EX Exercises

Introduction

This unit covers Python’s data structures, including lists and data frames (using pandas). You will work through various tasks to build familiarity with these concepts.

🧪 Task 1: Working with Lists

📋 Description:

In this task, you will practice using Python lists. You’ll define lists, access elements, and apply key list methods such as append(), remove(), and extend().

️ Instructions:

  1. Define two lists:
list1 = [19, 20, 3]
list2 = [48, 5, 6]
  1. Perform the following operations:
    • Concatenate list1 and list2 to create a new list called my_list.
    • Calculate the sum of list1 (use Accessing elements by index, no loops).
    • Find the length of list1 using the len() function.
    • Print the second element of list2.
  2. Modify my_list:
    • Append a new element 'apple' using append().
    • Remove the value 19 from the list using remove().
    • Extend the list with another list ['tree', 'leave', 'root'] using extend().
    • Finally, print the updated length of my_list.

💡 Reminder:

  • append() adds a single item.
  • extend() adds each element from another iterable.
  • Lists are mutable, so you can modify them in place.

🧪 Task 2: Compare Array Elements

📋 Description:

You will create a NumPy array and use an if-else statement to compare specific elements. No loops are required.

️ Instructions:

  1. Import the NumPy library.
  2. Create an array called scores with the values [88, 92, 75, 91].
  3. Compare the first and last elements of the array using an if-else statement:
    • If the first element is greater than the last, print: "First score is higher."
    • Otherwise, print: "Last score is higher or equal."

Task 3: Data Frames

Description:

Learn how to create and manipulate data frames using pandas.

Instructions:

  1. Create a data frame using pandas with the following data:
    • Name = ['Alice', 'Bob', 'Charlie']
    • Age = [25, 30, 35]
    • Salary = [50000, 60000, 70000]
  2. Perform the following operations:
    • Display the first two rows of the data frame.
    • Add a new column called Department with values ['Human Resources', 'Engineering', 'Marketing'].
    • Select the Name and Salary columns.
    • Filter the data frame to only show rows where Age > 28.

Task 3: Matrices

Description:

Learn how to create and manipulate matrices using numpy.

Instructions:

  1. Create a 2x3 matrix with the following values: 
     [[1, 2, 3],
  [4, 5, 6]]
  2. Perform the following operations:
    • Transpose the matrix.
    • Calculate the sum of all elements.
    • Multiply each element of the matrix by 2.
    • Access the element at row 1, column 2.

Happy coding!

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