---

You can use the following syntax to sort a pandas DataFrame by both index and column:

df = df.sort_values(by = ['column_name', 'index'], ascending = [False, True])

The following examples show how to use this syntax in practice.

Examples: Sort DataFrame by Both Index and Column

The following code shows how to sort a pandas DataFrame by the column named points and then by the index column:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'id': [1, 2, 3, 4, 5, 6, 7, 8],
                   'points': [25, 15, 15, 14, 20, 20, 25, 29],
                   'assists': [5, 7, 7, 9, 12, 9, 9, 4],
                   'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]}).set_index('id')

#view first few rows
df.head()

	points	assists	rebounds
id			
1	25	5	11
2	15	7	8
3	15	7	10
4	14	9	6
5	20	12	6

#sort by points and then by index
df.sort_values(by = ['points', 'id'], ascending = [False, True])

	points	assists	rebounds
id			
8	29	4	12
1	25	5	11
7	25	9	9
5	20	12	6
6	20	9	5
2	15	7	8
3	15	7	10
4	14	9	6

The resulting DataFrame is sorted by points in descending order and then by the index in ascending order (if there happen to be two players who score the same number of points).

Note that if we don’t use the ascending argument, then each column will use ascending as the default sorting method:

#sort by points and then by index
df.sort_values(by = ['points', 'id'])

        points	assists	rebounds
id			
4	14	9	6
2	15	7	8
3	15	7	10
5	20	12	6
6	20	9	5
1	25	5	11
7	25	9	9
8	29	4	12

If the index column is currently not named, you can rename it and then sort accordingly:

#sort by points and then by index
df.rename_axis('index').sort_values(by = ['points', 'id'])

        points	assists	rebounds
id			
4	14	9	6
2	15	7	8
3	15	7	10
5	20	12	6
6	20	9	5
1	25	5	11
7	25	9	9
8	29	4	12

Additional Resources