Pie charts are perfect for showing proportions and percentage distribution of data in a simple and visually appealing way.

In this guide, you’ll learn how to create and customize pie charts using Matplotlib.

🔹 What is a Pie Chart?

A pie chart is a circular graph divided into slices, where each slice represents a proportion of the whole.

👉 It answers:

  • What percentage does each category contribute?
  • How is data distributed in parts?

🔹 When to Use Pie Chart?

Use a pie chart when:

✔ You want to show percentage distribution
✔ You have limited categories (ideally < 5)
✔ You want a simple visual representation

🔹 Basic Example

import matplotlib.pyplot as pltlabels = ['Python', 'Java', 'C++']
sizes = [45, 30, 25]plt.pie(sizes, labels=labels)
plt.title("Pie Chart Example")plt.show()

🔹 Output Explanation

  • labels → Categories
  • sizes → Values (proportions)
  • plt.pie() → Creates the pie chart

🔹 Real-Life Use Cases

📊 Market share analysis
💻 Programming language usage
💰 Budget distribution
📦 Product category contribution

🔹 Adding Percentages

plt.pie(sizes, labels=labels, autopct='%1.1f%%')
plt.title("Pie Chart with Percentages")plt.show()

👉 Displays percentage values on each slice.

🔹 Customizing Pie Chart

colors = ['gold', 'lightblue', 'lightgreen']plt.pie(sizes, labels=labels, colors=colors, autopct='%1.1f%%')
plt.title("Customized Pie Chart")plt.show()

🔹 Customization Options

FeatureExampleDescription
Colorscolors=['red','blue']Set slice colors
autopct'%1.1f%%'Show percentages
startanglestartangle=90Rotate chart
explode[0.1, 0, 0]Highlight a slice

🔹 Exploding a Slice

explode = [0.1, 0, 0]plt.pie(sizes, labels=labels, explode=explode, autopct='%1.1f%%')
plt.title("Exploded Pie Chart")plt.show()

👉 Highlights important category.

🔹 Donut Chart (Advanced)

plt.pie(sizes, labels=labels, autopct='%1.1f%%')
centre_circle = plt.Circle((0,0), 0.70, fc='white')
fig = plt.gcf()
fig.gca().add_artist(centre_circle)plt.title("Donut Chart")plt.show()

🔹 Saving the Chart

plt.savefig("pie_chart.png")

🔹 Best Practices

✔ Use only a few categories
✔ Ensure total = 100%
✔ Avoid too many colors
✔ Use labels clearly
✔ Prefer bar chart if data is complex

🔗 Useful Resources

🔚 Conclusion

Pie charts are simple yet powerful for showing proportions. When used correctly, they make your data easy to understand at a glance.

However, use them wisely—too many slices can make them hard to read.

🔖 Hashtags

#Matplotlib #Python #DataVisualization #PieChart #DataScience #MachineLearning #Coding #Analytics #Programming #AI #BigData

Learn Python