You can use the following methods to change the order of boxplots along the x-axis in seaborn:

Method 1: Order Boxplots Using Custom Order

sns.boxplot(x='group_var', y='values_var', data=df, order=['A', 'B', 'C'])

Method 2: Order Boxplots Using a Metric

group_means=df.groupby(['group_var'])['values_var'].mean().sort_values(ascending=True)

sns.boxplot(x='group_var', y='values_var', data=df, order=group_means.index)

The following examples show how to use each method in practice with 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

Example 1: Order Boxplots Using Custom Order

The following code shows how to create a boxplot to visualize the distribution of points for each team and order the boxplots in the following order based on team name: C, A, B.

import seaborn as sns

#create boxplots with custom order
sns.boxplot(x='team', y='points', data=df, order=['C', 'A', 'B'])

Notice that the boxplots are ordered along the x-axis in the exact order that we specified.

Example 2: Order Boxplots Using a Metric

The following code shows how to create a boxplot to visualize the distribution of points for each team and order the boxplots in ascending order based on the mean points scored by team:

import seaborn as sns

#calculate mean points by team
mean_by_team = df.groupby(['team'])['points'].mean().sort_values(ascending=True)

#create boxplots ordered by mean points (ascending)
sns.boxplot(x='team', y='points', data=df, order=mean_by_team.index)

Notice that the boxplots are ordered along the x-axis based on the mean points value by team in ascending order.

import seaborn as sns

#calculate mean points by team
mean_by_team = df.groupby(['team'])['points'].mean().sort_values(ascending=False)

#create boxplots ordered by mean points (descending)
sns.boxplot(x='team', y='points', data=df, order=mean_by_team.index)

The boxplots are now ordered along the x-axis based on the mean points value by team in descending order.

Note: To order the boxplots based on a different metric (e.g. the median), simply specify that metric after the groupby() function in the code above.

The following tutorials explain how to perform other common functions in seaborn: