, choose the list, our source is in here, press okay. And we have our list for the regions created. Now let’s create our GETPIVOTDATA formula just by referencing it in our Pivot Table. So we have our value there. So now what we’re gonna do is instead of using the January argument in our formula, we’re gonna get rid of it, and we’re gonna reference it in our data validation list. Now for Americas in the regions, we’ll do the same thing, backspace to get rid of that. Choose our data validation list and press Enter. So we have our value there. So now as we changed our months, the formula gets updated. And also as we change our regions, our formula gets updated as well. So I call it a trick that you use when you’re creating customer reports with GETPIVOTDATA formula. (upbeat music) Then GETPIVOTDATA, it does have a shortfall. And let’s reference our pivot data for Q1 Americas, and press enter. And we have our formula in here and say that we’ll want to add in the sales month of January into this formula, and let’s see what happens. So in there we’ll put in sales month, and then January, and press Enter. We get an error message. So if the sales month is not part of our Pivot Table in here, anywhere in our column labels or row labels, if it’s not part of our Pivot Table, then it’s not gonna give us a result. So what we’re gonna make sure is to grab the sales month and drop it in there, and then we have our GETPIVOTDATA updated. Now in here, we have our sales quarter Q1 as part of our formula. So we grab our sales quarter and we’ll take it out. The reference is valid because our data is not part of our Pivot Table. So to fix this, we just got to make sure that you get rid of that argument there and press Enter. So if you wanna make sure that your GETPIVOTDATA formulas is working, then make sure that you drop in all the fields into your areas here so they can work properly. Another thing to note is that if you drop in fields into the report filter, then your GETPIVOTDATA is not gonna pick that information up. (upbeat music) We have our Pivot Table here with our regions on our row labels and our months on our column labels. And it goes all the way to the right-hand side there. So what I wanna do is bring these grand totals to the left-hand side of the Pivot Table. Now to do that press equals or plus, and we’ll go all the way to the grand total and enter that in there. So we’ll get our grand total there. Now, if we drag it down, then it’s fixed to the Americas grand total. So what we need to do in here, instead of having this Americas name, we just got to reference the cell C3, and then we can just drag it all the way down there. Now for the grand total to work, we just got to do the same clicking the grand total. If you see in the argument here for our grand total, it only has the data field, which is grabbing the sales values and the Pivot Table location, which is C1. Now this works well if you keep the format like this. But say that you want to add in some more fields, like the quarter in there, well, this doesn’t work. First what we wanted to do is say that if the first cell here C3 equals to grand total, then we need to put in this formula here. If not, then put in that formula there. So let’s grab this formula from in here, Control + Copy, and then in here we’ll say, if C3 equals bracket grand total, then let’s press Control + V and put in our formula that we took from the bottom. So if you C3 equals to grand total, then it would give us the grand total amount there. If not, then it would give us all the regional totals. And then close parentheses and press Enter. And now we can just drag all the way down here. You can drag all the way down if you want, if you’re gonna add some more items in there. So that fixes that problem. And we’ll have another problem with the REF error. Now to fix that, all if to put in there is an if error formula, if you’re using Excel 2010 or beyond. If you’re using Excel 2007, then you’ve got to pull if is error, I’m using a 2010, so I’ll put in if error, go to the end, comma value if error, well, the brackets, so it means blank. Then I’m here, double-click, and then you can see we have our grand totals for our regions and also our grand total in there. So call it dope workaround if you wanna see your grand totals on the left-hand side of your Pivot Table. (upbeat music) We’ve got our Pivot Table on the top here, and we’ve included our sales regions and our sales months and years on the top and the actual and plan in the values area. If we go right across you can see it all the months there all the way across. Now it’s pretty ugly looking. Now, we’re gonna do a better report here at the bottom, by using the GETPIVOTDATA formula. Now let’s close the field list there, and what we’ve done here is we’re putting the months from January all the way through December here, we just type that in. And we’re gonna use that later in our formula. And in there, we’ve actually put in the months and if I press Control + One, you can see that we’ve entered the mmm and that puts in Jan, if we press in another M, you put in the whole month, it doesn’t really matter, we just wanna show that it is January, even though the actual date is the first of the first, 2014, and then the first of the second, 2014 and so on. Then we’re gonna us these to determine whether our action month is an actual or a planned month based on the end of month date. So let’s go into the end of month date and in there, we’re gonna put in a formula called end of month and today. So press Plus, end of month. And then the start date, we’ll just put in there another formula which says today and close brackets, comma, and the month we don’t want any full months, we just want today’s month. So today’s end of month is the 31st of the fifth, 2014. We know that because if we go here, today’s the 21st of the fifth, 2014, so the end of the month is gonna be the 31st of May. Now in here, we’re gonna put actual or plan based on what today’s date is. So if today is less than the end of month date, then it’s actual, if it’s not, then it’s planned. So in here, we have to put in a if formula. So let’s put in if, and let’s click in there. So if B15, so if January, now let’s press F4 twice so we can lock it in because we’re gonna drag the formula down. So if January is less than or equal to the end of month date, let’s press a F4 once to lock it in. So if that is true, then return us an actual in text, if false, we return us to the plan. So anything from May onwards will be plan, and before that, it will be actual, as you can see there. So now we can create our GETPIVOTDATA, and based on this actual or plan detail, you’ll return us the values from within the Pivot Table, press plus or equals and click in the Pivot Table there next to Americas, it doesn’t matter that it’s 2012, we can change those values later and we’ll get the GETPIVOTDATA. Now what we’re gonna do is we have the actual there in brackets, so the first argument is the data field. So it’s taking the data from the actual, but we want it to reference this cell here, if we press Enter, we get a reference. Now I’ll show you a trick that will give us the actual data. So it’s B16, let’s press the and sign and then the two parentheses and that means that it’ll lock it in as text. You see that it works. So we’ve got the actual there, now let’s go into B16 and press F4 twice so we get lock in the row 16. The second argument is the Pivot Table and the defaults to A2, it could be anywhere in the Pivot Table, let’s leave that, that’s fine. The sales region is Americas, but let’s get rid of this, and then let’s reference it in here, and then press F4 three times to lock in the column A. And the financial year, 2012, but we can actually put an actual formula there and we can say, year and then we can go in there. So we’re getting the year from January, which is 2014 and let’s press F4 twice to lock in the row 15 and then close bracket. And then sales month, we’ve got January, let’s get rid of this and then let’s reference it to January. So, as I told you before, we’re gonna use the months names in there in our formula and here it’s where it’s gonna help us out. And then press F4 twice to lock in the row and then press Enter. So we get 260,257. So we can see that Jan, 2014 actual is 260,257 so that’s correct. So our formula works, all we’re gotta do is just drag it across there and then drag it all the way down. And I’ve what I’ve got here are some sub-totals. Now we’re gonna put in some conditional formatting here, so if it’s planned, then it’s gonna be grayed out, if not, it’ll be blank. So let’s highlight all the cells there and go to conditional formatting, new rule, and then use a formula to determine which cells to format. Let’s put in there an if function, so if B16 and press F4, so if B16 equals plan then true or else false. So we’re saying, yes, if it’s plan, then we’re gonna format it in gray. If not, it’ll be blank. Let’s format and let us put in a gray color there, press okay and okay there. So you see that it’s grayed out. Now let’s test to see if this works. So let’s say we’ll go into our next month and let’s put in the 30th of the 6th, 2014, and you’re gonna see that this plan here changes from plan to actual and the values change from the plan, it gives us the actual values for 2014 in June and the conditional format as well, gets blanked out. So let’s put in there one month ahead and press Enter. And you see, we get the live change there. Again, let’s go two months ahead, and that changes accordingly. So you’re gonna have a situation where your actual data gets inputted in here, and all you need to do is just go to the Pivot Table, right click, refresh and then the information will get updated accordingly. And when you go into the end of month date, then the values change. So the GETPIVOTDATA formula gives you some awesome power to create some live reports, and you can print this out and send it off to your boss on a monthly basis and you don’t have to recreate this each month. (upbeat music) We have listed our channel partners on the left-hand side here, and we’ve got the different months, and we’ve got the individual values for the years. And on the right-hand side here is we have a report that we’ll want to compare each channel partner and based on the base year that we choose, and the comparative year, we wanna see the variance. Now we’ll need to do this by inserting a GETPIVOTDATA formula, and I’ll show you how to do this in a second. Now, the first thing we need to do is create some Pivot Tables. Now we’ve got the month base year and comparative year. Now let’s highlight the month and go to insert and Pivot Table, and let’s go to an existing worksheet and we’ll just put it in there just for the moment. And it’s drop in the month in the row labels, so we have our Pivot Table there. And then we can go to move Pivot Table and let’s put there. Now we’ll do the same thing for the base year, insert Pivot Table, and let’s put it in here and I press okay. And then the base year into the row labels, and then let’s move it in May, and then finally, we go to comparative year and let’s do the same for that. Because that’s the first step done, let’s go to our report up here. Now, the base year, so let’s reference that to the months Pivot Table. So the first entry there and press Enter and the same thing for the comparative year. Now we’re gonna use slicers later on to control the months. And I’ll show you how to do that in a second. Now in the base year we’re gonna reference that to the base year Pivot Table, so the first entry there, and then the comparative year, and we’ll do the same thing and then enter there. The next step is to put in there a GETPIVOTDATA formula. So let’s press Enter and then choose anywhere in there. So we’re taking the sales as being the data field, which is correct ’cause we are using the sales information there. Our Pivot Table is in A3 and the financial year instead of having 2012, let’s get rid of that to here and then press F4 twice to lock in the row number. Your sales month is January, but then let’s get rid of that and then we can reference that to I12 and press F4 twice to lock that in. And the channel partners, we can get rid of that. We can go in there and just go up one and press the F4 three times to lock in the column and then press Enter. So we can check this now that ABC telecom in January, 2012 was 103,000, so 2012 January, ABC Telecom 103,501. So let’s put in there an if error, because if we get an error then we’ll get a zero because some channel partners that don’t have any values and press Enter. Drag this across press Control + Copy, and then highlight this area right-click and then put the FX in there. So we’ll have our values there. The final step is to insert a slicer. So let’s click on our Pivot Table and go to options and insert slicer, and then press the month. So we have a month there, now let’s put that into three groups and we can move it up there. Let’s do the same thing for the base year, insert slicer and then move that up here as well. And then finally, put the comparative year, click in there and insert the slicer. And let’s move that in there. So then we’ll have our slicers if we choose the base year, you can see that this changes and so there is the GETPIVOTDATA for the base year column, 2013 and 2014. Comparative year the same thing happens, the information changes, and you can see that because it takes the first entry in the Pivot Table. And we’ve referenced that in here. Now let’s choose a value there. And now we can also do the months as well. So then do the analysis based on the different months. And we get the variance dollar and the variance percentage. So by using the GETPIVOTDATA in some slicers, we can do some comparative reports on channel partners, and it’s not only limited to them, you can do comparative analysis on products, on employees, on whatever metrics that you like. (upbeat music) Macros enable you to record steps that you do in Excel, and then run those steps automatically with the press of a button. You can create these macros for your clients or colleagues to give them the analysis power that they wouldn’t normally have. And to create a macro, assumingly to go into your ribbon and then choose view. And on the far right hand side, you have the macros button and you can press the record macro button from in here. Another way you can do it is through the developer tab. Now you may not have this activated, but I’ll show you how to do this. First, you go to file, then options, then under the customize ribbon option, on the right-hand side, you have the developer box there. Now it may be unchecked if that’s the case, just check it and press okay. And that will activate it. Now, another thing you’ve got to take into consideration is the trust center. So click in there, then under trust center settings, click that and choose macro settings. Now in here, you have different macro settings. If you choose the disable macros, then once you open your workbook, the macros will be disabled and then you’ll need to enable them. Now, if you want to enable them with a notification, that means that on top of the formula bar, you’re gonna get a yellow strip that says enable. Well, choose this option. If you wanna disable all macros without notification, choose the first option. And if you wanna disabled all macros except digital sign macros, then choose this option. Now, the last option is not recommended. That means enable whole macros when you open the workbook. Now you may have some dangerous code in there, so never choose this. So let’s choose the second option and press okay, and okay. And now in your developer tab, you have the code here, the macros that you’ve recorded, you have also the addings here that come from your computer, and also you can insert some form controls in here. So there’s a few options in here under the developer tab. The main thing is the record macro, or bringing up the macros that you’ve already recorded. (upbeat music) We’re gonna record a simple macro to refresh a Pivot Table. Now to do this, first of all, we need to go to the record macro button under the developer tab, or you can go to view macros and record macro. So let’s do it from here. And then it brings up the dialog box, and in here you need to name your macro. So let’s call it RefreshPivot, make sure there are no spaces. You can put in here a short key just to activate that macro, next time you want to run it. And also you’ve got the option here to store the macro in. If you choose this workbook, then that means that you can share this macro with other people. So if you email these documents to someone else like a client or a colleague, then choose this option. If you want to keep it just for yourself, then choose the personal macro workbook. And if you want to store it into a new workbook, then choose that, we’ll choose this workbook, so that can be embedded into this workbook. And description, you can just write in a short description, if you like, we’re not gonna have to write anything we’ll press okay. So now the macro is running and we know that because on the bottom here, we have the blue box that says, “A macro is currently recording.” And we can press that to stop it. Now, if we go to the developer tab, then you can see that it’s running there and it says “stop recording.” So we’ll know that it’s recording. Now, all we’re gonna do is click in our Pivot Table, right click and press refresh and stop recording. That’s our macro. Now to see our macro, let’s go to macros in there and you can see the refresh pivot there. Next in all open workbooks, or we can choose this workbook and it comes there. So now we can run it from in here and we can edit it or delete it from in there. Let’s cancel out of there. What we’re gonna do is insert a shape and then we’re gonna attach that macro in there. So let’s put in a shape, and then from the shape styles, let’s choose a button like this. And then in here we (indistinct) to right-click and choose assign a macro, and then from in here, we can just choose our RefreshPivot macro and press okay. Now, once we’ve done that, you can see that the hand has been activated. So if you click that, you will refresh the Pivot Table. Now let’s right-click and then type in there refresh Pivot Table. Press Control + A and let’s format this a bit, let’s make it a little bit bigger and then put this in the yellow and then step out of it. So if we go to our data table, and then we change the amount here to say 10 Million, and then we need to refresh our Pivot Table, we just go in there and press refresh. It’s very simple to create a quick macro. Now, another thing you’ve got to make sure is if you go to file and save, it’ll give you a dialog box that says, because this is a macro you need to save it as a macro enabled workbook. So to continue saving as a macro free workbook click yes, that’s not advisable let’s click no and then it brings up our save as dialog box and then from in here, all we’re gonna do is just from the dropdown box, choose Excel Macro-Enabled Workbook, and then press save. And let’s get out of this. And now we’re in here and you can see that this Macro-Enabled Workbook, the type is macro-enabled workbook and also you get the exclamation mark. So let’s double-click to get back in. And now we have the enable content. So for the macro to work again, if you click here, it’s not gonna work, we would click enable content and then refresh Pivot Table and you’ll refresh again. (upbeat music) Now we wanna create a macro where we filter our dates, so we can see this month’s values. This quarter’s values, and also the year to date values. Now we have the order dates here in our row labels, but it can be invoices due or customer payments to be received. It could be any dates. Now to create this macro, first of all we’re got to clear whatever is in the filter and then run the macro for each of the three filters. So let’s choose any day filter. Now let’s go into our developer tab and press record macro. So the first macro will be called this month, and we’ll keep it into this workbook and press okay. So the macro is recording, the first action would be to clear the Pivot Table. So let’s go in there and press clear filter, and then let’s create the date filter for this month. So click on the dropdown box, date filter, and choose this month and then stop recording. That’s our first macro. Let’s create our second macro, press record macro and call it this quarter and press okay. First step is to clear the filter, the second step is to choose this quarter filter and then press stop recording, record macro for year to date, record macro, call it year to date, press okay. Let’s clear the filter, let’s go back in, date filter, year to date and stop recording. So now we’ve created our three macros and now we’re gonna put in some buttons and assign those macros to each of the buttons. And let’s insert shape and we can insert this color shape there, and let’s choose the start here. So what we can do now is just click on the shape with our left mouse button, press Control + Shift. And then this moves that across, let go of the mouse button, you’re still holding on Control + Shift and then click and drag across. So we’ve created our three shapes. Now in here, we’re gonna call this month, in there we’ll call it this quarter and the next shape we’ll call it year to date. We can click on one shape, press the Control key and select the three shapes. And then we can edit it from in here. We can center it, we can make it bigger, we can make it into a yellow color, and then we’ll go to the format and text effects we can put in their a shadow if you like. And then we may just drop it down a bit like that. So we have about three different buttons. And now let’s assign the macros. right-click, assign macro, this month, okay. Right-click, assign macro, this quarter, assign macro, year to date. So let’s see if this works. This month, if I click this quarter or the step was to clear the filter and run the date filter for this quarter. So it does that and then year to date. Now today’s date is the 20th of March, so obviously we’re in the 1st quarter. So year to date and this quarter will be the same. So here you have a quick macro, to see your date filters, so when you open this workbook next month, or in a few months down the track, then Excel is smart enough to know your current date and then recalculate the date filters based on your current date. (upbeat music) We’re gonna record a macro, where we’re gonna get different Pivot Table views depending on the button that we’re going to press. Now, the trick to this is that the first step of the macro is to clear the Pivot Table and the the second step is to create the Pivot Table. So let’s go and record our first macro and call it region by quarter and press okay. So the first step is go to the options tab, clear, clear all, the second step is to create the regions by quarter. So grab the quarter’s, region and then we’ll grab the sales twice into the values area. Now from the dropdown arrow, we choose value field settings, and then we put in here average and press okay. Finally, select everything, go to the home tab and just put in a comma and go to the decimal places and then we can go to developer and stop recording. That’s our first macro done. The second macro is gonna be called year to date sales by month, so press record and call it year to date sales by month and press okay. The first step, once again, go to options, clear, clear all, the second step is to create the Pivot Table, let’s grab the years in the row labels, sales month as well, and drop in the sales twice into the values area. And from the dropdown arrow, the value field settings and show values as, and from the dropdown box here, we’re gonna show values as a running total in and the base field will be sales month. And the custom name we’ll change it to year to date and press okay. And then once again, click in here, go to the home tab and customize it a bit like this, develop a tab, stop recording, the third macro is gonna be called top 10 channels, press okay, options, clear all, grab our regions and our channel partners on the left and our sales in our values area, and then from the channel partners, we can filter it by value filters and top 10 and just press okay. And then finally, in the Pivot Table, we just right-click and so largest to smallest and go to develop a tab and stop recording. So we’ve done our three macros. Now all that’s left to do is to insert the shapes and assign the macros to the shapes. So let’s do this insert shape in there, and we’ll get one set in there. Now let’s choose the color of the shape like this, now hold down with your mouse key and then press Control + Shift and drag down with your mouse, let go of the mouse key then while the Control + Shift key is still being pressed, click the mouse, drag down and then let go of the mouse key. So we’ve created three similar shapes. Now let’s name them. Region by quarter, sales and average, year to date sales by month, and then top 10 channels. Now let’s click in one here. Press Control + A, so we can format the shapes. And then in here we can just choose a color. I like color like this and press Bold and we can just make it a little bit bigger like that. Escape. So now let’s assign the macros. Right-click, assign macro and in here we wanna choose region by quarter, and then the second one is year to date sales, and the third one is the channel partners. Now all that’s left is to press the button, sit back and enjoy the magic of the macros. So we have the region by a quarter sales and average, the year to date sales by a month, and then the top 10 channels by region sorted from largest to smallest. (upbeat music) We’re gonna record our macro where we’re gonna see our top customers by using eight scroll bar. So as we scroll up or down, then the number of customers in our Pivot Table changes as well. So our macro will be to clear an actual filter and then create the filter of the top X customers. Now let’s go to the developer tab and record macro, and call it top customers, and press enter. And in here, make sure that you have the filtered Pivot Table. So the first step will be to clear the filter. The next step is go to our value filter, choose top 10, and then just press okay from in here. And then stop the recording. So that’s our macro done. The next step is to insert a scroll bar. So in the developer tab under insert, let’s choose this scroll bar here, and then we can just simply put it in there, just like this. Okay. So right-click in there and format control. The minimum value will be one, the maximum you can do as high as you want, just depending on your customers. We’ll put in there a maximum of 100. The incremental change will be one. So as you move the scroll bar, it moves by one. And the page change will be 10, keep it at that. Now the cell link, we have to link it into the cell, A1. And press okay. So now as we’re moving this, you see that the number changes automatically. Okay, up or down, or we just take this and move it all the way up or down like this. Okay. We’ve got 100 there, let’s make this a little bit bigger. So now let’s go into our visual basic button, and then under modules, choose this and double-click. And the value that we have here instead of one, let’s get rid of that and we’re gonna type in there ActiveSheet.Range, and then put in there the parenthesis and in brackets we gonna put in there E1. So (*E1*).Value. You can save this and close it. So what we’re saying is, as this number changes, then our macro filter will change as well. The final step is to right-click in our scroll bar and assign the macro top customers, press okay. So now we can move this up or down and you can see that our customers and the values change as well as the grand total. So a cool little trick that you can use to see your top customers. (upbeat music) In our chapter 12.3, we created three different data filters. And now what we’re gonna do is put these macros into our quick access toolbar, which is over here. And then we can access them from there rather than having buttons. So let’s go to file and options, and then quick access toolbar. Choose here from the dropdown box macros, and you have the three different macros. So we can just select the macros and add, and add, and add. And then from in here, now press modify. And in here we can choose whatever design we like. So just up to you, there’s all these different designs. Now I just use a different color like this. And for in here, I’ll use another color and a year to date, I can just use that. Press okay, and then you can see that the macros are here. If you hover over it, you’ll see what it relates to. Just press that and they change automatically. (upbeat music) One way to reduce your file size is to copy an existing Pivot Table into a different worksheet. Now we have our Pivot Table here and we can go to that file and look at our properties, and our size is 45 meg. Let’s escape out of there. So what we can do now is go to options and select entire pivot, press Control + Copy. Now we’ll go to file and new blank workbook, and press Control + V. And here we have our new Pivot Table. And if we go to file and save, we can save this as book three, that’s fine. Now, if we go back into the backend, we can see that our size has reduced to 11.8 megs. Now let’s just go out of there. Now, if we go to options and change data source, it’s linked back to our data source in our other workbook. That’s fine. Now we can also see our data set if we just go to the grand total and double-click, and it comes up in this workbook. Okay, so that’s a quick workaround where you can reduce your file size by copying it into a new workbook. (upbeat music) Another way to reduce the memory size is to delete the data source. Now because our Pivot Table is run by the pivot cache, then we can make the changes without having the data source there. But the only thing is that we cannot refresh the Pivot Table. Let’s look it out file size, which is 45 meg. And let’s go to our data source, right-click and delete and press okay. So we deleted out data source. If we go to options and refresh, well, we cannot refresh because our data source is gone. But what we can do, we can actually rearrange this Pivot Table because it’s written by the pivot cache and then put in there the regions. So we can make changes to our Pivot Table. That’s not a problem. I’m gonna press save. Let’s go and see our five size now, which is 12 meg. So it’s reduced dramatically. Let’s go back. Now if we want to see our data source again, all we’re gonna do is click in our grand total on the bottom right-hand corner, double-click, and our data source has been included in there. Now we can connect the Pivot Table, just go to options, change data source, and then select our table here, and press okay. And we have our data source connected once again. (upbeat music) A good way to reduce file memory is by saving your Excel file as an Excel Binary Workbook. Now these files store information in binary format since .XLSB files are binary that can be read from and written to much faster, making them extremely useful for very large spreadsheets. Now our file size is 45 meg. Now, if we save this as a binary format all we gotta do is choose the format from in here. And the third option is Excel Binary Workbook, click that, press okay. And now let’s go to the file tab and have a look that our size has reduced to 26 meg. (upbeat music) If you have over a million rows of data, then it’s best to use Microsoft Access to create a Pivot Table. Excel only allows you 1,048,576 rows of data that you can input. So anything above that you’ll need to put it into a database like Access. In here, we have an Access database with over 1 million rows of data. So we’ve got about 1.5 million rows of data here. And what we’re gonna do is we’re gonna import that into an Excel worksheet and create a Pivot Table. Now let’s get out of this and go to our Excel workbook. And from in here, we gonna go to insert a Pivot Table, now we’re gonna choose the use an external data source option, and then click on choose a connection. We’re gonna browse for more. And then what we’re gonna do is go on to our directory where our file is kept. So here it is here, we’re gonna double-click that, and we’re gonna create a cell A1, press okay. So from in here, we have all of our fields and we can simply drop in and create our Pivot Table just like that. So we have all our data there that you can see. Now just to make sure that everything is there, we can drop in the sales again, and then you use account just to count the number of transactions that are there. We can go all the way down, you’ll see we’ve got 1.5 million rows of transaction as we had in the Access database. So as your Access database gets amended, then all you do is press refresh to make the updates, or you can go to your connection properties, and in there choose refresh every X number of minutes, or refresh data when opening the file. Another advantage is that if we’ll save this, then our file size is small. Let’s have a look, file and we’ve got 28 Meg of data. (upbeat music) Now there are a few compatibility issues with Excel 2007 and Excel 2010. Now Excel 2010 has slicers. In Excel 2007, they’re not visible. So if you create an Excel file with slicers in Excel 2010, and you open an Excel 2007, they’re not visible. A box will appear instead stating that the slicer cannot be viewed in Excel 2007. Also Excel 2010 has six different calculations. Now if these calculations were created in Excel 2010 and opened an Excel 2007, you will see the results, but if you refresh, then these go away. And in Excel 2010 under the report and layout, the repeat all items labels option, if these calculations were created in Excel 2010 and opened in Excel 2007, then you will see the results, but if you refresh, it’ll go away. And finally, if you’ve saved an Excel file in Excel 2007 as compatibility mode, and you open that in Excel 2010, then you need to refresh the pivot in order to have the full Excel 2010 pivot features. (upbeat music) Now you can share a Pivot Table via Microsoft’s OneDrive. Now OneDrive is the same as SkyDrive, they’ve recently changed the name. And before that to have access to it, you needed to set up an account with live.com. So all you need to do is have access to OneDrive via Microsoft, and then you can upload all your files in there, which I’ve done here, and then you can share it. So if you click on this creating a custom style Excel workbook, and then go to share, we’ve got the option to invite people or get a link. Now we have three options. The person can view only, they can edit, or it can be public to everyone. Now let’s go to edit and create link. So now, what I can do is go to invite people and then I’ve got here, I can write a note that please see my Pivot Table for this year’s results. And then here you got the recipients can edit, which is the step that I chose before, but you can click there and you can do the view only, but let’s do edit. And in there recipients don’t need in a Microsoft account. So you don’t really have to have Microsoft account to access it, you can open it in a web browser. Now let’s press share, and then press close. And now I’m gonna go into my inbox. And now that I’m in my inbox, you can see that I received this email and it says here, John has a document to share with you on OneDrive. To view it, click the link below. So I’m going to click this link, and it opens up a web browser. So you don’t have to have an account there. And in here we have our Pivot Table with our slicers that work. Now in here, I can just right-click and show field list. And then I can take out the information here. So financial year goes out, and then I’ll put in there the sales quarter, and that gets updated as well. So you can make changes there with your field list. Also, if you want to save this on your computer, you can just go to file and then save as, and then save it onto your computer there. So this is a good way to send information and view your Pivot Table with the slicers over the web, and it eliminates sending emails. (upbeat music) We have our data source here and in our financial year, we have data just for the year 2014. And what we wanna do is create a sales forecast based on a 5%, 10% and 20% increase on the 2014 actual financial year. So let’s go to our Pivot Table here. And we’ve created a Pivot Table with our sales regions and our months going on top, and we have that up there. So now we can create a sales forecast simply by going into the calculated field. So now we’re in anywhere in our Pivot Table, we can go to options and then fields, items and sets, calculated field. So from in here, we can create our different calculated fields. The first one is gonna be forecast next year at 5%, forecast next year at 5%. So the formula will be the field with the actuals, and then let’s use the multiplication sign and press 1.05. So that’s a 5% increase. And we can add that. Now let’s set another one at 10%. And in here, we’re gonna bring in the sales and then 1.1 and press add. So we’ve got that there. And then we’ll do another one at 20%, and then 1.2 and press add. So we’ll have the three different scenarios there, and press okay. So we can see here in our values that there’ve been added in here. Let’s just make this a little bit bigger. So we can see that there. And let’s go in there into each one, the value field settings. And in here we can put in an asterisk just to distinguish that it’s a calculated field and press okay. We’ll do the same for the next one. And then last for that one there and press okay. So we can reduce that a bit there, and like this. Now they’ve also been added to our field list. Okay, let’s get out of here. And we can see if we just double-click in between the columns that we have the actuals, the forecast at 5% increase, the forecast at 10% increase, and the forecast at 20% increase. And it goes all the way across each month. And then we have the totals. So now, right-click and go back into the show field list. So what we can do is actually take out the sum of actual and just leave in that 5% amount. So we can see from in here if we can just double-click to reduce it, we have the 11 million. Now right-click to show the field list again. And let’s take out 5% and let’s put in there the 10% figure and see what we get, we get the 11 million grand total. Okay, we take that out and we put in the 20% and we get 12.7 million there. So with calculated fields, you can put in different scenarios based on your actual data, use a multiplication sign and then put an increase or a decrease, and you can do some different sales forecasting models. We can just highlight all that, press Control + Copy, and Control + V in there and Control + V there. Okay, so the first one we can put in the 5% scenario. In the second one, we’ll put in the 10% scenario and click on your third one and we’ll leave it at 20% there. So we have our three different scenarios and you can make your decision on which one to use based on what your business sees as feasible. (upbeat music) With a Pivot Table wizard, we can actually consolidate information into one Pivot Table. Now we have here four different salespersons data, and they’re all in a similar format. You see their salesperson one, salesperson two, salesperson three and salesperson four. Now, if they’re all in the same format, then we can consolidate. Let’s go to the consolidated report. Now the pivot chart wizard, there’s two ways to bring it up. One is to press ALT + D + P, and we can bring it up like that. Let’s cancel out of there. The other way is to go into the quick access toolbar, commands not in ribbon, and then put in Pivot Table and pivot chart wizard. Now to do that, we’ll go to file and options, quick access toolbar, and then from the dropdown box commands not in ribbon, and then click in there and put P to go all the way down. And then we can just choose the Pivot Table and pivot chart wizard and press add, press okay, and then it’s added in here. So let’s press that to start our wizard. And it gives us three options. The first option is Microsoft Excel list or database. The second option is external data source. And the third option is multiple consolidation ranges. And we choose the Pivot Table and press next. And then in here to create a page field, choose I will create the page fields, and press next. So now the first step is to select the range and let’s go in here and select that, and press enter, and then add. Go to the second sales range, select data then add it. The third salesperson’s data select that, add. And then finally the fourth sale information there, and then press add. Now how many page fields do you want? We’re put in there zero, ’cause weren’t gonna use any page fields. And then press next. And then finally it asks us, where do you wanna put the Pivot Table report? Let’s choose somewhere there and press finish. And you see the Pivot Table field list here has got a row, column and a value, because it’s defaulted to those names. Now the values we can just choose a dropdown arrow, go to value field settings, and then a number format. And go to number, no decimal places, 1000 separator, and press okay, and then okay there. So here we have our consolidated report from the four different salespeople. Now, if we go into one report here and let’s just say, there’s a change that was made. For example, let’s put in a big amount, 1 million, and press enter. Put that back here. All you need to do is right-click and refresh. And then you see the value change on the bottom right-hand corner there from 127 to about 128 million, press refresh, and see that gets updated. So each time your salesperson sends you an updated report, you can just refresh this Pivot Table and you get the consolidated data. I’ll show you another cool little trick. Say you receive your data like this in this format, and you want to put it into a tabular format. For example, in the first column, you want to show the regions, the second column you wanna have all the months, and the third column, you wanna show the values. Now to do this, we have to bring in our Pivot Table wizard and then choose multiple consolidation ranges, press next. I will create the page fields, press next. In the range just choose this, okay. Press enter, and then next. And we can just put it in there and press finish. So it brings up our consolidated range, but we already consolidated one piece of information, that’s fine. The trick to this is you’ve gotta double-click in your grand total. And then you see here that you get your tabular layout. So you have your regions in the first column, you can change this to regions instead of having a row. The column, you can change that to months, and we have the values, and go all the way down there. So it’s a good workaround when you get information that comes in on tabular formatted style, and you wanna put it back into a Pivot Table tabular format. (upbeat music) Sometimes in finance or accounting you wanna do a frequency distribution to see how your sales or costs are distributed depending on different groups. Now we have our information here without actual dollar sales and let’s create a Pivot Table, we’ll go into insert, and the Pivot Table, and let’s put it into our existing worksheet in there and press okay. Now from in here, we’re gonna put in now actual dollars in our row labels and then drop it again into the values area. And from in here, we just wanna get a count. So we’ll see how many transactions fall in between a different group. So let’s click in our row label and right-click, and only to group here our sales, and we have a automatic starting and ending point based on the minimum and maximum amounts. Now we can change that to put in 10,000, and then ending at 100,000. And increment, we can have 10, that’s fine. Press okay. So we have our sales ranges there and we can see the amount of transactions that we have in the values area there. Now we can put that in the graph by going into options and pivot chart, and we can choose a column and press okay. Now just right-click there and hide all field buttons on chart. And let’s make this a little bit bigger. And we can call this frequency distribution of sales. Okay. And then you can just get rid of that. So now we have our graph, and we can see the amount of times that we have sales between 10,000 and 19,999, you can see it there if you hover over this 22. And you’ve got the different sales groups, and we’ll have our frequency distribution in the graph. And you quickly see which sales ranges are more popular and which sales ranges are not. (upbeat music) We can do a breakeven analysis with a Pivot Table. We have a scenario and item and a value table here. So in our scenario, we have three different scenarios, slow production, normal production, and fast production. For each scenario, we have a variable cost per unit and a total fixed cost. And we see the values there. Now we can create a Pivot Table from here. Just click anywhere in there and go to insert and Pivot Table, and we just put it down here for now. In our row labels, we’ll put in there the item, and the value, will go into the values area. Now let’s drop in a slicer for the scenario and press okay. So we have our slicer there. So as we choose the different productions, the Pivot Table changes. And by this, we can go into our breakeven model and then reference the sales to the total fixed cost, and the variable cost per unit. And as we change these scenarios, then our break even model gets updated accordingly. So let’s grab our slicer, press Control + X and go into our breakeven point and Control + V to put it in there. Now we’ll have our breakeven model, which is a price per unit, which is a manual entry we’re gonna pull. The unit sold, again, a manual entry. And the total sales is the price per unit times the unit sold. The cost is the variable costs, and in here, we’re gonna put the units times the variable cost per unit that’s in our Pivot Table. So let’s choose the units and then press times and go to our scenario to get the variable cost per unit, which is in there and press enter. Now, the fixed cost would just be the fixed cost total from the Pivot Table. So go in there and grab that and press enter. So now we’re gonna put in a price. Let’s put in $10 and the unit sold, let’s put in there 2,000 and press enter. So on a slow production, we’re making a profit. On a normal production our profit reduces because our variable cost has increased and our total fixed cost has increased. And under a fast production, we have a breakeven point there. Now you can change these amounts just to play around with the numbers, but based on this analysis and using a slicer, you see how you can put in different scenarios and determine what your breakeven point is for your product or a new business model. (upbeat music) Now in here, I’ve created several different slicers that you can copy and paste into a new workbook and apply to your current slicers. Now, for that, you need to go on to chapter 7.4, copy a custom style into a new workbook, to see how you can do that. But here, I’m gonna show you the different styles that I’ve created and also shows you the flexibility that you have when creating a custom slicer. You have many options and I’ll give you some ideas to see what things you can do. Okay, so let’s click in our slicer there and go to options. And in here on the top, I’ve created eight different slicers. So the first one is to this, and you see the things that they can do. Let’s go to the second one. We got to the third one there. The next one. Then in here. So you see the different styles and fonts that you can use. And finally, we have this one here. So depending on your creativity, probably yours is much better than mine. You can create different styles. Now I’ve created this, it’s pretty quick. You have the guide here on the left to see what you need to change. And once you do one, you can actually do many more. So once again, in chapter 7.4, I teach you how to copy a custom style into a new workbook. And in chapter 7.3, how you can create a custom style. (upbeat music) With a Pivot Table and slicers, we can create a balance sheet that’s interactive. Now I’ve created the one here and what I’ve got in there are four different Pivot Tables. I’ve got two graphs that I connected and also some metrics up here. And then with a slicer, once I make the change, the metrics change, the graph changes and so do the Pivot Tables. So I can see my different status as at every month. So you can see, you can do some pretty powerful reports, and it’s not that hard. I will show you in the next couple of minutes, how to do this. So the first thing you need to do is when you’re creating a dashboard or a interactive slicer with charts, you gotta make sure that you set out your canvas and then separate it into different areas. So on the top here, we’re gonna put in there the slicers. And then second, we’re gonna put the metrics. At the bottom, we’re gonna have the graphs and down here we’re gonna have our Pivot Tables. So let’s go onto our data. And we have our data here which has the months. And we have the years for 2014 only. And we have our balance sheet items into current assets, current liabilities and non-current assets and non-current liabilities. And the type here, we have the different types of assets and liabilities as defined in a normal accounting business structure, and press okay. And we have the actual amounts there. So from in here, we can create a Pivot Table, go to insert Pivot Table and existing worksheet, and let’s put it in here and press okay. So we’re gonna drop in our balance sheet into the row labels and type into the row labels. So you can see it’s like this. Now we’ll make some space here so we can fit it in. Now, from in here, make sure that under options and options, the auto-fit column is switched off. And the design sub-totals, do not show sub-totals, and then field headers, we can get rid of them. And also the no buttons. Now, one thing we’ve gotta drop in are the actuals into the values area. Now, from in here, we can actually get rid of that and then just press a space. So it recognizes that as a character and it’s a work around to having a blank header. In the grand total, we’re gonna change that to total current assets, and press enter, and that’s fine. Let’s go back to our values and we can put in there the dollar signs into the number format. Let’s go to currency and choose dollar signs with a negative red and zero decimal places, and press okay there. Now we can filter this just for the asset. So when we go into the balance sheet, we can just select the current assets, and press okay. So it just gives us the current assets and in the design, we can choose this one in there. Now we can click and go to options and select entire Pivot Table and press Control + Copy. And in there, press Control + V. We’ve pasted the similar format in here. So we’ll have to go and redo all the formatting again. So the only thing now is instead of the balance type being assets, we can just choose current liabilities. And that changes there. Now let’s do the same for the non-current asset. So again, click there, select entire Pivot Table, Control + Copy, and down here press Control + V. And we can do the same thing there. So let’s click in the non-current assets. Let’s change that to select the non-current assets. And in here let’s select to include the non-current liabilities. Now let’s delete this space here. And then in here, we can just highlight it and put in a light gray. And the total assets, let’s do the sum, which is the current assets plus the total current assets. Now we get up and GETPIVOTDATA. So let’s escape out of there. Let’s click in a Pivot Table, go to options, and from the dropdown option, let’s get rid of GETPIVOTDATA ’cause we don’t want that. Once again, let’s click in there. And then we’ll do the same thing for the liabilities. So we have our Pivot Tables there for the assets and the liabilities. We can actually highlight all of this and choose a different font if you like. Okay, so the next step now is going to put the ratios there. So the current ratio is current assets divided by current liabilities. The quick ratio is the current assets minus the inventory divided by the current liabilities. So we’ll get that minus that inventory, and then divided by the current liabilities. Now the debt equity ratio equals the total liabilities divided by the owner’s equity. So let’s go to the total liabilities there, and divide it by the owner’s equity. And the owner’s equity is simply total assets minus total liabilities. So total assets minus total liabilities. So we have our numbers there. And in here, we can just adjust that if you like. Now, one thing I noticed here that we didn’t change the names for the grand totals here. So here it should be total on current assets. Here it should be total current liabilities. And in here total non-current liabilities. The next thing is to put in here the chart that relate to the total liabilities. So let’s highlight total liabilities and the amount there, and got to insert and bar chart, and we can include that in there. So let’s just start in here for the moment. We can get rid of the totals there. And then the gridlines, let’s make this a little bit bigger. And then highlight that and get rid of it. So there’s a click in our bar chart and press Control + 1. And then from in here, we can go to fill and pattern fill, and then choose this format there. And then we can choose the red color and then let’s click outside of the border there. And then the border color have no line as well. Now from the X-axis, click on that, press Control + 1. Maximum, you can leave it as automatic, but we can put it into maximum of 1 million. And the major unit will be 200,000. Display unit, we’re gonna put that in hundreds. And then the minor tick mark we’ll have that cross. We’ll show display units on global chat, that’s fine, and press okay. And finally, let’s make this in gray color and this as well. So we’ve created the chart or we can just make it a little bit smaller or bigger just depending on the size there. So we’re gonna do the same thing for the other chart. So instead of going through the same process, we’re gonna save this chart. So go to design, save template as, now when you do that, it goes to the Microsoft templates and charts, and we’re gonna call it in the interactive balance sheet. So let’s create the other chart. Let’s click on the total assets and go to insert and bar, and bar, and we’ll have that there. So let’s go to the change chart type from the template. Let’s hover over here and go on to our interactive balance sheet and press okay. Now we’re gonna change this to a green color, and also it’s gonna go from right to left as well. Let’s click in the chart, press Control + 1. And then the fill is gonna be a green color. And let’s click in here and the values are gonna be in reverse order, and press okay. One thing you’ll notice is that we have hundreds and let’s click in here and press Control + 1, and we change it to thousands. And the same thing for that, let’s click the X-axis and change that to thousands. So now we can put the charts in our dashboard and we can reduce it like this, just to make it fit. We can change that later on. Okay. Now the same thing for this. We can just put in there. Okay, now one thing is that background should be great. So click there and then put in the light gray background, click in the graph, press F4 to repeat, the same thing in there, press F4 to repeat. And we have our chart in there. The final thing we’ll need to do is put in that right slicer so we can control the months. So click anywhere in the Pivot Table, go to options and insert a slicer, and let’s choose month and press okay. And from in here, we can put it into six columns. We can drag it across like that. Right-click, slicer settings, get rid of the display header. Now let’s choose the custom slicer, which I created earlier called Johns Wicked Slicer. And we can read this like this, or we can just make the buttons a little bit bigger. So we’re gonna fit it in there. So that’s fine in there. Now, one thing we need to do is connect the slicer to the four different Pivot Tables. So and click on the slicer then right-click, and Pivot Table connections and just check all the boxes. So we’re connecting all the Pivot Tables to the slicer, and press okay. So now we can press January, the Pivot Tables change, the totals update and so do our metrics. So we have our live and interactive dashboard. You can see at any time how your business is doing, which is a pretty powerful tool to use, but it is pretty easy to create this once you know how to use Pivot Tables, slicers, and a couple of charts. And by going through this course, you’re gonna find out how to do all this stuff here. And it’s not that hard. It looks pretty fascinating to you use the Pivot Table principles and some common sense and then you can create a dashboard just like this. (upbeat music) Here we’re gonna create a monthly sales manager performance, where we see the sales for each sales manager on the left-hand side going all the way down the rows, and then get a percentage variance from the previous month. So we track each salesperson’s progress from one month to the next, to see whether they’ve increased the sales or decreased the sales from their previous month. And we’re gonna use some conditional formatting to show the variances visually. Now let’s create this. Click anywhere in our data set, go to insert and Pivot Table, and go to new worksheet. On the left-hand side, we’re gonna put in the financial year, then the sales month, the salesperson will go on the column labels. And we’re gonna put in there, the sales twice. Now let’s close that. Let’s reduce this a bit. Now go to design and grand totals off for rows and columns. Let’s make a few adjustments here. Let’s just make this centered. Okay, now let’s bring in our field list and we have our sum of sales there. Now let’s click in there just to format our numbers. And in here we can click and choose show values as, and we get the different from percentage difference from the previous month. So we’re gonna show values as a percentage difference from the previous sales month and press okay. We can go back in there and just format the numbers. Let’s go to custom and choose a red in there. And then before the semi-colon we’ll put in a percentage. And press okay, and okay. Let’s change the name here. Instead of sum of sales, let’s call it delta or variance, I’ll call it a delta and that changes there. And here, instead of sum of sales, let’s call it sales. That already exist. Let’s press okay, and put a space. And then we have that in there. Now we need to put in there a conditional format. So let’s click in the variance column and go to conditional formatting and choose the icon set. And let’s choose these arrows here. Now, from this dropdown box, let’s choose the last option just so we can see the conditional format only on the values and not the sub-totals. Now finally, we need to go back to conditional format, manage rules, double-click in here and let’s show icon only. So we don’t wanna see the percentages, we just wanna see the icon. And the values here, when the value is bigger than zero, a number and also zero and number. So it’s bigger than zero it will be green. If it’s zero, it’ll be orange, and if it’s less than zero it’ll be red. Now let’s press okay. Apply this, okay, it works perfect, and okay once again. We can see here that 294 is bigger than 170, 312 is bigger that 294, and then 229 is the less than 312. So it goes down. So you see the delta for Homer Simpson, the delta for Ian Wright and so forth. Now, finally, let’s go and put in a slicer. Let’s make some space up here so we can put it in there. Let’s got to options, insert slicer and got to salesperson. Now let’s make it like this. And we can go to columns, just make it a little bit bigger, and we can increase the size a bit. And we can change it to a color like that. We can put in there to make it a little bit bigger. Okay, so we have that salesperson there. So now if we choose Homer Simpson, we see his values there. We can just make this a little bit smaller so you can see it goes all the way down there. Okay. Now let’s double-click here so we can get a bit more space. Ian Wright, John Michaloudis, and if you wanna see all of them again, just clear the filter. So by using show values as, some conditional formatting and some slicers, you can do some impressive sales manager performance reports. (upbeat music) We have a list of customers here, and we have the payments column here. And in black, we have the outstanding receivables and in red, we have the payments that we have received from them. Now we can do a reconciliation by going into customers and sorting from A to Z. So we can have all the customers sorted alphabetically, and then we can go to the payments column and then manually see whether that equals to zero. And we can see down here that it does equal to zero. But imagine if we had 1,000 customers, we’ll be here all day doing this. And there’s a quick way to reconciling customer payments. Let’s go to insert Pivot Table, and we can just put it in here in existing worksheet and let’s drop the customers in the row labels, and then the payments in our values. Now, by doing this, it sums up the credits and the debits, and it gives us a zero amount if our customers have paid. And then we can see here that 123 Warehousing and ABC Telecom have paid the bills. Now Acme Corp, we have $3,467 outstanding. So they still owe us some money, but in Ajax we have a negative 2,900. So they overpaid us. And we can have a look here. If we highlight that, we can see that there were two payments of 3,200. So it shows us there that our customer has overpaid us and wanted to return the money. So by doing a Pivot Table, you can quickly analyze a bank reconciliation instead of doing it the manual way, and you’re sure to save heaps of time. (upbeat music) Now, I’m gonna show you a great add-in that will save you heaps of time when you’re working with Pivot Tables. It’s called pivot power and an add-in from contextures.com. Now, Debra Dalgleish is the one that invented these add-in and it’s absolutely fabulous. And she’s written lots of books on Excel Pivot Tables, and has been around the game for many years. And based on her experiences, she’s come up with this little gem where it’s gonna save you heaps of time. Now I’ve got a 20% discount for you. So if you stick around at the end of this video, I’ll show you the code where you can use and purchase it from her website. I’ll show you some quick benefits of this add-in. Now when we have a Pivot Table and we create it into a new worksheet or any worksheet. Say we wanna put in there some fields. For example, let’s put in our quarters in our row labels, and then let’s put in our sales month down here as well. Then the years on the column labels, and then the sales here. So we’ll have our Pivot Table here, and that’s the default Pivot Table. And it’s pretty ugly looking. You have this star here, which is not very nice. The numbers are not formatted with a comma, and you have the gridlines in the back, which looks pretty ugly. So every time you do a Pivot Table you gotta go into the design, choose your favorite design. Then you gotta go in to here, value field settings, and then change the number format from in here. So you see there, you’ve got about three, four steps to choose. And then view and get rid of the gridlines. So you got a few steps here every time you do a Pivot Table. So imagine you had a default setting. So you press one button and then it gets updated automatically. This is where that Pivot Power comes in. So the add in is in here. So once you purchase it and you download it, you’ve got all these different features here. And I’ll talk about it, just a couple of them now. So you’ve got the set default. So in here is where you see your default of how you want your Pivot Table to look. And then next time you come in there, all you gotta press the apply default, and it will apply to all your Pivot Tables. So in here we can choose the format, auto-fit column widths. We can get rid of that because every time you refresh, you don’t want it to reduce the column size. You wanna keep it the way that you want it. You’ve gotta get some grand totals as well. Now, the good thing here is the sort field list from A to Z. So you can sort it automatically. So from A to Z, imagine you had a big list and it wasn’t sorted alphabetically, then it’d be a mess to get in there and trying to find some fields. You’ve got some printing settings there. Now in the report layout, you can choose a compact tabular outline. Now I personally like the compact, but I know a lot of people like the tabular and the outline format. So you can choose whichever one you like. I’ll keep it compact. And the style, you got all the different styles there. Okay. So if you go into your design, and then hover, whichever one you like, you see you get your style number. So this is called medium two. So I can go back in there and say, I want to show the medium two. Okay. So medium two, you got everything in there. You choose whatever one you like, I’ll keep it there. Okay, so let’s go back here and just do the compact. We had the auto-fit columns off. Now in here, you got a few other things that you can do refresh data on file open. You can keep it like that. Now let’s go to the pivot field. You got a few settings in here that you can choose. And also if you’ve got a number format, here, you got the different formats. So you got number, accounting, percentage, now I like a number with a zero decimal. And I’ll apply this selected number format all the time. You also have the workbook settings here. And in here, you got the option to show gridlines or not show. I hate gridlines, so I’m not gonna show them. Let’s press save and apply. And look at that, it’s applied that to our Pivot Table. So you wanna go back to your data table and do another Pivot Table in to a new worksheet. You just drop a few things in here, it doesn’t have to be an order. Whatever you like. What you gonna do is go back to your Pivot Power add-in and say, apply default, and apply our defaults, and it updates it automatically, and you save heaps of time. So you have a Pivot Table here, and you just want to quickly put in some number formats. Or you go to Pivot Power and apply this number or format, and it does automatically and saves you heaps of steps. In this Pivot Table, I’ve got some counts of sales and average of sales. And if you look in there, right-click, you have your different values there. And so when we wanna change all of these into your sales, we’ll have to go back into one value field settings, sales and do the same thing for each one of them. Imagine you had about 10 different metrics there, and you just want the sales. Well, in Pivot Power, you go to Pivot Power and choose the sum all. And it changes it to the sum, and go to number format and it puts in the format in there. Now let’s drop in some filters in here. And then we can just quickly choose a few of the filters. And then sales region, choose a couple. Okay, so we’ll have a few of our filters there. Now say you wanna clear them, you gotta go in and press all and then go in and press all. And that’s a long way. Let’s press Control + Z and we’ll go back. And so we had, okay, a couple of more filters here, a lot of our customers, and choose a couple. Now a quick way to clear the filter is Pivot Power, and then go to clear all filters with one step. Another things is the GETPIVOTDATA is just right there. So you can turn it on or off. A great feature is on the Pivot Table. You go to Pivot Table and list or Pivot Tables, and it shows you in a separate sheet, which Pivot Table that you have active in the workbook. And it also shows you the pivot cache number in there. And also the last refresh date. We’ll go back in here, you go to cache, you go to cache list. It shows you how many caches you have. And here we have cash index number one. So if you’ve got an array of different buttons, that will save you heaps of time when you’re working with Pivot Tables. Whether you’re new to Pivot Tables or an advanced user, this was definitely a great add-in. And because you’ve purchased my Extreme Pivot Table Course, then Deborah and I will give you a 20% discount if you put in this code in here, M-E-R-X-P-T-C. And that’s short for My Excel Online Extreme Pivot Table Course. So you put in those seven letters when you go to the checkout, which is also listed now. You’ll get a 20% discount upon checkout. So if you have any queries or any issues, you can send me an email and then I’ll be glad to answer any questions that you may have. (upbeat music) So we have Excel 2013 on the top here. We have the ribbon here and we have Excel 2010 at the bottom half here. And I’m just gonna through a couple of the cosmetic changes in Excel 2013. When we click in the Pivot Table, we get that Pivot Table tools option in Excel 2010. And we have the options and design tab. In Excel 2013, options has been changed to analyze. So you can see that it’s called analyze, and 2010 it’s called options. That’s pretty much the major difference. Everything else has remained the same. It’s just a name change just to confuse us. But apart from that, nothing else has changed. So another thing you see in 2013, we have the insert timeline, which I wanna talk about shortly. That’s a new feature in Excel 2013, and also the recommended Pivot Tables over here. I’ve got a design and then go to design in Excel 2010 here, nothing much has changed. Everything else has remained the same there. So the major change is a name from options to analyze, but that is just a simple name change, and a couple of extra features that have been added into Excel 2013, which I’ll talk about. Now let’s talk about the Pivot Table field list here. So now on the left hand side, I have the 2013 Excel version. On the right-hand side, I have 2010. So we see the different pivot field lists. Nothing has changed there. Now, one thing you see here is more tables here. Now this is the data model in Excel 2013, which I will explain. That’s the more tables option here. And the other thing we can see here is, in Excel 2010, it’s called row labels. In Excel 2013 it’s called rows. In Excel 2010 it’s called column labels, in Excel 2013 it’s called columns. Now they’re just simple main changes. Apart from that, everything else seems the same. (upbeat music) We have an Excel table here, and let’s go insert a Pivot Table. Go to insert, and you can see here in Excel 2013 is recommended Pivot Tables here. Now, if you don’t know which Pivot Table layout will be best to use with your data, then I highly recommend you apply this recommended Pivot Table options. Now click on that. And it has the 10 different ways that you’re gonna summarize the Excel table that we have here. And you can scroll all the way down, and then choose with your mouse. And then you can see it over here. So it’s a count of sales by products, count of sales by sales. So it gives you a preview of the different layout that can be applied with the data that you have. Let us click down here. So this is quite good, especially if you have a lot of data and you don’t know what to stay, you think, okay. So what goes in the rows? What goes in the columns? This will definitely help you to get started, especially if you’re a newbie, even if you’re an intermediate or even advanced user, sometimes you get caught up with all the data and it’s good to sit back and see the different options that are available. And it may just you to create a Pivot Table that you never thought you would have created previously. Now you click here on a blank Pivot Table, and it gives you just a blank Pivot Table. You can start from fresh. You can also change your data source and you can get another data source if you like, but just choose one of them here. Let’s choose this, I like that, press okay. And you see that, it’s already done it for you. It’s put in the fields in the rows and in the values here. So it’s just to save you lots of dragging and clicking. And if you don’t like this, well, you can just move it around. So, great, great new feature in Excel 2013, which is gonna save you lots of time and expand your Pivot Table horizons. (upbeat music) If you want to do a distinct count using Excel 2010, you have to put in a complex sum product formula. But in Excel 2013, you can do this quickly using the data model feature. Now we have our sales table here and there’s a lot of order dates here. You go all the way down to about 3,000 rows. And as you can see, a lot of dates are duplicated. And we wanna know how many distinct or unique counts we have in the order date. To do this, we’ll need to create a Pivot Table. Go to insert, and Pivot Table, and then add this to the data model. Now let’s put in our order to date in the rows column there. And again, the order date in the values here. Now this will count it here. So it’ll show the total number of transactions. And let’s drop it in again here. And what we wanna do now in the second one, we’ll not do the distinct count. So let’s click in the drop-down, choose value field settings, and then in the summarize values by, there’s a new distinct count calculation here that’s been added, and that is just fabulous. So all we’re gonna do is we can just change this here, distinct count and press okay. So there you have it. All right, number one, just to confirm that that works properly. (upbeat music) Excel 2013 extends slicers for date fields, and these are called timelines. Now a new timeline slicer enables you to easily filter your Pivot Table by month, quarter, or year. In our Excel table here, we have order dates. So our timeline slicer will be created because you need a date to create that. So let’s go to insert and Pivot Table and put into a new worksheet and press okay. Let’s put in some sales in our values area over there, and put in the sales regions like that. Now we’re in the Pivot Table, Pivot Table tools, analyze, and here insert timeline. Let’s read these. Use a timeline to filter data interactively. Timelines make it faster and easier to select time periods in order to filter Pivot Tables, pivot charts, and cube functions. Let’s press that. Now it gives us the slicer, the only slicer that’s available is order date because that is a date. If I had more columns with dates, it’ll bring it up. Because I’ve only got one date column, it gives me only one option, click that press okay. And here we have it, how nice is this? So the order date is the field name there. And if you scroll all the way to the left there, we have Jan, 2012 all the way to December, 2014. And that is the range that we have here. So that’s the data range that we have from 2012 to 2014. And it shows it here. These are the available filters that we have based on our data. And you can expand that and make it bigger like this. And so you can scroll all the way there. And let’s choose January, February and see how it changes. And here it gives you the option to expand and include other months. So we can do the first quarter in January. And you see, when I did that, it says Q1 2012. Let’s click on April and hold down the left mouse key. And it automatically puts Q2 over there. Now let’s clear to filter here, and let’s go if we want by years. So it automatically puts it by years, and you can say 2012, 2013, 2014. Let’s put it by quarters. And let’s go Q1 two, three, four, and you can highlight all that. Let’s clear the filter, let’s go to months and it gives us the months. And then we go all the way down to days, all the way down to days. Day one from January. So this is really good filter if you wanna drill down and expand on your analysis, this is a great, great tool and a great feature in Excel 2013. Now let’s go back to quarters over here. And just sort of timeline tools. When you click on that and click out, let’s click back into it. It gives us a timeline tools option here, and we can color it like a slicer. We can use different slicers as there with different colors. And we had several other timelines, we can use this report connections to connect them. That’s creating a dashboard. And I talked about that in previous chapters. So if you have different timelines slicers, then you can connect them and create an interactive dashboard. Now you can move the height, the width, include the header title, get rid of that, the selection label, the scroll bar, and also the time label. So different stuff there. This is very, very nice, I like it. And you can also create a new timeline style, by clicking in there. And we talked about how you create slicer styles. The same thing applies here to timelines. This is a great feature. Go for it, insert it, play around with it and wow your boss. (upbeat music) An Excel data model is new in Excel 2013. And it allows you to take information from different Excel tables and create a Pivot Table from it. Now, before this, you had to use VLOOKUPs or SUMIFs, and it got a bit messy, but if there’s a relationship between each of the tables, then you can create a data model. So we have an Excel tab here, and if you click on it and go to the design, it’s called sales data. The same thing here for customer, are called the customer data and product are called the product data. So let’s go to the sales here. So this has, if we scroll all the way down, it has nearly 50,000 transactions. So these are daily transactions and it’s usually what we download from our ERP system. And it has a product key and a customer number. Now the customer number here, you can see it’s depicted by 1001 all the way to 1010. And in our customer table here, we have the customer numbers, 1001, all the way to 1010. And these are distinct values. Now, if these are distinct values, then we can create a relationship. If we had, for example, two rows with 1001 and a different customer name, then this wouldn’t work. For a data model to work, one of the table has to have distinct values. And the other one, for example the sales can have as many values as it wants. So this is the one to many relationship. So the one is this unique Excel table here with the unique customer numbers. And then the many is the sales transactional Excel table with many customer numbers. So we have customer number here and we can create a relationship within the customer here. Now we also have a product key here. So we have a product key. It goes all the way down from one to 20. And then our product table, we have these unique entries and that means that we can create a data model relationship. Now to do this, let’s click in any one of our tables. Let’s click sales and go to insert, and a Pivot Table. And we get our create Pivot Table dialog box. Now, what I can do is put in here, add this to the data model and press okay. So you can see here, it’s loading to the data model. So that loads it all the way there into the data model. And if you got it all. Now in all, we have all the different tables that are available so now for us to create a Pivot Table. So we created a data model and what we need to do now is to create a relationship. So to create a relationship under analyze and relationships, and go to new. Now, the table here is the table that has all the transactions. So that’d be the sales down here. So let’s click on the sales data and let’s create a relationship. So we said that the customer number is unique to sales and also to the customer table. Now the related table will be the customer data. And the related column will be the customer number in this Excel table there. Now the primary key is the table that has the unique identifiers. If there are any duplicates in there, it’s not gonna work. So this is the primary means of the one. The foreign means many, so it’s a one to many relationship. So if you ever get confused, always put your Excel table that doesn’t have duplicates into the primary area. And then if you have a sales data table which has many rows, then obviously we’ll have duplicates, put it into the foreign area. Now let’s press okay. So that’s created that relationship. Let’s add another one. Let’s go to new, so our sales data, we’re going into the many side, which is the foreign side, and we’re gonna put the product key now because we’re gonna relate it to the product data Excel table. And then in here, the product key was the unique identifier. So it’s one to many relationship, and press okay. Now you see when I did that here on the right-hand side, that the top of this diagram went gray. That means that there is a relationship and is now loaded to the data model. Then I wanna change this around here, just so again for our purposes. Okay, so we can see it much better, and that’s great. So now all we can do is get the sales data, the sales amounts from the sales, that will bring the values there. And we can get another field in here. We have the product key in the sales item, but we don’t know where the product name is. Because of the product key and the product key are related here, that and that are related, we can get any of these fields and drop them in here and create a Pivot Table analysis. So let’s get a product name and then let’s put it in the row labels. And you can see that it shows us the sales per product name. So it’s taken two Excel tables and created a Pivot Table from that. And without using any VLOOKUP. We can also go in here and put in a customer name if we like, because we’ve said the name is linked to the customer number. So if the customer number and the customer number here, are linked then we can take any of these fields and bring them into our analysis. Let’s put in the name in the columns area and there you have it over there. Let’s just put that over there. And that’s our analysis that we have our three Excel tables that are linked together, and we can choose which fields to use because they’re all related to each other, and it gives us the power to do all this great analysis. (upbeat music) A new feature in Excel 2016 is the ability to auto-group a date column. Now we have our table here and we have our order date there. Now let’s create a Pivot Table and I’ll show you how this works. Let’s got to insert Pivot Table and a new worksheet, and we have here our, let’s make it a little bit bigger. Okay, so you can see. Okay we have our order date there and let’s put in sales first in there. So let’s put in the order date in the rows and have a look at what’s gonna happen. It automatically grouped into years, quarters, and it’s got our order date in there as well. So in our Pivot Table, we can expand here and we say the quarters, and we’ll get them to go deeper into the months. So this is a great feature and it saves you the hassle of right-clicking in a date and then choosing the group. Now this automatically groups, and it’s super, super awesome feature they’ve added in Excel 2016. And if you don’t like this, then you can just right-lick and press ungroup, and it’ll bring everything back in there and get rid of the years and quarters. Now let’s right-click and group and put it like this as it was before. So if there are multiple years, the years will come up and then you have your quarters and you have your original data field there. So a great feature in Excel 2016. (upbeat music) In the previous versions of Excel, when you had to select a slicer and you wanted to select say a second or third slicer, you had to hold on Control key. So I’m holding the Control key and pressing Asia and Europe. You see that? Now we’ve Excel 2016, this icon here which is multi-select, so you can press that and then you can left-click with your mouse without holding the Control key, and it selects multiple items. (upbeat music) A new feature in Excel 2016 is the ability for pivot charts to expand or collapse its data. Let me show you an example. Click in our Excel table and go to insert and pivot chart, and let’s press new worksheet and just press okay. So let’s put in our sales in our values area, and let’s put in our products in our axes. And then when we put in two or more fields in one of our axes or legend series, then it gives us the ability to zoom in or zoom out. So I’ll show you that. When I put this and you see in the bottom right-hand corner, the plus and minus sign. So it’s put in the sales region in there. So you can see the collapse field, you can collapse that. And also the Pivot Table gets collapsed, or you can expand it and then see all the details in there. So this is great if you just wanna show two different scenarios, when you’re doing a presentation to your boss. (upbeat music) Now if your data has geographical fields such as addresses or postcodes, you can build a Pivot Table on a map by using the 3D maps icon on the insert tab. So we have postcodes here for US, and they’re all the way down there. So you’ve got different postcodes and what we need to do is go to insert and 3D map here. And we can put in a new tour. And you can see here, it’s put in our postcode if we zoom in there, the different postcodes that we have located. So it shows us where our values are located. So where our sales are located. Now in the height here, we can add a values field. So click on that and put in our sales. So you can see that from in here, let’s just bring this down here and we can get rid of that, and just bring it up to there. So we can see that because we chose a stack column. It shows us a stack column like this, which is a little bit weird. And then we have the bubble and then the heat map, which is a little bit better, which shows us where our most sales are. So whatever he has has a dark red there, it means that there’s a lot of sales there. So this is pretty cool in Excel 2016. If you have addresses or zip codes, it uses Bing to visualize a map. And it just gives you another way where you can visualize your data to your management team. And I think they’re gonna be very impressed. (upbeat music) So Excel introduced many wonderful new features in its update in Excel 2019. And before we get into them, I like to just let you know which Excel version that you currently have, because a lot of people get confused, every three years there’s a new update. So they get confused and they don’t know what Excel version they actually have. So I will just quickly show you how you can check which Excel version you’re currently using. Now I’m using Excel Office 365. With that, I get the new updates when they are released. So when Excel 2019 was released, then automatically I got all those features. But if you purchase the one time license for Excel 2019, then you will also have these new features. So I’m just gonna let you know how you can check which Excel version that you have. So you need to go to file and then account, and then about Excel over here on the right hand side. Now in here, it’ll say Excel for Office 365, because I’m on the subscription model. If you have Excel 2019, it’ll here Excel 2019. If you have any other version like 2016, 2013, 2010, it’ll say that up here. So being Office 365, I always get the new versions updated. So therefore being on this subscription model, I have the latest version, which means I have Excel 2019. You can also check below. I have a link that goes to my blog and explains the different Excel versions and how to check them. It just makes it easier for you to find which Excel version that you’re using. (upbeat music) Over the last few years, I’ve held many Pivot Table webinars, and I get lots of questions in the webinar chat. And one of the most common questions is how can I make my Pivot Table layout a default layout? So every time I create a Pivot Table, it shows me the layout that I want and not the default layout that Excel gives. Thankfully in Excel 2019, this feature is finally available. So you can personalize the default Pivot Table layout. Now I’ll show you what I mean. We have a data source here and I’m just gonna create a Pivot Table. So I got to insert, Pivot Table and put it into a new worksheet and press okay. And I’m just gonna create a Pivot Table here, and it’s going to create a default Pivot Table layout based on Excel’s options. So let’s put in our customer in here, and we’ll put in our products. Now let’s get our order date in the columns area. And now let’s get the sales in the values area. So this is it, this is Excel’s default Pivot Table layout which is in a compact form. And you can see that the sub-totals on the top here. Okay, so the sub-totals on the top and then the values at the bottom. And you can see the grand total is in the rows and in the columns here. But some people may not want this ’cause is confusing. Because normally when you’re adding these up, this is what the value should be, should be at the bottom, the sub-total should be at the bottom. And in previous lessons I’ve showed you how you can do that. You can just go to the design and go to the report layout and you can change it all here in compact outline tabular, repeat all items, grand totals, there you go it’s all there. And the sub-totals as well. You also got the blank rows. So this is how you can change it, but you can actually predetermine the layout. So each time you create a Pivot Table in the future, Excel knows the layout that you like and it’ll always show you that layout. So let’s get into it. To do this, you gotta go to file and then go to options. And under data, you’ve got this one here, you’ve got edit default layouts and make changes to the default layer of Pivot Tables. Click on that. The sub-totals, we want to at the bottom, we don’t want them at the top. The default is show all sub-totals at top of group. It makes no a sense for me. I wanna put it at bottom of group. Grand totals on for rows and columns, yes, I like that. Let’s keep that. Report layout showing compact form. I personally like this, but a lot of people wanna show it in a tabular format or in the outline format. Let’s put an eight tabular form. Now you have many other things you can do. You can insert blank line after each item if you like, you can repeat all item labels and you can include filter items in totals. Now there are more options here. So I’m just gonna unclick that and go to Pivot Table options. And in here, layout and format, whatever you do here, it’s gonna affect the layout. So if you have any error values, you can put in a zero or N/A. And for empty cells, you can put any number that you like. The same thing here. So totals and filters, display, printing, and data. And we go through this in the earlier lessons of this course. So any changes you make here, it’s gonna affect this here. I’m just gonna leave it the same now. Okay. So I’m just gonna press okay. And these are the changes that were made. We made two changes. Show all sub-totals at the bottom of group, and also the report layout should be in tabular form. Now let’s make a third one. Let’s insert a blank line after each item, just to make it a little bit different, and press okay, and then press okay. Now it hasn’t taken shape because you need to create a new Excel Pivot Table. So let’s go in here again. Click on there, insert Pivot Table, new worksheet. Let’s put the customer in there. The products as we had before, the order date in the columns, and now have a look at it. You see, it’s taking shape, it’s a different shape, isn’t it? Let’s put the sales in here. There you go. So as you can see here, it has made these changes. It’s put in the sub-totals at the bottom of the group. It’s made it into a tabular format as you can see here, you can compare to the earlier version, it’s in compact, so everything is in one column. Tabular means it just expands that out into two columns. And then it has a values there. And we’ve also added a blank line after each item. So it looks much better. And each time you open your Pivot Table report or any Excel workbook, and you input data, and you create a Pivot Table, this layout, the default layout that you tell Excel is going to show all the time. So this is awesome, it’s gonna save you a lot of time. (upbeat music) Another cool feature in Excel 2019 is the automatic relationship detection in your Excel tables and in your Excel Pivot Table. Now Excel knows when your analysis requires two or more tables to be linked together and it notifies you. Now with one click, it does all the work to build the relationships so you can take advantage of them straight away. Before you go any further into this tutorial, it is a must that you watch the video that I did in the new Excel 2013 features. It is for the data models. So I’ll suggest you go and watch that video now. So you can have a look at how you can do this data relationship manually. So pause this, go back into chapter 15.5 data models, have a look at it and come back when you’re finished. All right, so I hope that you got lots of value from that video tutorial. And it just goes to show you what data model is and the relationships and how to create them manually. There’s a bit of work involved, but in Excel 2019, they’ve made this a lot easier. Now we have the same data source as the tutorial that you saw previously in 15.5 called Data Models. We have the sales here, as you can see. These all are transactions, about 50,000 transactions. And this is the many transactions that we have, and these are the one or the unique. So this is the one to many, and the product is one to many. So as I said before, under the customer table, we have the unique values to do a relationship. You can have unique values here. If you had two rows with the same number 1001 and 1001, it’s not gonna work. So these values have to be unique. And this table here also has unique values for the product key. Now to do this auto relationship detection, we have to do the same thing. Go to insert Pivot Table and just click here, add this to the data model and press okay. And it automatically will add all the tables in this workbook in the data model. We know this because if you go to all here and we just hover over here, you can see the data source, the name, table, it’s customer data. That’s a good name there, and it’s model table name. So that’s in the data model. We click on there, and it’s a model as well and that’s a model. So it’s created the tables into the data model. So now instead of going to relationships and new, we can press auto-detect, but this is not the best way to do it, ’cause if we do this now, it’s not gonna know anything. So we’ll need to put in some values in here first. In the sales data, let’s put in the sales amount in here first and the product data, we said that the product key and the product key are connected. But we can put anything in here from the product data. It doesn’t have to be product key, it could be product name, product costs. So we can put in any of these items in here. So let’s put in our product name in the columns in there. And this message comes up. Relationships between tables maybe needed. Instead of creating, let’s go to auto-detect. And it says one new relationship created, perfect. Let’s go to manage relationships. And we’re gonna see that the product key and the product key are going to be in that relationship. So click on that and go to edit. As you can see here in the foreign is product key and the primary is a product key. This is the one to many relationships, and these are the tables that got the relationships from. So it detected it, it’s awesome. So you don’t have to manually go and click this table like we did previously in Excel 2013 and then put in the relational column. So you didn’t have to do that. It’s just automatically does that for you here. So that’s perfect. All of these press okay and close it. There it is there. Let’s do the same thing for the customer data table. As we said in the previous video, customer number and customer number are related, and we can put in anything in here. We can put in the address, the city, the country. Let’s put in the country, let’s put it in the rows in there. Now another message that comes up, let’s press auto-detect. It says one is created, manage relationships, Now let’s go in there again and click edit and you see the customer number that is a related column. It’s perfect, we like it. Press okay and close. And as you can see here, the data changes and it has automatically created relationships for us. We didn’t have to go create it, it’s a great new feature. You should go and give it a try and practice, and once you have data that is all related, you can create some awesome Pivot Table reports without using VLOOKUP or SUMIFs. Data model is great. It’s gonna make your life easier and you create much more enhanced reports, which is gonna make you a data wiz. (upbeat music) In Excel 2016, Microsoft introduced the automatic grouping of dates. And that was an awesome feature where you can just drag your data field into the Pivot Table, and it automatically puts it into months, quarters and years. Now, you can see that tutorial in the Excel 2016 tutorial videos that I have for you. And in Excel 2019, they have gone one step further and they’ve included automatic grouping of time. In our data set here, we have the time of order as you can see here all the way there, and we can actually group this automatically. Let’s give it a go. Let’s go to insert, and Pivot Table and press okay. And we have here our Pivot Table, and we’re gonna get our time of order and put it in our rows. Once we do that, you bring this on the left, the automatic grouping of the time. All right. So then you see there from 12:00 a.m. all the way down to 11:00 p.m., beautiful. And if you click on there, you can see that it is grouped into minutes as well. And you can see here that it automatically puts it into hours and minutes. It’s created this hours group and also the minutes group. And you can also see it here. So it’s automatically created new fields for us. And that is just awesome just with drag and drop ease. Now let’s put in our sales in here and we can see that the sales values are grouped into the time that the order was made. So you can do a lot of analysis on there. You can have a look at what is your best time where most of the orders come in and go into that data and give it to your boss and you’ve got some great and awesome insights there just with drag and drop ease. Now, if you don’t want this option to be automatic, you can switch it off. Go to file, options, and under data you’ve got here, disable automatic grouping of date or time columns and Pivot Tables. So if you click on that and press okay, the next time you drag a date or time field into your Pivot Table, it’s not gonna automatically group. But I suggest having this checked off and it’s just gonna make your Pivot Table slicker, and you’re gonna be able to analyze your data much, much quicker. So there you go. Automatic time grouping in Excel 2019 and Office 365. So give it a go and see what you can come up with.
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