A simple donut chart is nothing but a simple form. It is a pie chart with its center cut out, which looks like a donut shape. It helps us ensure the area parameter that trips users up in a pie chart is clear.

The main difference between a simple donut chart and a pie chart is that a pie chart. It consists of a circle divided into segments that represent the parts of the whole. The donut chart follows the circumference of the circle shape. In contrast, donut charts also look like pie charts in Python, but with a hole in the middle and an axis for a pie chart. To show many series, we use one graphical visualization nested donut chart. Usually, we will find the series related. We represent it as categorical data or pie slices. It will be like the distribution of some category values. We can use the donut chart to divide a certain field by percentage coverage. We can use the donut chart for numbers instead of percentages. It will help represent the specific categorical data that compose the whole. To create a donut chart, we must install two important libraries, Matplotlib and NumPy.

Then, you can import them as import matplotlib and numpy. We can use Matplotlib for plotting and its numerical mathematics extension. It allows us to create static, animated, and interactive visuals. The pie radius allows us to add space for the pie radius around slices. For example, consider another situation where we must prepare a mark report of students in a test. You can then visualize their performance using a donut chart. We can get the result by running the above code snippet.

### Advantages:

- Donut charts can be customizable.
- It is easy to understand.
- Donut charts are user-friendly.

### Disadvantages:

- Donut charts have fewer categories.
- It has vague values, making it difficult to determine the exact values.
- Donut charts are not suitable for changing data.

Here is an example of creating a donut chart using matplotlib in Python:

Fig: Preview of the output that you will get on running this code from your IDE.

### Code

In this solution we're using Matplotlib and NumPy libraries.

### Instructions

__Follow the steps carefully to get the output easily.__

- Install PyCharm Community Edition on your computer.
- Open terminal and install the required libraries with following commands.
- Install Matplotlib - pip install matplotlib.
- Install NumPy - pip install numpy.
- Create a new Python file(eg: test.py).
- Copy the snippet using the 'copy' button and paste it into that file.
- Run the file using run button.

I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.

*I found this code snippet by searching for **'donut chart using matplotlib'** in kandi. You can try any such use case!*

### Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

- The solution is created in PyCharm 2022.3.3.
- The solution is tested on Python 3.9.7.
- Matplotlib version 3.7.1.
- NumPy version v1.24.2.

Using this solution, we are able to create donut chart using Matplotlib in Python with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to create donut chart using Matplotlib in Python.

### Dependent Libraries

matplotlibby matplotlib

matplotlib: plotting with Python

matplotlibby matplotlib

Python 17559 Version:v3.7.1 License: No License

numpyby numpy

The fundamental package for scientific computing with Python.

numpyby numpy

Python 23755 Version:v1.25.0rc1 License: Permissive (BSD-3-Clause)

*You can also search for any dependent libraries on kandi like **'Matplotlib'** and **'NumPy'.*

**FAQ: **

**1. How do you build a Pie Chart in Python? **

First of all, import libraries. import matplotlib.pyplot as plt and import numpy as np. Then create a dataframe and draw standard and nested donut charts.

**2. What is the difference between a donut chart and a nested donut chart? **

It is a pie chart with its center cut out, which looks like a donut shape. Also, it helps us to clarify the area parameter that trips users up in a pie chart.

**3. Are there any differences in how we can create a Donut Chart using the plotting library? **

For example, consider another situation where we must prepare a mark report of students in a test. You can visualize their performance using a donut chart.

**4. What kinds of categorical data are best represented with donut charts? **

Frequency tables, pie, and bar charts represent the appropriate graphical data.

**5. Could you provide an example code snippet to create a simple donut chart in Python? **

Use the above code snippet as an example to create a simple donut chart.

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