Graphs Cookbook

Drawing a bar chart Drawing a box plot Drawing a function Drawing a histogram Drawing a horizontal line Drawing a line plot Drawing a normal curve Drawing a scatterplot Drawing a single point Drawing a stacked bar chart Drawing a vertical line Drawing arrows Drawing circles Drawing empty circles Drawing error bars Drawing horizontal bar plots Drawing multiple histograms in one plot Normalizing a histogram Plotting scatter plot with category

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Plotting scatter plot with category in Matplotlib

Programming

Python

Matplotlib

Cookbooks

Graphs Cookbook

Jul 1, 2022

Last updated

local_offer Python●Matplotlib

Basic example of plotting scatter plot with categories

To plot a scatter plot with categories or classes in Matplotlib, use the following code:


        
        
            
                
                
                    import matplotlib.pyplot as plt
import pandas as pd

labels = ['A','B','A','C']
arr_int_classes = pd.Categorical(labels).codes
scatter = plt.scatter([5,2,3,3], [1,2,4,1], c=arr_int_classes)
plt.legend(handles=scatter.legend_elements()[0], labels=arr_str_labels)
plt.show()

Here, we are first converting our string labels into numerical values using Pandas' Categorical(~) function:


        
        
            
                
                
                    arr_int_classes = pd.Categorical(labels).codes
arr_int_classes
                
            
            array([0, 1, 0, 2], dtype=int8)

This results in the following plot:

Plotting scatter plot with categories using custom colors

To plot a scatter plot with categories, use ListedColormap:


        
        
            
                
                
                    import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import pandas as pd

labels = ['A','B','A','C']
arr_int_classes = pd.Categorical(labels).codes
colours = ListedColormap(['g','blue','#EA131B'])
scatter = plt.scatter([5,2,3,3], [1,2,4,1], c=arr_int_classes, cmap=colours)
plt.legend(handles=scatter.legend_elements()[0], labels=arr_str_labels)
plt.show()