You can use the loc function in pandas to select multiple columns in a DataFrame by label.

Here are the most common ways to do so:

Method 1: Select Multiple Columns by Name

df.loc[:, ['col2', 'col4']]

Method 2: Select All Columns in Range

df.loc[:, 'col2':'col4']

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

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],
                   'points': [5, 7, 7, 9, 12, 9, 9, 4],
                   'assists': [11, 8, 10, 6, 6, 5, 9, 12],
                   'rebounds': [6, 7, 7, 6, 10, 12, 10, 9]})

#view DataFrame
print(df)

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

Example 1: Select Multiple Columns by Name

The following code shows how to use the loc function to select the ‘points’ and ‘rebounds’ columns from the DataFrame:

#select points and rebounds columns
df.loc[:, ['points', 'rebounds']]

        points	rebounds
0	5	6
1	7	7
2	7	7
3	9	6
4	12	10
5	9	12
6	9	10
7	4	9

Notice that each row from the ‘points’ and ‘rebounds’ columns are returned.

Also note that the order you specify the columns in the loc function is the order they’ll be returned in.

For example, we could return the ‘rebounds’ column first and then the ‘points’ column:

#select rebounds and points columns
df.loc[:, ['rebounds', 'points']]

	rebounds points
0	6	 5
1	7	 7
2	7	 7
3	6	 9
4	10	 12
5	12	 9
6	10	 9
7	9	 4

Example 2: Select All Columns in Range

The following code shows how to use the loc function to select all columns between the ‘points’ and ‘rebounds’ columns in the DataFrame:

#select all columns between points and rebounds columns
df.loc[:, 'points':'rebounds']

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

Notice that all columns between the ‘points’ and ‘rebounds’ columns in the DataFrame are returned.

Note: To select columns by index position, use the function instead.

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

How to Select Rows Based on Column Values in Pandas