How to add plot inside another plot

logo of a chart:Colours

In Matplotlib, you can enhance the informativeness and visual appeal of your charts by incorporating a plot within the main plot.

This step-by-step guide elucidates the process and offers insights into customizing the inset plot to suit your needs.

Libraries

First, we need to install the following libraries:

  • matplotlib: for plotting
  • mpl_toolkits: for adding sub plots
  • pandas: for data manipulation
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes

import pandas as pd

Dataset

Let's create a simple dataset for this post:

x = ['Group A', 'Group B', 'Group C', 'Group D']
y = [38, 47, 25, 30]

df = pd.DataFrame(
    {'x': x,
     'y': y}
)

Simple chart

Here is a simple barplot using matplotlib:

fig, ax = plt.subplots(figsize=(8, 6))
ax.bar(df['x'], df['y'])
plt.show()

Sub plot

Having a smaller plot inside a bigger one is a good way to show more information, either for a legend or a zoom-in.

In practice, we add an Axes object (which is basically a plot) inside another Axes object. This is done using the inset_axes() function from the mpl_toolkits library.

For this, we have to define the parent axes (the bigger plot) and the size of the smaller plot.

fig, ax = plt.subplots(figsize=(8, 8))
ax.bar(df['x'], df['y'])

sub_ax = inset_axes(
    parent_axes=ax,
    width="40%",
    height="30%",
    borderpad=1  # padding between parent and inset axes
)

plt.show()

Add content in the sub plot

Once the sub plot is created, we can work on it as if it was a regular axes object:

fig, ax = plt.subplots(figsize=(8, 8))

# main plot
ax.bar(df['x'], df['y'])

# create inset plot
sub_ax = inset_axes(
    parent_axes=ax,
    width="40%",
    height="30%",
    borderpad=1  # padding between parent and inset axes
)

# add content inside inset plot
random_variable = [1, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]
sub_ax.hist(
    random_variable,
    bins=5,
    color='red',
    alpha=0.5
)

plt.show()

Customize the sub plot

We can easily customize all features of the inset plot:

  • dimensions by modifying the width and height parameters
  • position by modifying the loc parameter
  • background color by modifying the facecolor parameter
  • and many more...
fig, ax = plt.subplots(figsize=(8, 8))

# main plot
ax.bar(df['x'], df['y'], color='#d5e9f5')

# create inset plot
sub_ax = inset_axes(
    parent_axes=ax,
    width=3.5,
    height=1.5,
    loc='center',
    axes_kwargs={
        'facecolor': '#beface'
    }
)

# add content inside inset plot
random_variable = [1, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5]
sub_ax.hist(
    random_variable,
    bins=5,
    color='red',
    alpha=0.5
)
sub_ax.set_title('Histogram of Random Variable')

plt.show()

Going further

This article explains how to create a sub plot in a chart using matplotlib.

For more examples of advanced customization, check out this beautiful chart where the legend is actually a sub plot and how to add an image in a chart.

Animation with python

Animation

Contact & Edit


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