Seaborn: How to Display Mean Value on Boxplot

You can use the showmeans argument to display the mean value in boxplots created using seaborn:

sns.boxplot(data=df, x='x_var', y='y_var', showmeans=True)

The following example shows how to use this syntax in practice.

Example: Display Mean Value on Seaborn Boxplot

Suppose we have the following pandas DataFrame that shows the points scored by basketball players on three different teams:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'A', 'A', 'A', 'B', 'B', 'B',
                            'B', 'B', 'C', 'C', 'C', 'C', 'C'],
                   'points': [3, 4, 6, 8, 9, 10, 13, 16, 18, 20, 8, 9, 12, 13, 15]})

#view head of DataFrame
print(df.head())

  team  points
0    A       3
1    A       4
2    A       6
3    A       8
4    A       9

We can use the following code to create boxplots to visualize the distribution of points for each team:

import seaborn as sns

#create boxplot to visualize points distribution by team
sns.boxplot(data=df, x='team', y='points')

By default, the boxplots display the median value using a horizontal line inside each boxplot.

To display the mean value for each boxplot, you must specify showmeans=True:

import seaborn as sns

#create boxplot to visualize points distribution by team (and display mean values)
sns.boxplot(data=df, x='team', y='points', showmeans=True)

By default, seaborn uses green triangles to display the mean value for each boxplot.

To customize the appearance of the mean value, feel free to use the meanprops argument:

import seaborn as sns

#create boxplot to visualize points distribution by team
sns.boxplot(data=df, x='team', y='points', showmeans=True,
            meanprops={'marker':'o',
                       'markerfacecolor':'white', 
                       'markeredgecolor':'black',
                       'markersize':'8'})