Multiple histograms overlay in Matplotlib - Step-by-Step Execution

Concept Flow - Multiple histograms overlay

Prepare data sets

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Call plt.hist() for each data set with alpha

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Histograms drawn on same plot

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Add labels, legend, title

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Show combined histogram plot

We prepare multiple data sets, then draw their histograms on the same plot with transparency to see overlaps.

Execution Sample

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

# Two data sets
data1 = np.random.normal(0, 1, 1000)
data2 = np.random.normal(2, 1.5, 1000)

plt.hist(data1, bins=30, alpha=0.5, label='Data 1')
plt.hist(data2, bins=30, alpha=0.5, label='Data 2')
plt.legend()
plt.show()

This code draws two histograms on the same plot with some transparency so we can see where they overlap.

Execution Table

Step	Action	Data Used	Bins	Alpha	Plot State	Output
1	Generate data1	Normal(0,1), 1000 points	-	-	No plot yet	data1 array created
2	Generate data2	Normal(2,1.5), 1000 points	-	-	No plot yet	data2 array created
3	Plot histogram for data1	data1	30	0.5	Plot with data1 histogram	Histogram bars for data1 shown with 50% transparency
4	Plot histogram for data2	data2	30	0.5	Plot with data1 and data2 histograms	Histogram bars for data2 shown overlapping data1 with 50% transparency
5	Add legend	-	-	-	Plot with legend	Legend shows 'Data 1' and 'Data 2' labels
6	Show plot	-	-	-	Plot displayed	Combined histogram plot visible with overlays

💡 All steps complete, plot shown with both histograms overlayed.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	Final
data1	None	Array of 1000 values ~ N(0,1)	Array unchanged	Array unchanged	Array unchanged	Array unchanged
data2	None	None	Array of 1000 values ~ N(2,1.5)	Array unchanged	Array unchanged	Array unchanged
plot_state	Empty	Empty	Empty	Histogram of data1 drawn	Histograms of data1 and data2 drawn	Plot with legend and shown

Key Moments - 3 Insights

Why do we use alpha=0.5 when plotting multiple histograms?

Alpha sets transparency. Using 0.5 lets us see overlapping bars clearly, as shown in execution_table steps 3 and 4.

What happens if we don't call plt.legend() after plotting?

Without plt.legend(), the plot won't show labels for each histogram, making it hard to tell which bars belong to which data set (see step 5).

Why do both histograms use the same number of bins?

Using the same bins (30 here) aligns the bars for easy comparison, as seen in steps 3 and 4.

Visual Quiz - 3 Questions

Look at the execution_table at step 4. What does the plot state show after plotting data2?

A Plot with data1 and data2 histograms overlayed

B Plot with only data2 histogram

C Empty plot with no histograms

D Plot with legend only

💡 Hint

Check the 'Plot State' column at step 4 in execution_table.

At which step is the legend added to the plot?

A Step 3

B Step 5

C Step 4

D Step 6

💡 Hint

Look for the action 'Add legend' in execution_table.

If we remove alpha=0.5 from both plt.hist calls, what will happen to the plot?

A Histograms will be transparent and easy to compare

B Plot will show no histograms

C Histograms will be fully opaque and overlapping bars may hide each other

D Plot will show only one histogram

💡 Hint

Refer to key_moments about the role of alpha transparency.

Concept Snapshot

Multiple histograms overlay:
- Use plt.hist() multiple times on same plot
- Use same bins for alignment
- Use alpha (0-1) for transparency
- Add labels and plt.legend() for clarity
- Call plt.show() to display combined plot

Full Transcript

This visual execution shows how to overlay multiple histograms using matplotlib. First, two data sets are created with different normal distributions. Then, plt.hist() is called twice with the same number of bins and alpha=0.5 for transparency. This allows both histograms to appear on the same plot, showing overlaps clearly. A legend is added to label each histogram. Finally, plt.show() displays the combined plot. Key points include using alpha for transparency and adding a legend for clarity.