Multiple histograms overlay in Matplotlib

Introduction

Overlaying multiple histograms helps compare different data groups visually in one chart.

Comparing test scores of two classes in one graph.

Showing sales distribution for different months together.

Visualizing heights of men and women in the same plot.

Comparing customer ages from two regions side by side.

Syntax

Matplotlib

import matplotlib.pyplot as plt

plt.hist(data1, bins=number, alpha=transparency, label='label1')
plt.hist(data2, bins=number, alpha=transparency, label='label2')
plt.legend()
plt.show()

alpha controls transparency so histograms can be seen overlapping.

Use label and plt.legend() to add a legend for clarity.

Examples

Plot two histograms together using a list of datasets.

Matplotlib

plt.hist([data1, data2], bins=10, alpha=0.5, label=['Group 1', 'Group 2'])
plt.legend()
plt.show()

Plot two histograms separately with same bins and transparency.

Matplotlib

plt.hist(data1, bins=15, alpha=0.7, label='Set A')
plt.hist(data2, bins=15, alpha=0.7, label='Set B')
plt.legend()
plt.show()

Sample Program

This code creates two groups of random numbers with different averages and spreads. It then plots their histograms on the same chart with some transparency so you can see where they overlap.

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

# Create two sets of random data
np.random.seed(0)
data1 = np.random.normal(50, 10, 1000)  # Group 1
np.random.seed(1)
data2 = np.random.normal(60, 15, 1000)  # Group 2

# Plot histograms overlay
plt.hist(data1, bins=30, alpha=0.5, label='Group 1')
plt.hist(data2, bins=30, alpha=0.5, label='Group 2')
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.title('Overlay of Two Histograms')
plt.legend()
plt.show()

Important Notes

Make sure bins are the same for all histograms to compare properly.

Adjust alpha to see overlapping areas clearly.

Use plt.legend() to identify each histogram easily.

Summary

Overlaying histograms helps compare multiple data groups visually.

Use alpha for transparency and label with legend for clarity.

Keep bins consistent for meaningful comparison.