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 pdDataset
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
widthandheightparameters - position by modifying the
locparameter - background color by modifying the
facecolorparameter - 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.
