Introduction

Data visualization plays an important role in presenting information in a clear and meaningful way.
Pie charts are commonly used to display data as percentages of a whole, making it easier to understand
how different categories compare. In Python, the Matplotlib library enables us to quickly create
visually appealing pie charts with various customization options. In this beginner-friendly guide,
you will learn how to create and customize pie charts step-by-step.

What You Will Learn

• How to install Matplotlib
• How to prepare data for pie charts
• How to create and customize pie charts
• How to add labels, percentages, and legends

Prerequisites

• Basic understanding of Python
• Python 3 installed on your machine
• Matplotlib library installed

Step 1 — Create a Project Folder

First, create a folder where your code will be stored:

mkdir pie-chart
cd pie-chart

Step 2 — Install Matplotlib

Run the following command in your terminal to install Matplotlib:

pip install matplotlib

Step 3 — Write the Code

Create a file named pie_chart.py and add the following code:

import matplotlib.pyplot as plt

# Data to be plotted
languages = ['Python', 'JavaScript', 'Java', 'C++']
popularity = [40, 25, 20, 15]

# Plotting pie chart
plt.pie(popularity, labels=languages, autopct='%1.1f%%', startangle=90, shadow=True)

# Adding title
plt.title('Programming Language Popularity')

# Display the chart
plt.show()

Step-by-Step Code Explanation

1. Import Matplotlib: We import Matplotlib’s pyplot module to create charts.
2. Define data: We create two lists — one for languages and one for their popularity.
3. plt.pie(): This function draws the pie chart.
4. autopct: Displays percentage values on each slice.
5. startangle: Rotates the chart for better orientation.
6. shadow: Adds a subtle 3D effect.
7. plt.title: Adds a title above the chart.
8. plt.show: Displays the chart window.

Step 4 — Run the Script

Execute the script using the following command:

python pie_chart.py

A new window will open, displaying your pie chart.

Customizing Your Pie Chart

Matplotlib allows extensive customization. For example:

• Custom colors to match your theme
• Explode to highlight a particular slice
• Legend to add additional context

colors = ['#ff9999','#66b3ff','#99ff99','#ffcc99']
explode = (0.1, 0, 0, 0)

plt.pie(popularity, labels=languages, colors=colors, explode=explode, autopct='%1.1f%%')
plt.legend()
plt.show()

Real-World Use Cases

Pie charts are useful in various scenarios, such as:

• Market share analysis
• Customer segmentation
• Survey result visualization
• Budget allocation
• Election result distribution

Common Errors & Fixes

• ModuleNotFoundError: Ensure Matplotlib is installed correctly.
• Empty chart: Make sure your data lists contain values.
• Wrong pip version: On Linux/Mac, try pip3 install matplotlib.

Conclusion

Pie charts are a simple yet effective way to visualize category-based data. With Matplotlib,
creating and customizing them becomes easy even for beginners. You can now use these skills
to present survey insights, business reports, analytics, and more in a visually appealing manner.