How to manipulate dataframes in Python?

Table of Contents

• Introduction
• Creating a DataFrame
• Indexing and Selecting Data
  • Accessing Rows and Columns
    • Selecting Columns
    • Selecting Rows
• Filtering Data
  • Example of Filtering
• Adding and Modifying Columns
  • Adding a New Column
  • Modifying an Existing Column
• Grouping and Aggregating Data
  • Example of Grouping
• Practical Examples
  • Example 1: Calculating the Average Age
  • Example 2: Finding Unique Values
• Conclusion

Introduction

DataFrames are a fundamental data structure in Python's Pandas library, allowing for efficient storage and manipulation of structured data. They are similar to SQL tables or Excel spreadsheets and are widely used for data analysis tasks. This guide covers various methods for manipulating DataFrames, including indexing, filtering, grouping, and aggregating data.

Creating a DataFrame

Before manipulating data, you first need to create a DataFrame. Here’s an example:

Sample Output:

Indexing and Selecting Data

Accessing Rows and Columns

You can select specific rows and columns using various methods.

Selecting Columns

Selecting Rows

Filtering Data

You can filter rows based on specific conditions.

Example of Filtering

Sample Output:

Adding and Modifying Columns

Adding a New Column

You can add new columns to your DataFrame easily.

Modifying an Existing Column

Grouping and Aggregating Data

You can group data and perform aggregate functions to summarize it.

Example of Grouping

Sample Output:

Practical Examples

Example 1: Calculating the Average Age

You can calculate the average age of people in your DataFrame.

Example 2: Finding Unique Values

To find unique values in a column:

Conclusion

Manipulating DataFrames in Python using Pandas is a powerful way to handle and analyze structured data efficiently. By understanding how to create, index, filter, group, and aggregate data within DataFrames, you can perform complex data analysis tasks with ease. The Pandas library provides a comprehensive set of tools that make data manipulation straightforward and effective, enhancing your data analysis capabilities.