Python – Mosaic Plot

A mosaic plot is a graphical representation of the interaction between two categorical variables. It is particularly useful for visualizing the relationship between these variables and how they are distributed within each category.

In Python, you can create a mosaic plot using the ‘mosaic’ function from the ‘statsmodels.graphics.mosaicplot’ module. This function allows you to specify the two categorical variables to be compared, as well as any additional parameters such as colors or labels.

Here is an example of how to create a mosaic plot in Python:

import numpy as np
import pandas as pd
import statsmodels.api as sm
import statsmodels.graphics.mosaicplot as sg

# Create a sample dataset
data = {'Gender': ['Male', 'Female', 'Male', 'Female', 'Male', 'Female'],
        'Education': ['High School', 'High School', 'College', 'College', 'Graduate', 'Graduate']}
df = pd.DataFrame(data)

# Create the mosaic plot
mosaic = sg.mosaic(df, ['Gender', 'Education'])

# Display the plot
plt.show()

In this example, we have created a sample dataset with two categorical variables – ‘Gender’ and ‘Education’. We then use the ‘mosaic’ function to create a mosaic plot comparing these two variables. The resulting plot visually represents the distribution of education levels within each gender category.

Mosaic plots are a great way to explore the relationships between categorical variables in your data and can provide valuable insights into how these variables interact.