How to Create a Stacked Bar Plot in Seaborn (Step-by-Step)


A stacked bar plot is a type of chart that uses bars divided into a number of sub-bars to visualize the values of multiple variables at once.

This tutorial provides a step-by-step example of how to create the following stacked bar plot in Python using the Seaborn data visualization package:

stacked bar chart in seaborn

Step 1: Create the Data

First, let’s create the following pandas DataFrame that shows the total number of customers that a restaurant receives in the morning and evening from Monday through Friday:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'Day': ['Mon', 'Tue', 'Wed', 'Thur', 'Fri'],
                   'Morning': [44, 46, 49, 59, 54],
                   'Evening': [33, 46, 50, 49, 60]})

#view DataFrame
df

	Day	Morning	Evening
0	Mon	44	33
1	Tue	46	46
2	Wed	49	50
3	Thur	59	49
4	Fri	54	60

Step 2: Create the Stacked Bar Chart

We can use the following code to create a stacked bar chart to visualize the total customers each day:

import matplotlib.pyplot as plt
import seaborn as sns

#set seaborn plotting aesthetics
sns.set(style='white')

#create stacked bar chart
df.set_index('Day').plot(kind='bar', stacked=True, color=['steelblue', 'red'])

The x-axis displays the day of the week and the bars display how many customers visited the restaurant in the morning and evening each day.

Step 3: Customize the Stacked Bar Chart

The following code shows how to add axis titles, add an overall title, and rotate the x-axis labels to make them easier to read:

import matplotlib.pyplot as plt
import seaborn as sns

#set seaborn plotting aesthetics
sns.set(style='white')

#create stacked bar chart
df.set_index('Day').plot(kind='bar', stacked=True, color=['steelblue', 'red'])

#add overall title
plt.title('Customers by Time & Day of Week', fontsize=16)

#add axis titles
plt.xlabel('Day of Week')
plt.ylabel('Number of Customers')

#rotate x-axis labels
plt.xticks(rotation=45)

stacked bar chart in seaborn

Note: We set the seaborn style to ‘white’ for this plot, but you can find a complete list of seaborn plotting aesthetics on this page.

Additional Resources

The following tutorials explain how to create other common visualizations in Seaborn:

How to Create a Pie Chart in Seaborn
How to Create a Time Series Plot in Seaborn
How to Create an Area Chart in Seaborn

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