You can use the following methods to sort the rows or columns in a pandas crosstab:

Method 1: Sort Crosstab by Row Values

pd.crosstab(df.col1, df.col2).sort_index(axis=0, ascending=False)

Method 2: Sort Crosstab by Column Values

pd.crosstab(df.col1, df.col2).sort_index(axis=1, ascending=False)

The following examples show how to use each of these methods in practice with the following pandas crosstab:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'A', 'B', 'B', 'B', 'B', 'C', 'C', 'C', 'C'],
                   'position':['G', 'G', 'F', 'G', 'F', 'F', 'F', 'G', 'G', 'F', 'F'],
                   'points': [22, 25, 24, 39, 34, 20, 18, 17, 20, 19, 22]})

#create crosstab to display count of players by team and position
my_crosstab = pd.crosstab(df.team, df.position)

#view crosstab
print(my_crosstab)

position  F  G
team          
A         1  2
B         3  1
C         2  2

Example 1: Sort Crosstab by Row Values

We can use the following syntax to sort the rows of the crosstab based on the values in the team column in descending order (from Z to A):

#create crosstab with rows sorted from Z to A
pd.crosstab(df.team, df.position).sort_index(axis=0, ascending=False)

position  F	G
team		
C	  2	2
B	  3	1
A	  1	2

Notice that the rows of the crosstab are now sorted based on the team values in reverse alphabetical order.

Note: The crosstab() function displays the row values of the crosstab in alphabetical order (from A to Z) by default.

Example 2: Sort Crosstab by Column Values

We can use the following syntax to sort the columns of the crosstab based on the values in the team column in descending order (from Z to A):

#create crosstab with columns sorted from Z to A
pd.crosstab(df.team, df.position).sort_index(axis=1, ascending=False)

position  G	F
team		
A	  2	1
B	  1	3
C	  2	2

Notice that the columns of the crosstab are now sorted based on the position values in reverse alphabetical order.

Note: The crosstab() function displays the column values of the crosstab in alphabetical order (from A to Z) by default.

The following tutorials explain how to perform other common tasks in pandas: