Python Tutorials · Python Matplotlib

Matplotlib Histograms

Learn all about Matplotlib Histograms in this comprehensive tutorial.

5 min read intermediate

Matplotlib Bars

Matplotlib Pie Charts

•A histogram is a graph showing frequency distributions.
•In Matplotlib, we use the hist() function to create histograms.

Histogram

A histogram is a graph showing frequency distributions.

It is a graph showing the number of observations within each given interval.

Example: Say you ask for the height of 250 people, you might end up with a histogram like this:

You can read from the histogram that there are approximately:

2 people from 140 to 145cm5 people from 145 to 150cm15 people from 151 to 156cm31 people from 157 to 162cm46 people from 163 to 168cm53 people from 168 to 173cm45 people from 173 to 178cm28 people from 179 to 184cm21 people from 185 to 190cm4 people from 190 to 195cm

Create Histogram

In Matplotlib, we use the hist() function to create histograms.

The hist() function will use an array of numbers to create a histogram, the array is sent into the function as an argument.

For simplicity we use NumPy to randomly generate an array with 250 values, where the values will concentrate around 170, and the standard deviation is 10. Learn more about Normal Data Distribution in our Machine Learning Tutorial.

python

import numpy as npx = 
  np.random.normal(170, 10, 250)print(val_1)

The hist() function will read the array and produce a histogram:

python

import matplotlib.pyplot as pltimport numpy as npx = 
  np.random.normal(170, 10, 250)plt.hist(val_1)plt.show()

Module quiz

2 questions

Which of the following is true about Matplotlib Histograms?

It is strictly typedIt is evaluated at runtimeIt requires explicit memory managementIt is deprecated

What is the most common pitfall when working with Matplotlib Histograms?

SyntaxErrorIndentationErrorNameErrorTypeError

Answer all questions to submit.