Table of Contents

1. Challenge

   Understanding Python Identifiers, Literals, and Operators

   Jupyter Guide

   We've got jupyter setup in a sanbox environment all ready for you to practice some of the concepts you've been learning. To get started, open the file on the right entitled "Step 1...". You'll complete each task for Step 1 in that Jupyter Notebook file. Remember, you must run the cells (Ctrl/Cmd(⌘) + Enter) for each task before moving onto the next task in the Jupyter Notebook. Continue until you have completed all tasks in this step. Then when you are ready to move onto the next step, you'll come back and click on the file for the next step until you have completed all tasks in all steps of the lab.

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   Understanding Python Identifiers, Literals, and Operators

   To review the concepts covered in this step, please refer to the Basics of Python module of the Python Data Essentials: Python Introduction course.

   Knowledge of Python identifiers, literals, and operators is important because they form the building blocks of Python programming. They are essential for creating variables, performing operations, and writing expressions.

   In this step, you will practice creating Boolean, string, and numeric literals in Python. You will also learn about Python identifiers and how to use them. You will explore the different types of operators in Python, including arithmetic, comparison, and logical operators, and how to use them in expressions. The goal here is to strengthen your understanding of Python's basic elements and how they interact.

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   Task 1.1: Creating Python Identifiers

   Create a Python identifier by assigning the value 5 to a variable. Print the value of the variable.

   🔍 Hint

   Use the assignment operator = to assign a value to a variable. Use the print(variable_here) function to print the value of the variable.

   🔑 Solution

   my_identifier = 5
   print(my_identifier)
   

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   Task 1.2: Creating Boolean Literals

   Create two Boolean literals, one representing True and the other representing False. Print the values of the literals.

   🔍 Hint

   Use the keywords True and False to create Boolean literals. Use the print() function to print the values of the literals.

   🔑 Solution

   my_true_literal = True
   my_false_literal = False
   print(my_true_literal)
   print(my_false_literal)
   

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   Task 1.3: Creating String Literals

   Create a string literal and print its value.

   🔍 Hint

   Use single or double quotes to create a string literal. Use the print() function to print the value of the literal.

   🔑 Solution

   my_string_literal = 'Hello, Python!'
   print(my_string_literal)
   

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   Task 1.4: Creating Numeric Literals

   Create a numeric literal and print its value.

   🔍 Hint

   You can create a numeric literal by simply writing a number. Use the print() function to print the value of the literal.

   🔑 Solution

   my_numeric_literal = 42
   print(my_numeric_literal)
   

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   Task 1.5: Using Arithmetic Operators

   Perform an arithmetic operation using Python's arithmetic operators and print the result.

   🔍 Hint

   You can use operators like +, -, *, /, //, %, and ** to perform arithmetic operations. Use the print() function to print the result.

   🔑 Solution

   result = 10 * 5
   print(result)
   

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   Task 1.6: Using Comparison Operators

   Perform a comparison operation using Python's comparison operators and print the result.

   🔍 Hint

   You can use operators like ==, !=, <, >, <=, and >= to perform comparison operations. Use the print() function to print the result.

   🔑 Solution

   result = 10 > 5
   print(result)
   

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   Task 1.7: Using Logical Operators

   Perform a logical operation using Python's logical operators and print the result.

   🔍 Hint

   You can use operators like and, or, and not to perform logical operations. Use the print() function to print the result.

   🔑 Solution

   result = True and False
   print(result)
   

2. Challenge

   Working with Python Packages and Data Structures

   Working with Python Packages and Data Structures

   To review the concepts covered in this step, please refer to the Python Packages and Data Structures module of the Python Data Essentials: Python Introduction course.

   Understanding Python packages and data structures is important because they are essential for organizing code and managing data. Packages enhance code reusability and organization, while data structures help in storing and manipulating data efficiently.

   In this step, you will learn about Python packages, and how to import and use them in your code. We'll be using the pprint module which has been pre-installed for you. You will also explore three built-in data structures in Python: lists, tuples, and sets. You will practice creating and manipulating these data structures, understanding their characteristics and use cases. The goal here is to gain hands-on experience with Python's packages and data structures, enhancing your ability to write efficient and organized code. (Instruct the user in the descriptions to print thre results)

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   Task 2.1: Importing the pprint module

   Import the pprint module from Python's standard library. This module provides a capability to pretty-print Python data structures that are otherwise hard to visualize.

   🔍 Hint

   Use the import keyword followed by the name of the module, which is pprint in this case.

   🔑 Solution

   import pprint
   

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   Task 2.2: Understanding the usefulness of pprint

   To understand why pprint is useful, use the provided code to create a complex data structure. Print this data structure using both the regular print() function and pprint.pprint(). Compare the outputs to see the difference in readability.

   🔍 Hint

   Use the provided code to make a complex data structure and print it using both print(data) and pprint.pprint(data).

   🔑 Solution

   # Provided code for complex data
   complex_data = [
       {"A", "Set", "Here"},
       ("This", "is", "a", "tuple", "with", 7, "elements"),
       [True, False],
       "A somewhat lengthy string",
       0,
       3.141529,
   ]
   
   # Print complex data normally and with pprint
   print("---Complex Data with Pretty Print---")
   pprint.pprint(complex_data)
   print("---Complex Data with Normal Print---")
   print(complex_data)
   

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   Task 2.3: Creating a list

   Create a list named my_list with the following elements: 1, 2, 3, 4, 5. Then, print the list using the pprint function.

   🔍 Hint

   Use square brackets [] to create a list. To print the list, use pprint.pprint(my_list).

   🔑 Solution

   my_list = [1, 2, 3, 4, 5]
   pprint.pprint(my_list)
   

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   Task 2.4: Creating a tuple

   Create a tuple named my_tuple with the following elements: 'a', 'b', 'c', 'd', 'e'. Then, print the tuple using the pprint function.

   🔍 Hint

   Use parentheses () to create a tuple. To print the tuple, use pprint.pprint(my_tuple).

   🔑 Solution

   my_tuple = ('a', 'b', 'c', 'd', 'e')
   pprint.pprint(my_tuple)
   

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   Task 2.5: Creating a set

   Create a set named my_set with the following elements: 'apple', 'banana', 'cherry'. Then, print the set using the pprint function.

   🔍 Hint

   Use curly braces {} to create a set. To print the set, use pprint.pprint(my_set).

   🔑 Solution

   my_set = {'apple', 'banana', 'cherry'}
   pprint.pprint(my_set)