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 to a new value for an individual DataFrame column:

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

(2) Replace multiple values to 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 to 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 to 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:

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 to ‘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 to ‘Green’ values under the first column:

But what if you want to replace multiple values to 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 to 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 to a ‘Green’ color under the first column:

Suppose that you want to replace multiple values to 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 to a ‘Green’ color; and
• The ‘Red’ color to 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 to 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 into ‘Green’ across the entire DataFrame: