How to Replace Values in Pandas DataFrame

Depending on your needs, you may use either of the following methods to replace values in Pandas DataFrame:

(1) Replace a single value with a new value for an individual DataFrame column:

df['column name'] = df['column name'].replace(['old value'],'new value')

(2) Replace multiple values with a new value for an individual DataFrame column:

df['column name'] = df['column name'].replace(['1st old value','2nd old value',...],'new value')

(3) Replace multiple values with multiple new values for an individual DataFrame column:

df['column name'] = df['column name'].replace(['1st old value','2nd old value',...],['1st new value','2nd new value',...])

(4) Replace a single value with a new value for an entire DataFrame:

df = df.replace(['old value'],'new value')

In the next section, you’ll see how to apply the above templates in practice.

Steps to Replace Values in Pandas DataFrame

Step 1: Gather your Data

To begin, gather your data with the values that you’d like to replace.

For example, I gathered the following data about different colors:

first_set	second_set
Green	Yellow
Green	Yellow
Green	Yellow
Blue	White
Blue	White
Red	Blue
Red	Blue
Red	Blue

You’ll later see how to replace some of the colors in the above table.

Step 2: Create the DataFrame

Next, create the DataFrame based on the data that was captured in step 1:

import pandas as pd

colors = {'first_set':  ['Green','Green','Green','Blue','Blue','Red','Red','Red'],
          'second_set': ['Yellow','Yellow','Yellow','White','White','Blue','Blue','Blue']
         }

df = pd.DataFrame(colors, columns= ['first_set','second_set'])

print (df)

Run the code in Python, and you’ll see the following DataFrame:

Step 3: Replace Values in Pandas DataFrame

Let’s now replace all the ‘Blue’ values with ‘Green’ values under the ‘first_set’ column.

You may then use the following template to accomplish this goal:

df['column name'] = df['column name'].replace(['old value'],'new value')

And this is the complete Python code for our example:

import pandas as pd

colors = {'first_set':  ['Green','Green','Green','Blue','Blue','Red','Red','Red'],
          'second_set': ['Yellow','Yellow','Yellow','White','White','Blue','Blue','Blue']
         }

df = pd.DataFrame(colors, columns= ['first_set','second_set'])
df['first_set'] = df['first_set'].replace(['Blue'],'Green')

print (df)

Run the code, and you’ll notice that all the ‘Blue’ values got replaced with ‘Green’ values under the first column:

But what if you want to replace multiple values with a new value for an individual DataFrame column?

If that’s the case, you may use this template:

df['column name'] = df['column name'].replace(['1st old value','2nd old value',...],'new value')

Let’s say that you’d like to replace the ‘Blue’ and ‘Red’ colors with a ‘Green’ color under the ‘first_set’ column.

This it the syntax that you may use in Python:

import pandas as pd

colors = {'first_set':  ['Green','Green','Green','Blue','Blue','Red','Red','Red'],
          'second_set': ['Yellow','Yellow','Yellow','White','White','Blue','Blue','Blue']
         }

df = pd.DataFrame(colors, columns= ['first_set','second_set'])
df['first_set'] = df['first_set'].replace(['Blue','Red'],'Green')

print (df)

You’ll now notice that both the ‘Blue’ and ‘Red’ colors got replaced with a ‘Green’ color under the first column:

Suppose that you want to replace multiple values with multiple new values for an individual DataFrame column.

In that case, you may use this template:

df['column name'] = df['column name'].replace(['1st old value','2nd old  value',...],['1st new value','2nd new value',...])

Let’s say that you want to replace:

• The ‘Blue’ color with a ‘Green’ color; and
• The ‘Red’ color with a ‘White’ color

You can then apply this code in Python:

import pandas as pd

colors = {'first_set':  ['Green','Green','Green','Blue','Blue','Red','Red','Red'],
          'second_set': ['Yellow','Yellow','Yellow','White','White','Blue','Blue','Blue']
         }

df = pd.DataFrame(colors, columns= ['first_set','second_set'])
df['first_set'] = df['first_set'].replace(['Blue','Red'],['Green','White'])

print (df)

You’ll notice that the ‘Blue’ became ‘Green’ and the ‘Red’ became ‘White’ under the first column:

So far you have seen how to replace the values under an individual DataFrame column.

But what if you’d like to replace a value across the entire DataFrame?

In that case, you may use the following template:

df = df.replace(['old value'],'new value')

For example, you may run the code below in order to replace the ‘Blue’ color with a ‘Green’ color throughout the entire DataFrame:

import pandas as pd

colors = {'first_set':  ['Green','Green','Green','Blue','Blue','Red','Red','Red'],
          'second_set': ['Yellow','Yellow','Yellow','White','White','Blue','Blue','Blue']
         }

df = pd.DataFrame(colors, columns= ['first_set','second_set'])
df = df.replace(['Blue'],'Green')

print (df)

Once you run the code, you’ll see that ‘Blue’ became ‘Green’ across all the columns in the DataFrame:

And if you decided, for example, to replace two colors, such as ‘Blue’ and ‘Red’ into ‘Green,’ then you may use this syntax:

import pandas as pd

colors = {'first_set':  ['Green','Green','Green','Blue','Blue','Red','Red','Red'],
          'second_set': ['Yellow','Yellow','Yellow','White','White','Blue','Blue','Blue']
         }

df = pd.DataFrame(colors, columns= ['first_set','second_set'])
df = df.replace(['Blue','Red'],'Green')

print (df)

Both the ‘Blue’ and ‘Red’ colors would now get replaced with ‘Green’ across the entire DataFrame: