Lesson Tutorial: Learn Pandas Basics for Tabular Data Manipulation

Introduction to Pandas and DataFrames

Pandas is a powerful Python library for data manipulation and analysis, built on top of NumPy. The key data structure in Pandas is the DataFrame, which allows you to work with tabular data (rows and columns).

Creating a Pandas DataFrame

1. Creating a DataFrame from a Dictionary

2. Setting a Custom Index

3. Creating a DataFrame from a CSV File

Indexing and Selecting Data in DataFrames

1. Selecting Columns

2. Selecting Rows

3. Using loc and iloc

• loc: Label-based indexing.
• iloc: Integer-based indexing.

Assignment

Use the following dataset to complete the exercises:

Questions

1. Display the DataFrame df.
2. Select and print only the “capital” column.
3. Select and print both “country” and “population” columns.
4. Print the first three rows of the DataFrame.
5. Use loc to print the data for “UK”.
6. Use iloc to print the last two rows of the DataFrame.

Answer Key

1. Display the DataFrame

2. Select and Print the “capital” Column

3. Select and Print “country” and “population” Columns

4. Print the First Three Rows

5. Use loc to Print Data for “UK”

6. Use iloc to Print the Last Two Rows

Learning Objectives Recap

By the end of this tutorial, you should:

• Understand what a Pandas DataFrame is and how to create one.
• Be able to index and select data using square brackets, loc, and iloc.
• Understand how to load and manipulate tabular data from CSV files.