Python Program For Pie Chart (With Output & Complete Code)

In this tutorial, you will learn about the python program for pie chart.

In this article, we will walk you through a step-by-step guide on how to write a Python program for creating a pie chart.

Let’s dive in and explore the exciting world of data visualization!

Data visualization plays a crucial role in understanding complex datasets and conveying information effectively.

Pie charts are an excellent way to represent data in a circular format, showcasing the proportionate values of different categories.

With Python’s extensive libraries, such as Matplotlib and Seaborn, creating pie charts has become easier than ever.

So, let’s get started and learn how to write a Python program for a pie chart.

Before we begin, make sure you have Python installed on your system.

Additionally, we will be using the Matplotlib library, so ensure it is installed as well.

You can install Matplotlib by running the following command.

pip install matplotlib

To start our Python program, we need to import the necessary libraries.

In this case, we will import Matplotlib’s pyplot module and NumPy for generating sample data.

Add the following lines of code at the beginning of your program.

import matplotlib.pyplot as plt
import numpy as np

Next, let’s create some sample data for our pie chart.

For demonstration purposes, we will consider a dataset showing the market share of different operating systems.

In this case, we will assume we have the following data.

Operating System	Market Share
Windows	45
macOS	30
Linux	15
Others	10

To create this dataset in Python, we can use NumPy’s np.array() function.

Here’s how you can define the data:

os_labels = ['Windows', 'macOS', 'Linux', 'Others']
market_share = np.array([45, 30, 15, 10])

Now comes the exciting part – creating the pie chart!

We will utilize Matplotlib’s pie() function to generate the chart.

Here’s the code snippet for creating the pie chart.

Python Program For Pie Chart

plt.pie(market_share, labels=os_labels, autopct='%1.1f%%')
plt.title('Operating System Market Share')
plt.axis('equal')
plt.show()

Let’s break down the code:

• plt.pie(market_share, labels=os_labels, autopct=’%1.1f%%’) creates the pie chart using the provided data. The autopct argument specifies the format of the percentage values displayed on the chart.
• plt.title(‘Operating System Market Share’) sets the title for the chart.
• plt.axis('equal') ensures that the pie chart appears as a perfect circle.
• plt.show() displays the chart on the screen.

Here is the output of the program.

How do you code a pie chart in Python?

To code a pie chart in Python, you can use libraries like Matplotlib or Seaborn.

First, import the necessary libraries, then define your data for the pie chart.

Use the plt.pie() function to create the chart, providing the data and labels.

Customize the chart as desired by adding a title, legend, or exploding slices.

Finally, use plt.show() to display the chart.

Refer to the previous sections of this article for a detailed step-by-step guide.

What is pie chart plot in Python?

In Python, a pie chart plot is a graphical representation that displays the proportionate values of different categories as slices of a circular pie.

The size of each slice represents the relative magnitude of the corresponding category’s value in the dataset.

Pie chart plots are commonly used to visualize categorical data and are effective for understanding the distribution or composition of the dataset at a glance.

How do you make a pie chart dataset in Python?

To make a pie chart dataset in Python, you need to define the values and labels for each category.

You can store the category labels in a list and the corresponding values in another list or NumPy array.

Ensure that the values are numerical and represent the proportions or magnitudes of each category.

With the dataset ready, you can pass it to the plt.pie() function in Matplotlib, along with other optional parameters, to create the pie chart.

How do you make a pie chart with percentages in Python?

Making a pie chart with percentages in Python is straightforward.

When creating the pie chart using the plt.pie() function, you can use the autopct parameter to specify the format of the percentage values displayed on the chart. Set it to '%1.1f%%' to display the percentages with one decimal place.

The percentages will automatically be calculated based on the values in the dataset and shown on each slice of the pie chart.

How can I save the pie chart as an image file?

Saving the pie chart as an image file is straightforward.

After creating the chart using plt.show(), you can use the savefig() function to save it in various formats, such as PNG, JPEG, or SVG.

Here’s an example:

plt.savefig('pie_chart.png', dpi=300, bbox_inches='tight')

Is it possible to explode a specific slice of the pie chart?

Absolutely! Exploding a slice means pulling it out from the center to highlight it.

You can achieve this by specifying the explode parameter in the pie() function.

The explode argument takes a list of values, where each value represents the extent of the slice’s displacement.

For example:

explode = [0, 0.1, 0, 0] # Explode the second slice (macOS) 
plt.pie(market_share, labels=os_labels, autopct='%1.1f%%', explode=explode)

Can I add a legend to the pie chart?

Yes, you can add a legend to the pie chart using the legend() function from Matplotlib.

By default, the legend displays the labels passed to the pie() function.

Here’s an example of adding a legend to our pie chart:

plt.pie(market_share, labels=os_labels, autopct='%1.1f%%') 
plt.title('Operating System Market Share') plt.axis('equal') 
plt.legend(title='Operating Systems', loc='best') 
plt.show()

Are there any alternatives to Matplotlib for creating pie charts?

Yes, besides Matplotlib, you can also use other Python libraries like Plotly, Seaborn, and Bokeh to create pie charts.

Each library has its own set of features and advantages.

Feel free to explore them and choose the one that best suits your requirements.

In this article, we learned how to write a Python program for creating a pie chart.

We explored the necessary steps, from importing libraries to generating sample data and visualizing it using Matplotlib.

By following this guide, you can create customized pie charts to represent various datasets.

So, go ahead, unleash your creativity, and bring your data to life with captivating pie charts!

Happy Coding!

Learn more about other python libraries and modules.