How to Use the assign() Method in Pandas (With Examples)

The assign() method can be used to add new columns to a pandas DataFrame.

This method uses the following basic syntax:

df.assign(new_column = values)

It’s important to note that this method will only output the new DataFrame to the console, but it won’t actually modify the original DataFrame.

To modify the original DataFrame, you would need to store the results of the assign() method in a new variable.

The following examples show how to use the assign() method in different ways with the following pandas DataFrame:

import pandas as pd

#define 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
print(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

Example 1: Assign New Variable to DataFrame

The following code shows how to use the assign() method to add a new variable to the DataFrame called points2 whose values are equal to the values in the points column multiplied by two:

#add new variable called points2
df.assign(points2 = df.points * 2)

    points  assists	rebounds   points2
0	25	  5	      11	50
1	12	  7	       8	24
2	15	  7	      10	30
3	14	  9	       6	28
4	19	 12	       6	38
5	23	  9	       5	46
6	25	  9	       9	50
7	29	  4	      12	58

Note that this assign() method doesn’t change the original DataFrame.

If we print the original DataFrame, we’ll see that it remains unchanged:

#print original DataFrame
print(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

To save the results of the assign() method, we can store the results in a new DataFrame:

#add new variable called points2 and save results in new DataFrame
df.assign(points2 = df.points * 2)

#view new DataFrame
print(df_new)

   points  assists  rebounds  points2
0      25        5        11       50
1      12        7         8       24
2      15        7        10       30
3      14        9         6       28
4      19       12         6       38
5      23        9         5       46
6      25        9         9       50
7      29        4        12       58

The new DataFrame called df_new now contains the points2 column that we created.

Example 2: Assign Multiple New Variables to DataFrame

The following code shows how to use the assign() method to add three new variables to the DataFrame:

#add three new variables to DataFrame and store results in new DataFrame
df_new = df.assign(points2 = df.points * 2,
                   assists_rebs = df.assists + df.rebounds,
                   conference = 'Western')

#view new DataFrame
print(df_new)

   points  assists  rebounds  points2  assists_rebs conference
0      25        5        11       50            16    Western
1      12        7         8       24            15    Western
2      15        7        10       30            17    Western
3      14        9         6       28            15    Western
4      19       12         6       38            18    Western
5      23        9         5       46            14    Western
6      25        9         9       50            18    Western
7      29        4        12       58            16    Western

Notice that three new columns have been added to the DataFrame.

Note: You can find the complete documentation for the pandas assign() method here.

Additional Resources

The following tutorials explain how to use other common functions in pandas:

How to Use describe() Function in Pandas
How to Use idxmax() Function in Pandas
How to Apply a Function to Selected Columns in Pandas