Book Image

matplotlib Plotting Cookbook

By : Alexandre Devert
Book Image

matplotlib Plotting Cookbook

By: Alexandre Devert

Overview of this book

Table of Contents (15 chapters)
matplotlib Plotting Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Plotting boxplots


Boxplot allows you to compare distributions of values by conveniently showing the median, quartiles, maximum, and minimum of a set of values.

How to do it...

The following script shows a boxplot for 100 random values drawn from a normal distribution:

import numpy as np
import matplotlib.pyplot as plt

data = np.random.randn(100)

plt.boxplot(data)
plt.show()

A boxplot will appear that represents the samples we drew from the random distribution. Since the code uses a randomly generated dataset, the resulting figure will change slightly every time the script is run.

The preceding script will display the following graph:

How it works...

The data = [random.gauss(0., 1.) for i in range(100)] variable generates 100 values drawn from a normal distribution. For demonstration purposes, such values are typically read from a file or computed from other data. The plot.boxplot() function takes a set of values and computes the mean, median, and other statistical quantities on its own. The following points describe the preceding boxplot:

  • The red bar is the median of the distribution.

  • The blue box includes 50 percent of the data from the lower quartile to the upper quartile. Thus, the box is centered on the median of the data.

  • The lower whisker extends to the lowest value within 1.5 IQR from the lower quartile.

  • The upper whisker extends to the highest value within 1.5 IQR from the upper quartile.

  • Values further from the whiskers are shown with a cross marker.

There's more...

To show more than one boxplot in a single graph, calling pyplot.boxplot() once for each boxplot is not going to work. It will simply draw the boxplots over each other, making a messy, unreadable graph. However, we can draw several boxplots with just one single call to pyplot.boxplot() as follows:

import numpy as np
import matplotlib.pyplot as plt

data = np.random.randn(100, 5)

plt.boxplot(data)
plt.show()

The preceding script displays the following graph:

The pyplot.boxplot() function accepts a list of lists as the input, rendering a boxplot for each sublist.