How to Rename the Rows in a Pandas DataFrame

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You can use one of the following methods to rename the rows in a pandas DataFrame:

Method 1: Rename Rows Using Values from Existing Column

df = df.set_index('some_column', drop=False).rename_axis(None)

Method 2: Rename Rows Using Values from Dictionary

row_names = {'old_name0':'new_name0',
             'old_name1':'new_name1',
             'old_name2':'new_name2'}

df = df.rename(index = row_names)

The following examples shows how to use each method in practice with the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],
                   'points': [18, 22, 19, 14, 14, 11, 20, 28],
                   'assists': [5, 7, 7, 9, 12, 9, 9, 4],
                   'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]})

#view DataFrame
print(df)

  team  points  assists  rebounds
0    A      18        5        11
1    B      22        7         8
2    C      19        7        10
3    D      14        9         6
4    E      14       12         6
5    F      11        9         5
6    G      20        9         9
7    H      28        4        12

Example 1: Rename Rows Using Values from Existing Column

Currently the rows of the DataFrame are labeled from 0 to 7.

We can use the following syntax to rename the rows using the values from the team column:

import pandas as pd

#rename rows using values in the team column
df = df.set_index('team', drop=False).rename_axis(None)

#view updated DataFrame
print(df)

  team  points  assists  rebounds
A    A      18        5        11
B    B      22        7         8
C    C      19        7        10
D    D      14        9         6
E    E      14       12         6
F    F      11        9         5
G    G      20        9         9
H    H      28        4        12

Notice that the rows are now labeled from A to H, which match the values from the team column.

If you would like to drop the team column from the DataFrame when renaming the rows, you can remove the argument drop=False from the set_index() function:

import pandas as pd

#rename rows using values in the team column and drop team column
df = df.set_index('team').rename_axis(None)

#view updated DataFrame
print(df)

   points  assists  rebounds
A      18        5        11
B      22        7         8
C      19        7        10
D      14        9         6
E      14       12         6
F      11        9         5
G      20        9         9
H      28        4        12

Notice that the rows are labeled from A to H and the team column has been dropped entirely.

Example 2: Rename Rows Using Values from Dictionary

We could also define a dictionary that specifies the new row labels for the DataFrame:

import pandas as pd

#define new row names
row_names = {0:'Zero',
             1:'One',
             2:'Two',
             3:'Three',
             4:'Four',
             5:'Five',
             6:'Six',
             7:'Seven'}

#rename values in index using dictionary called row_names
df = df.rename(index = row_names)

#view updated DataFrame
print(df)

      team  points  assists  rebounds
Zero     A      18        5        11
One      B      22        7         8
Two      C      19        7        10
Three    D      14        9         6
Four     E      14       12         6
Five     F      11        9         5
Six      G      20        9         9
Seven    H      28        4        12

Notice the row names of the DataFrame now match those that we specified in the dictionary.

Additional Resources

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

How to Rename Index in Pandas
How to Rename Columns in Pandas
How to Rename Columns in Groupby Function in Pandas