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The index of a Pandas DataFrame can be easily renamed using the DataFrame.rename() method. This method takes in a dictionary with the old index names as keys and new index names as values. The inplace argument can also be set to True to modify the existing DataFrame. The DataFrame.reset_index() method can also be used to reset the index and then rename it. Both of these methods work on both single and multi-level indexes.
You can use the following syntax to rename the index column of a pandas DataFrame:
df.index.rename('new_index_name', inplace=True)
The following example shows how to use this syntax in practice.
Example: Rename Index in Pandas DataFrame
Suppose we have the following pandas DataFrame:
import pandas as pd #create DataFrame df = pd.DataFrame({'points': [25, 12, 15, 14, 19, 23, 25, 29], 'assists': [5, 7, 7, 9, 12, 9, 9, 4], 'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]}) #view DataFrame df points assists rebounds 0 25 5 11 1 12 7 8 2 15 7 10 3 14 9 6 4 19 12 6 5 23 9 5 6 25 9 9 7 29 4 12
Currently the DataFrame has no index name:
#display index name print(df.index.name) None
We can use df.index.rename() to rename the index:
#rename index df.index.rename('new_index', inplace=True) #view updated DataFrame df points assists rebounds new_index 0 25 5 11 1 12 7 8 2 15 7 10 3 14 9 6 4 19 12 6 5 23 9 5 6 25 9 9 7 29 4 12
Note that inplace=True tells pandas to retain all of the original DataFrame properties.
We can verify that the DataFrame now has an index name:
#display index name print(df.index.name) new_index