How to Replace Values in a Pandas DataFrame (With Examples)

Often you may want to replace the values in one or more columns of a pandas DataFrame.

Fortunately this is easy to do using the .replace() function.

This tutorial provides several examples of how to use this function in practice on the following DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'B', 'B', 'B', 'C', 'C'],
                   'division':['E', 'W', 'E', 'E', 'W', 'W', 'E'],
                   'rebounds': [11, 8, 7, 6, 6, 5, 12]})

#view DataFrame
print(df)

  team division  rebounds
0    A        E        11
1    A        W         8
2    B        E         7
3    B        E         6
4    B        W         6
5    C        W         5
6    C        E        12

Example 1: Replace a Single Value in an Entire DataFrame

The following code shows how to replace a single value in an entire pandas DataFrame:

#replace 'E' with 'East'
df = df.replace(['E'],'East')

#view DataFrame
print(df)

  team division  rebounds
0    A     East        11
1    A        W         8
2    B     East         7
3    B     East         6
4    B        W         6
5    C        W         5
6    C     East        12

Example 2: Replace Multiple Values in an Entire DataFrame

The following code shows how to replace multiple values in an entire pandas DataFrame:

#replace 'E' with 'East' and 'W' with 'West'
df = df.replace(['E', 'W'],['East', 'West'])

#view DataFrame
print(df)

        team	division  rebounds
0	A	East	  11
1	A	West	  8
2	B	East	  7
3	B	East	  6
4	B	West	  6
5	C	West	  5
6	C	East	  12

Example 3: Replace a Single Value in a Single Column

The following code shows how to replace a single value in a single column:

#replace 6 with 0 in rebounds column
df['rebounds'] = df['rebounds'].replace(6, 0)

#view DataFrame
print(df)

        team	division  rebounds
0	A	E	  11
1	A	W	  8
2	B	E	  7
3	B	E	  0
4	B	W	  0
5	C	W	  5
6	C	E	  12

Example 4: Replace Multiple Values in a Single Column

The following code shows how to replace multiple values in a single column:

#replace 6, 11, and 8 with 0, 1 and 2 in rebounds column
df['rebounds'] = df['rebounds'].replace([6, 11, 8], [0, 1, 2])

#view DataFrame
print(df)

team	division	rebounds
0	A	E	1
1	A	W	2
2	B	E	7
3	B	E	0
4	B	W	0
5	C	W	5
6	C	E	12

Additional Resources

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

How to Replace NaN Values with Zeros in Pandas
How to Replace Empty Strings with NaN in Pandas
How to Replace Values in Column Based on Condition in Pandas