The provided text serves as a comprehensive set of lecture notes on Python programming. It begins with fundamental concepts like reserved words, assignment statements, and basic program structure. The notes progress to cover conditional execution, functions, file handling, and data structures, including lists, dictionaries, and tuples. Later sections discuss regular expressions and object-oriented programming concepts, with a focus on terminology rather than in-depth coding. The material also contains practical code examples for data analysis, such as word counting and visualization, demonstrating the application of these concepts in real-world scenarios. Finally, it walks through the construction of visualizations including word clouds and line charts.

Python Programming Study Guide

Quiz

1. What is an “if” statement used for in programming? An “if” statement is used for conditional execution of code. It allows a program to make a decision based on a true/false condition, executing a specific block of code only if the condition is true.
2. Explain the purpose of the “while” keyword in Python. The “while” keyword in Python creates a loop that executes a block of code repeatedly as long as a specified condition remains true. Once the condition becomes false, the loop terminates, and the program continues with the next line of code after the loop.
3. What are constants in Python? Constants are values that do not change during the execution of a program. They can be numbers, strings, or other data types, and they are used to represent fixed values in calculations or comparisons.
4. What are variables in Python? Variables are named storage locations in memory used to hold values that can change during program execution. They allow you to store and manipulate data within your program, and their values can be updated as needed.
5. Explain the difference between integer division in Python 2 and Python 3. In Python 2, integer division between two integers would truncate the decimal portion, resulting in an integer result, while in Python 3, integer division between two integers always produces a floating-point result. This change makes division more predictable in Python 3.
6. What does the “else” statement do in conjunction with an “if” statement? The “else” statement provides an alternative block of code to be executed if the condition in the “if” statement is false. It ensures that one of two blocks of code will always be executed, depending on the truthiness of the “if” condition.
7. What is the purpose of the “elif” keyword in Python? The “elif” keyword allows for multiple conditional checks in a single “if” statement. It provides a way to check additional conditions if the previous “if” or “elif” conditions were false, creating a multi-way branch.
8. Explain the concept of a function call and return value. A function call is the act of executing a defined function, passing arguments to it if necessary. The return value is the result that a function sends back to the calling code after it has finished executing, which can be used in expressions or assigned to variables.
9. What are definite loops? Definite loops iterate through the members of a set.
10. Explain how try and accept blocks work. Try and except blocks are a method of handling dangerous code. Place dangerous code in the try block and if the program would trace back (quit) that code jumps down into the accept block, executing that code instead.

Quiz Answer Key

1. An “if” statement is used for conditional execution of code. It allows a program to make a decision based on a true/false condition, executing a specific block of code only if the condition is true.
2. The “while” keyword in Python creates a loop that executes a block of code repeatedly as long as a specified condition remains true. Once the condition becomes false, the loop terminates, and the program continues with the next line of code after the loop.
3. Constants are values that do not change during the execution of a program. They can be numbers, strings, or other data types, and they are used to represent fixed values in calculations or comparisons.
4. Variables are named storage locations in memory used to hold values that can change during program execution. They allow you to store and manipulate data within your program, and their values can be updated as needed.
5. In Python 2, integer division between two integers would truncate the decimal portion, resulting in an integer result, while in Python 3, integer division between two integers always produces a floating-point result. This change makes division more predictable in Python 3.
6. The “else” statement provides an alternative block of code to be executed if the condition in the “if” statement is false. It ensures that one of two blocks of code will always be executed, depending on the truthiness of the “if” condition.
7. The “elif” keyword allows for multiple conditional checks in a single “if” statement. It provides a way to check additional conditions if the previous “if” or “elif” conditions were false, creating a multi-way branch.
8. A function call is the act of executing a defined function, passing arguments to it if necessary. The return value is the result that a function sends back to the calling code after it has finished executing, which can be used in expressions or assigned to variables.
9. Definite loops iterate through the members of a set.
10. Try and except blocks are a method of handling dangerous code. Place dangerous code in the try block and if the program would trace back (quit) that code jumps down into the accept block, executing that code instead.

Essay Questions

1. Explain the significance of indentation in Python and how it affects the structure and execution of control flow statements like “if,” “else,” “elif,” “while,” and “for” loops. Provide examples to illustrate how incorrect indentation can lead to errors and unexpected program behavior.
2. Compare and contrast definite and indefinite loops in Python, providing examples of when each type of loop is most appropriate. Discuss the use of “break” and “continue” statements within loops and how they can alter the flow of execution.
3. Describe the concept of loop idioms and their importance in solving common programming problems. Provide detailed examples of how loop idioms can be used for tasks such as finding the maximum or minimum value in a list, summing elements, and searching for specific patterns.
4. Discuss the different ways to open and read files in Python, including the use of file handles, “for” loops to iterate through lines, and the “read” method to read the entire file content. Explain how to handle newlines and white space when processing file data, and describe the use of “try” and “except” blocks for error handling.
5. Explain how dictionaries are used in Python, including how to create, access, and modify key-value pairs. Discuss the purpose and usage of the .get() method and how it simplifies conditional logic when working with dictionaries. Illustrate how dictionaries can be used to count word frequencies in a text file and find the most common word.

Glossary of Key Terms

• Conditional Execution: Executing a block of code only if a specific condition is met (true).
• Indentation: The spacing at the beginning of a code line. In Python, it is used to define the block of statements, and it is vitally important.
• Loop: A programming construct that repeats a sequence of instructions until a specific condition is met.
• Iteration Variable: A variable that changes with each iteration of a loop, often used to control the loop’s execution.
• Constants: Values that do not change during program execution.
• Reserved Words: Special words in a programming language with predefined meanings (e.g., if, else, while, for, def).
• Variables: Named storage locations that can hold values that change during program execution.
• Concatenation: Joining two or more strings or lists together.
• String Slicing: Extracting a portion of a string using indices.
• Function Call: Executing a defined function with optional arguments.
• Return Value: The value returned by a function after it has finished executing.
• Argument/Parameter: A value passed into a function.
• Indefinite Loop: A loop that continues executing until a specific condition is no longer met. Also known as while loops.
• Definite Loop: A loop that executes a predetermined number of times. Also known as for loops.
• Break Statement: A statement that terminates the current loop and transfers control to the next statement after the loop.
• Continue Statement: A statement that skips the rest of the current iteration of a loop and proceeds to the next iteration.
• Loop Idiom: A common pattern for constructing loops to accomplish specific tasks, such as finding the maximum or minimum value, summing elements, or searching.
• File Handle: A variable that represents an open file object, used for reading or writing data to the file.
• Try/Except Block: A construct used for error handling. The code in the try block is executed, and if an exception occurs, the code in the except block is executed.
• Dictionaries: Key-value pairs.
• Keys: Value that is associated with an element.
• Values: Value of an element.
• Mutable: Changeable.
• Concatenate: Adding sets together.
• Tuple: Like a list but with parentheses.
• Junction Table: A table that facilitates many-to-many relationships.

Python Programming Fundamentals: An Overview

Here’s a briefing document summarizing the main themes and ideas from the provided text excerpts.

Briefing Document: Python Programming Fundamentals

Overview:

The provided excerpts offer an introduction to fundamental concepts in Python programming. The material covers program structure, data types, control flow (conditional execution and loops), functions, strings, lists, dictionaries, tuples, file handling, and an introduction to SQLite database interaction. The overall theme is building a foundation for understanding and writing basic Python programs.

Key Themes and Ideas:

1. Program Structure and Control Flow:

• Sequential Execution: Code executes line by line, from top to bottom.
• Conditional Execution (if/else): The if statement allows code to be executed selectively based on a true/false condition. elif extends this to multi-way branching, executing only one branch within a block.
• “So, inside the if statement, right here, there is a question, saying, is x less than 10? That’s a, that resolves to a true or false… If it’s false, skip that code.”
• “And the way it works is it’s probably best to look at this here, where it checks the first one, and if it’s a true, then it runs that, and then it’s done. It doesn’t check them all.”
• Loops (while/for): Loops allow code to be repeated. while loops continue as long as a condition is true. for loops iterate over a sequence of items (e.g., numbers, strings, lines in a file).
• “This is repeated over and over and over and over again, and this is the essence of how we make computers do things that are seemingly difficult, while they’re more naturally difficult for people”
• “As long as n remains greater than zero, keep doing this indented block”
• Indentation: Python uses indentation to define code blocks, crucial for if statements, loops, and function definitions. Incorrect indentation leads to errors.
• Loop Control (break/continue): break exits a loop prematurely. continue skips the rest of the current iteration and goes to the next.
• “And if you hit the break, it exits the innermost loop out to the place beyond the end of the loop.”
• “Continue effectively says stop this iteration. We’re done with this iteration.”

1. Data Types and Variables:

• Constants: Values that don’t change (e.g., numbers, strings).
• “These are just things we call constants because they don’t change, they’re numbers, strings, et cetera.”
• Variables: Named memory locations that store values.
• “Variables are the third building block, and that is a way that you can ask Python to allocate a piece of memory and then give it a name”
• Data Types: Common types include integers (int), floating-point numbers (float), strings (str), and Booleans (bool). Python is sensitive to data types.
• “Type error can’t convert int object to str implicitly. So, that’s an integer right there, and that’s a string, and that’s what it’s complaining about, that little bit right there.”
• Type Conversion: Functions like int(), float(), and str() are used to convert values between data types.
• “You can also use a set of built-in functions, like float and int, to convert from one to another.”
• None: A special type with a single value (None) often used to indicate emptiness or the absence of a value.
• “But none type has one value, none. None is a constant. Capital none is a constant… None is often used to indicate emptiness.”

1. Operators:

• Arithmetic Operators: +, -, *, / perform mathematical operations. Division in Python 3 always produces a floating-point result.
• “Integer division produces a floating result in Python 3.0, not in Python 2.0. That is an improvement in Python 3.0.”
• String Operators: + concatenates strings.
• “We can also use this plus to concatenate two strings.”
• Comparison Operators: ==, !=, <, >, <=, >= compare values.
• Logical Operators: and, or, not combine Boolean expressions.
• Membership Operator: in checks if a value exists within a sequence (string, list, etc.).
• “We can use in differently as a logical operator, so we’re using it as an iteration structure in for loops, but we can also use it as a logical operator in if statements.”
• Identity Operator: is and is not check if two variables refer to the same object in memory. They are stronger than ==. Recommended for use with Booleans and None.
• “It is stronger. Double equal says are these things equal in type and value? …So is is stronger than equals, meaning that it demands equality in both the type of the variable and the value of the variable.”

1. Functions:

• Built-in Functions: Python provides many built-in functions (e.g., print(), len(), type(), max(), min(), sum()).
• User-Defined Functions: The def keyword defines a function. Functions can accept arguments (parameters) and return values. return exits a function and specifies the return value.
• “We use the def keyword to define a function and then later we’re gonna invoke this and there’s a bit to it…It starts with a def keyword”
• Function Invocation: Calling a function executes its code.

1. Strings:

• Indexing: Individual characters in a string can be accessed using square brackets (e.g., fruit[0] for the first character). Strings are indexed starting from zero.
• “So fruit is a variable that contains the string banana, and then fruit sub one is the character that’s in position one.”
• Slicing: Extracting substrings using [start:end]. The end index is exclusive.
• “S sub zero through four says, start at position zero, and then go up through, but not including four, right? So we don’t include four.”
• Immutability: Strings cannot be changed after they are created. Operations like lower() create new strings.
• “Strings are not mutable. So if I take a look at assigning banana into fruit, well, fruit sub-zero is a capital letter B…it turns out that strings are not mutable, meaning they’re not changeable once you create them.”
• String Methods: Functions associated with string objects (e.g., strip(), startswith(), find(), lower()).

1. Lists:

• Definition: Lists are ordered collections of items enclosed in square brackets ([]). Lists can contain items of different data types.
• “Lists are really a lot like arrays, but they’re surrounded with these square braces, like that. So the square braces are what defines a list.”
• Mutability: Lists can be modified after creation (elements can be changed, added, or removed).
• “Lists are mutable. Mutable is another word for changeable. They can be changed”
• Indexing and Slicing: Similar to strings.
• List Methods: Functions associated with list objects (e.g., append(), sort(), remove(), insert(), pop()).
• List Operations: + concatenates lists.
• Built-in Functions: len(), max(), min(), sum() can be used with lists.

1. Dictionaries:

• Definition: Dictionaries are collections of key-value pairs enclosed in curly braces ({}). Keys must be unique and immutable (e.g., strings, numbers).
• “Dictionaries are not sequential, they are just sort of a bag of stuff, and when you want to get something out of it, you look it up with a label”
• Accessing Values: Values are accessed using their corresponding keys (e.g., dictionary[‘key’]).
• Adding/Updating Pairs: New key-value pairs are added, and existing values can be updated.
• get() Method: Provides a way to retrieve a value associated with a key, with an option to specify a default value if the key doesn’t exist.
• “The get says in its first parameters, the key to lookup…and 99 is the default value that we get if the key doesn’t exist.”
• Looping through Dictionaries: Using .items() provides access to key-value pairs for iteration.

1. Tuples:

• Definition: Tuples are ordered, immutable collections of items enclosed in parentheses ().
• Immutability: Once created, tuples cannot be changed.
• Use cases: Tuples are often used for representing fixed collections of data.

1. File Handling:

• open() Function: Opens a file and returns a file handle object.
• “So then you have to use the open command… And the name of the file, which we put it in quotes. It’s really kind of a string and then this little r means read.”
• Reading a File: Files can be read line by line (using a for loop) or as a single string (using read()).
• “But the most common way that we’re gonna read through the file is to treat it as a sequence of lines… we use the for loop and we have an iteration variable… Python doesn’t know anything special by naming that variable line.”
• strip() Method: Removes whitespace (including newlines) from the beginning and end of a string.
• “Thankfully, as we saw in the previous chapter, there is a nice little function in Python for strings called strip that allows you to throw away white space.”
• Error Handling (try/except): Handles potential exceptions (e.g., FileNotFoundError) that might occur when opening a file.
• “We took out insurance on it, and we know that it might blow up, and so we have it in a try and accept block.”

1. Loop Idioms:

• Largest/Smallest Value: Finding the largest or smallest element in a sequence using a loop and a “largest_so_far” or “smallest_so_far” variable.
• “So I have this variable called largest so far, I set it to negative one, before the loop…If nine is greater than largest so far, well largest so far is negative one, so that’s true, so this code’s gonna run.”
• Counting: Counting occurrences of items or lines that meet a certain criteria using a loop and a counter variable.
• Summing: Adding up values in a sequence using a loop and a running total variable.
• SQLite Database InteractionUse import sqlite3 to interact with SQLite databases.
• Establish database connections.
• Create tables using SQL.
• Insert, update, delete, and select data.
• Utilize parameterized SQL to prevent SQL injection.
• Implement error handling and transaction management.
• Foreign key relationships: connect tables by referencing primary keys in other tables, enforcing data integrity.
• Junction tables: implement many-to-many relationships by having a table with foreign keys to the tables related.
• Foreign keys: “So I have the title artist ID. This is the foreign key to the artist table. And I got this value that I just moments ago retrieved.”

Important Considerations:

• Python’s Readability: The excerpts highlight Python’s emphasis on readability and ease of use, particularly in file handling and loop construction.
• Debugging: Tracebacks provide information about errors, helping to identify and fix problems.
• Code Style: The use of mnemonic variable names and consistent indentation improves code clarity.
• Iteration Variables: The use of singular and plural is common to better understand what the code is working with (e.g., friends (list of friends) and friend (an element in that list)).

This briefing document summarizes the core concepts. Further study and practice are essential for mastering Python programming.

Python Programming Fundamentals

Programming Concepts and Constructs

1. What is conditional execution in Python, and how is it implemented? Conditional execution allows a program to execute different code blocks based on whether a condition is true or false. In Python, it’s implemented using the if statement, optionally with elif (else if) and else clauses. The if statement evaluates a boolean expression, and if it’s true, the indented block of code following the if is executed. If it’s false, the code block is skipped. elif allows you to check multiple conditions in sequence, and else provides a default block to execute if none of the previous conditions are true. Only one of the branches (the if, an elif, or the else) in a conditional block will ever run in a single execution.

2. What is a loop, and what are the two main types of loops in Python? A loop is a control flow statement that allows code to be executed repeatedly. The two main types of loops in Python are:

• While Loop: Continues to execute a block of code as long as a condition is true. It is considered an indefinite loop because the number of iterations isn’t known beforehand. The loop continues until the condition becomes false.
• For Loop: Iterates over a sequence (like a list, tuple, string, or range) and executes a block of code for each item in the sequence. It is considered a definite loop because the number of iterations is determined by the length of the sequence.

3. What is the purpose of the break and continue statements within loops?

• break: Immediately terminates the loop and transfers control to the statement immediately following the loop.
• continue: Skips the rest of the current iteration and resumes execution at the next iteration of the loop.

4. What are constants and variables in Python, and how do they differ?

• Constants: Values that do not change during the program’s execution (e.g., numbers like 123, 98.6, or strings like “Hello World”).
• Variables: Named storage locations that can hold values. These values can be changed during the program’s execution using assignment statements. Variables are created when a value is first assigned to them.

5. How does Python handle data types, and what are some common data types? Python is dynamically typed, meaning the data type of a variable is determined at runtime and can change. Common data types include:

• Integer (int): Whole numbers (e.g., 1, 100, -5).
• Floating-point number (float): Numbers with decimal points (e.g., 3.14, 2.5, -0.01).
• String (str): Sequences of characters enclosed in quotes (e.g., “hello”, ‘world’).
• Boolean (bool): Represents truth values, either True or False.
• NoneType (None): Represents the absence of a value. The only value of this type is None. Python provides built-in functions like type() to check the data type of a variable or value, and functions like int(), float(), and str() to convert between data types.

6. What are functions in Python, and how are they defined and called? Functions are reusable blocks of code that perform a specific task. They promote modularity and code reuse. Functions are defined using the def keyword, followed by the function name, parentheses (optionally containing parameters), and a colon. The function body is an indented block of code. Functions are called by using their name followed by parentheses, passing arguments if necessary. A function can return a value using the return statement.

7. What is a list in Python, and how does it differ from a string? A list is an ordered, mutable (changeable) sequence of items. Lists are created using square brackets [] and can contain elements of different data types. Strings are sequences of characters, but are immutable. Lists can be modified after creation (e.g., by adding, removing, or changing elements), while strings cannot be changed directly.

8. What is a dictionary in Python, and how is it used? A dictionary is an unordered collection of key-value pairs. Each key must be unique, and the value can be of any data type. Dictionaries are created using curly braces {}. Dictionaries are useful for storing and retrieving data based on a key. You can add, remove, or modify key-value pairs in a dictionary. They’re particularly useful for tasks like counting the frequency of items in a sequence or storing configuration settings. Dictionaries are particularly useful for accumulating data when processing files.

Python Vocabulary and Reserved Words

The sources talk about vocabulary in the context of learning Python. Here’s a summary:

• When learning Python, it’s helpful to start with a basic vocabulary.
• Reserved words are a key part of the Python vocabulary. These words have specific meanings to Python and cannot be used for other purposes. Examples of reserved words include and, or, del, and if.
• Python looks at reserved words the same way a dog responds to the word “walk”. When Python sees a reserved word, it knows exactly what it means.
• When choosing variable names, it can be helpful to make them descriptive so that others can easily understand the code. Using descriptive names is also called using mnemonic variable names. Python is happy with any variable name.
• It’s important to choose variable names carefully to help readers understand the code.
• Python doesn’t understand singular and plural forms of variable names.
• Comments are also important for humans to read to understand what the code does. Comments in Python are added with a #.

Python Syntax Overview

Here’s a discussion of Python syntax, drawing from the sources:

• Translation: Python code is translated into machine language (zeros and ones) for the microprocessor to execute. Python acts as a translator.
• Installation: To get started, you need to install both Python 3 and a programmer’s text editor. A programmer’s editor is needed instead of a word processor.
• Running Code: Python code can be run in the command line, and the command cd tells you where you are in the folder. Code can be saved in a file with a .py suffix. In Windows, typing first.py will run the code.
• Errors: Syntax errors indicate that Python doesn’t understand what you’re trying to say.
• Statements: A Python program consists of a series of statements or lines that the computer executes in order, from beginning to end.
• Vocabulary: Python has reserved words that it recognizes, and these words cannot be used for other purposes.
• Variables: An assignment statement uses an equal sign, but this should be thought of as an arrow. For example, x = 2 means that the value 2 is assigned to the variable x. Python’s job is to remember the variable. Variable names can start with a letter or underscore, but it is bad practice to only differentiate variable names by case.
• Operators: Operators, such as + and =, perform actions. The + operator can add integers or concatenate strings.
• Types: Python is able to determine the type of data. The type() function can be used to ask Python about the type of a variable or constant. There are different types of numbers, such as integers and floating point numbers. You can convert between types using built-in functions such as float() and int().
• Comments: Comments are added to Python code using a pound sign (#). Python ignores everything after the pound sign.
• Conditionals: Conditional steps can be performed using if statements. Comparison operators include == (equal to), >=, <=, >, <, and != (not equal). Indentation is very important in Python to indicate blocks of code. Four spaces are normally used for each indent. After an if, you must indent.
• else: if statements may be followed by else.
• elif: Multiple conditions can be checked using elif.
• Try/Except: try and except are used for error detection.
• Functions: Functions are defined using the def keyword.
• Strings: Strings can be concatenated using the plus sign. Individual characters in strings can be accessed using indexing, starting at zero. There are many string methods available, such as lower(), upper(), find(), replace(), and strip().
• Files: Text files are a sequence of lines. To read a file, you must call the open() function, which returns a file handle. The newline character (\n) indicates the end of a line.
• Lists: Lists are a collection that can hold more than one item, which can be a mix of types. List values are in square brackets and are mutable.
• Dictionaries: Dictionaries are Python’s most powerful collection. Dictionaries use key value pairs.
• Tuples: Tuples are similar to lists, but use parentheses instead of square brackets, and are not mutable.

Python Reserved Words: Vocabulary and Usage

Reserved words are a key part of the Python vocabulary. These words have specific meanings to Python and cannot be used for other purposes.

• Examples of reserved words include and, or, del, and if.
• When Python sees a reserved word, it knows exactly what it means. It looks at reserved words the same way a dog responds to the word “walk”.
• There are only a few of them. A lot of them, you won’t end up using. They are just these are reserved for Python and part of the Python vocabulary.
• You can’t use them for any other purpose than the purpose that Python wants. It’s sort of part of the contract.

Python Conditional Steps: If, Else, and Try-Except

Here’s what the sources say about conditional steps in Python:

• Conditional steps in Python allow the program to make decisions based on whether a condition is true or false. This is where code starts to get intelligent.
• The keyword that is used is the if statement. The if is like a little fork in the road. You can go one way, or you can go another way, and you’re asking a question.
• The if statement has a question as part of it. The question resolves to a true or false.
• The syntax is the reserved word if, a question, and a colon. An indented block of code begins after the colon. If the question is true, the indented block of code is run. If the question is false, the indented block of code is skipped.
• When finished with an if statement, you deindent back.
• Comparison operators are used to ask true-false questions. These include <, <=, ==, >=, >, and !=.
• If there is only one line in the indented block, it can be pulled up to the same line after the equals.
• The indented block can include more than one line. As long as the code stays indented, it is part of the if block. If the question is false, all of the lines are skipped.
• An else statement can be added, with a colon, followed by a reindented block. The else is part of the block. The first indented block is what runs if the condition is true, and the second indented block, after the else, is what runs if the condition is false. With an if then else, one of the two branches is going to run.
• A multi-way branch can be implemented to pick one of many options using the reserved word elif. The questions are checked in order. If the first one is true, it runs and is done, and the other questions are not checked. Only one of the options is going to run. It is possible to have no else. With no else, it is not guaranteed that one of the blocks will run. There can also be many elif statements. The order in which the questions are asked matters.
• The try and except structure is used to handle code that might cause a traceback. Code that might blow up is put in a try block. If it fails, the code in the except block is run. The except is ignored if the code in the try block works.

Python Data Structures: Lists, Dictionaries, and More

Here’s what the sources say about data structures in Python:

• Algorithms involve using a programming language to express the steps to solve a problem, while data structures involve clever ways to lay out data to achieve a desired result.
• Lists are the first real data structure that is covered in the sources.
• When you put more than one thing in a data structure, you need to get them out.

Key characteristics and concepts related to data structures:

• Variables A variable is a piece of memory with a label on it, capable of holding a single value at a time.
• Collections Collections are like suitcases that can hold multiple items. Lists, dictionaries, and tuples are different ways to organize collections.
• Lists Lists are a simple data structure that can hold a variety of data types. Every time square bracket syntax is used, it’s working with lists. Lists maintain order, and the first thing in the list is the sub-zero position.
• Lists can contain strings, integers, and floating point numbers.
• Lists can contain other lists.
• Lists can be empty.
• The append method can be used to add items to a list.
• The sort method sorts the list in place.
• Strings Strings are like data structures.
• Dictionaries Dictionaries do not have a sense of order.
• Everything in a dictionary has a key.
• Dictionaries are like a purse or a bag where things are labeled, thrown in, and can be retrieved by shouting out the label.
• Dictionaries are referred to as associative arrays, property maps, or hash maps.
• Keys can be strings.
• Tuples Will be covered in more detail.
• Relationship between strings and lists The split function is used to split a string into a list of words.

By Amjad Izhar
Contact: amjad.izhar@gmail.com
https://amjadizhar.blog

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