How to Keep Certain Columns in Pandas (With Examples)

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You can use the following methods to only keep certain columns in a pandas DataFrame:

Method 1: Specify Columns to Keep

#only keep columns 'col1' and 'col2'
df[['col1', 'col2']]

Method 2: Specify Columns to Drop

#drop columns 'col3' and 'col4'
df[df.columns[~df.columns.isin(['col3', 'col4'])]]

The following examples show how to use each method with the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'A', 'B', 'B', 'B'],
                   'points': [11, 7, 8, 10, 13, 13],
                   'assists': [5, 7, 7, 9, 12, 9],
                   'rebounds': [11, 8, 10, 6, 6, 5]})

#view DataFrame
df

	team	points	assists	rebounds
0	A	11	5	11
1	A	7	7	8
2	A	8	7	10
3	B	10	9	6
4	B	13	12	6
5	B	13	9	5

Method 1: Specify Columns to Keep

The following code shows how to define a new DataFrame that only keeps the “team” and “points” columns:

#create new DataFrame and only keep 'team' and 'points' columns
df2 = df[['team', 'points']]

#view new DataFrame
df2

        team	points
0	A	11
1	A	7
2	A	8
3	B	10
4	B	13
5	B	13

Notice that the resulting DataFrame only keeps the two columns that we specified.

Method 2: Specify Columns to Drop

The following code shows how to define a new DataFrame that drops the “assists” and “rebounds” columns from the original DataFrame:

#create new DataFrame and that drops 'assists' and 'rebounds'
df2 = df[df.columns[~df.columns.isin(['assists', 'rebounds'])]]

#view new DataFrame
df2

        team	points
0	A	11
1	A	7
2	A	8
3	B	10
4	B	13
5	B	13

Notice that the resulting DataFrame drops the “assists” and “rebounds” columns from the original DataFrame and keeps the remaining columns.