Histograms

Matplotlib Basics

1 min read

Published Oct 5 2025

ChartsGraphsMatplotlibNumPyPandasPythonVisualisation

A histogram visualises the distribution of numerical data — it shows how many data points fall into a range of values (called bins).

Instead of plotting individual points, it groups values and displays the frequency in vertical bars.

Syntax:

plt.hist(x, bins=None, range=None, density=False, color=None, edgecolor=None, alpha=None, histtype='bar')

Parameters:

x = Data to plot
bins = Number of bins (int) or explicit bin edges
range = Lower and upper range of bins
density = Normalise histogram (area = 1)
color = Fill colour
edgecolor = Outline color
alpha = Transparency
histtype = Type of histogram: 'bar', 'step', 'stepfilled'
label = Legend label

Basic histogram example

import matplotlib.pyplot as plt

import numpy as np

data = np.random.randn(1000)

plt.hist(data)

plt.title("Basic Histogram")

plt.xlabel("Value")

plt.ylabel("Frequency")

plt.show()

This automatically chooses 10 bins by default.

matplotlib histogram chart basic example

Custom number of bins

import matplotlib.pyplot as plt

import numpy as np

data = np.random.randn(1000)

plt.hist(data, bins=20, color='skyblue', edgecolor='black')

plt.title("Histogram with 20 Bins")

plt.show()

matplotlib histogram chart custom bins example

Define custom bin edges

You can define the exact cut points:

import matplotlib.pyplot as plt

import numpy as np

data = np.random.randn(1000)

bins = [-3, -2, -1, 0, 1, 2, 3]

plt.hist(data, bins=bins, color='salmon', edgecolor='black')

plt.title("Custom Bin Edges")

plt.show()

matplotlib histogram chart custom bin edges example

Change Colour and Edge

import matplotlib.pyplot as plt

import numpy as np

data = np.random.randn(1000)

plt.hist(data, bins=15, color='orange', edgecolor='blue')

plt.title("Styled Histogram")

plt.show()

matplotlib histogram chart styled example

Multiple histograms on the same plot

You can overlay histograms to compare distributions:

import matplotlib.pyplot as plt

import numpy as np

data1 = np.random.normal(0, 1, 1000)

data2 = np.random.normal(2, 1, 1000)

plt.hist(data1, bins=20, alpha=0.5, label='Group A')

plt.hist(data2, bins=20, alpha=0.5, label='Group B')

plt.legend()

plt.title("Multiple Histograms (Overlayed)")

plt.show()

Use alpha for transparency so both remain visible.

matplotlib histogram chart multiple example

Stacked Histograms

Stack multiple datasets to see combined distribution:

import matplotlib.pyplot as plt

import numpy as np

data1 = np.random.normal(0, 1, 1000)

data2 = np.random.normal(2, 1, 1000)

plt.hist([data1, data2], bins=20, stacked=True, color=['skyblue', 'lightcoral'], label=['Group A', 'Group B'])

plt.legend()

plt.title("Stacked Histogram")

plt.show()

matplotlib histogram chart stacked example

Step and step-filled styles

Step:

import matplotlib.pyplot as plt

import numpy as np

data = np.random.randn(1000)

plt.hist(data, bins=30, histtype='step', color='navy', linewidth=2)

plt.title("Step Histogram")

plt.show()

Step Filled:

import matplotlib.pyplot as plt

import numpy as np

data = np.random.randn(1000)

plt.hist(data, bins=30, histtype='stepfilled', color='lightgreen', alpha=0.7)

plt.title("Step-Filled Histogram")

plt.show()

matplotlib histogram chart step filled example

Normalised histogram (density plot)

If you want the area under the curve = 1, use density=True. This is common for probability distributions.

import matplotlib.pyplot as plt

import numpy as np

data = np.random.randn(1000)

plt.hist(data, bins=30, density=True, color='plum', edgecolor='black')

plt.title("Normalised Histogram (Density=True)")

plt.ylabel("Probability Density")

plt.show()

matplotlib histogram chart density example

Cumulative Histogram

To show cumulative frequencies.

import matplotlib.pyplot as plt

import numpy as np

data = np.random.randn(1000)

plt.hist(data, bins=30, cumulative=True, color='lightblue', edgecolor='black')

plt.title("Cumulative Histogram")

plt.show()

matplotlib histogram chart cumulative example

Horizontal histogram

import matplotlib.pyplot as plt

import numpy as np

data = np.random.randn(1000)

plt.hist(data, bins=20, orientation='horizontal', color='lime', edgecolor='black')

plt.title("Horizontal Histogram")

plt.show()

matplotlib histogram chart horizontal example

Histograms

Matplotlib Basics

1 min read

Published Oct 5 2025

Guide Sections

Guide Comments

Basic histogram example

Custom number of bins

Define custom bin edges

Change Colour and Edge

Multiple histograms on the same plot

Stacked Histograms

Normalised histogram (density plot)

Cumulative Histogram

Horizontal histogram

Products from our shop

Docker Cheat Sheet - Print at Home Designs

Docker Cheat Sheet Mouse Mat

Docker Cheat Sheet Travel Mug

Docker Cheat Sheet Mug

Vim Cheat Sheet - Print at Home Designs

Vim Cheat Sheet Mouse Mat

Vim Cheat Sheet Travel Mug

Vim Cheat Sheet Mug

SimpleSteps.guide branded Travel Mug

Developer Excuse Javascript - Travel Mug

Developer Excuse Javascript Embroidered T-Shirt - Dark

Developer Excuse Javascript Embroidered T-Shirt - Light

Developer Excuse Javascript Mug - White

Developer Excuse Javascript Mug - Black

SimpleSteps.guide branded stainless steel water bottle

Developer Excuse Javascript Hoodie - Light

Developer Excuse Javascript Hoodie - Dark