Pandas: How to Add Prefix to Column Names

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You can use the following methods to add a prefix to column names in a pandas DataFrame:

Method 1: Add Prefix to All Column Names

df = df.add_prefix('my_prefix_')

Method 2: Add Prefix to Specific Column Names

#specify columns to add prefix to
cols = ['col1', 'col3']

#add prefix to specific columns
df = df.rename(columns={c: 'my_prefix_'+c for c in df.columns if c in cols})

The following examples show how to use each of these methods with the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'points': [25, 12, 15, 14, 19, 23],
                   'assists': [5, 7, 7, 9, 12, 9],
                   'rebounds': [11, 8, 10, 6, 6, 5],
                   'blocks': [6, 6, 3, 2, 7, 9]})

#view DataFrame
print(df)

   points  assists  rebounds  blocks
0      25        5        11       6
1      12        7         8       6
2      15        7        10       3
3      14        9         6       2
4      19       12         6       7
5      23        9         5       9

Method 1: Add Prefix to All Column Names

The following code shows how to add the prefix ‘_total’ to all column names:

#add 'total_' as prefix to each column name
df = df.add_prefix('total_')

#view updated DataFrame
print(df)

   total_points  total_assists  total_rebounds  total_blocks
0            25              5              11             6
1            12              7               8             6
2            15              7              10             3
3            14              9               6             2
4            19             12               6             7
5            23              9               5             9

Notice that the prefix ‘_total’ has been added to all column names.

Method 2: Add Prefix to Specific Column Names

The following code shows how to add the prefix ‘total_’ to only the points and assists columns:

#specify columns to add prefix to
cols = ['points', 'assists']

#add _'total' as prefix to specific columns
df = df.rename(columns={c: 'total_'+c for c in df.columns if c in cols})

#view updated DataFrame
print(df)

   total_points  total_assists  rebounds  blocks
0            25              5        11       6
1            12              7         8       6
2            15              7        10       3
3            14              9         6       2
4            19             12         6       7
5            23              9         5       9

Notice that the prefix ‘total_’ has only been added to the points and assists columns.

Additional Resources

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

How to Drop Columns in Pandas
How to Exclude Columns in Pandas
How to Change the Order of Columns in Pandas
How to Apply Function to Selected Columns in Pandas