How to make a nested pie chart in Python
A nested pie chart, also known as nested donut chart, displays the given data in multiple levels. Here, we’re going to understand how to implement a nested pie chart using matplotlib.
What is Matplotlib?
Matplotlib is a plotting library in Python, and its numerical mathematics extension NumPy, that allows users to create static, animated, and interactive visuals.
Implementing nested pie chart
First, we’re going to import the required libraries using the import function:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Next, we’ll assign values to the wedges of the pie chart. Here, the nested pie takes values in three different categories. We’re going to assign data corresponding to three classes.
In the inner circle, we will represent value as a member of its own group in the form of percentages. In the outer circle, we’ll represent their original categories along with the percentages.
After plotting the Pie, the donut shape should look like:
Code
Here, we take scores of three students and plot a nested pie chart using the percentage of these scores.
To achieve the concentric shape, we set the width of pie with the wedgeprops function.
To use data specific columns from the given data, we use df.iloc[] – this allows us to take certain values from the list.
# Importing required librariesimport numpy as npimport pandas as pdimport matplotlib.pyplot as plt# Taking raw data of three studentssource_data={'students':['Jake','Amy','Boyle'],'math_score':[68,82,97],'english_score':[70,93,99],'physics_score':[73,85,95]}# Segregating the raw data into usuable formdf=pd.DataFrame(source_data,columns=['students','math_score','english_score','physics_score'])df['cumulative_score']=df['math_score']+df['english_score']+df['physics_score']# Seperating the sub-parts of the given datax1= df.iloc[0:3,1]x2= df.iloc[0:3,2]# Setting figure colorscmap = plt.get_cmap("tab20c")outer_colors = cmap(np.arange(3)*4)inner_colors = cmap(np.array([1,5,9]))# Setting the size of the figureplt.figure(figsize=(8,6))# Plotting the outer pieplt.pie(x1, labels = df.iloc[0:3, 0],startangle=90, pctdistance =0.88 ,colors=outer_colors,autopct = '%1.1f%%', radius= 1.0, labeldistance=1.05,textprops ={ 'fontweight': 'bold','fontsize':13},wedgeprops = {'linewidth' : 3, 'edgecolor' : "w" } )# PLotting the inner pieplt.pie(x2,startangle=90, pctdistance =0.85,colors=inner_colors,autopct = '%1.1f%%',radius= 0.60,textprops ={'fontweight': 'bold' ,'fontsize':13},wedgeprops = {'linewidth' : 3, 'edgecolor' : "w" } )# Creating the donut shape for the piecentre_circle = plt.Circle((0,0), 0.25, fc='white')fig= plt.gcf()fig.gca().add_artist(centre_circle) # adding the centre circle# Plotting the pieplt.axis('equal') # equal aspect ratioplt.legend( loc=3, fontsize =15)plt.tight_layout()plt.show()
The above code plots a nested pie chart, which gives us the percentages or marks scored by different students. You can add more layers to the pie by adding more data columns.
