Replace values for multiple columns in pandas

Question

I have the following data frame.

col1 col2 col3
1    1    1
2    2    2
3    1    2
3    3    3

I want to replace numerical values based on the following mappings

col1: {1: dog, 2: cat, 3: bird}
col2: {1: yellow, 2: orange, 3: red}
col3: {1: dave, 2: pete, 3: tom}

How can I do this in Python through method chaining?

Expected Output:

col1  col2    col3
dog   yellow  dave
cat   orange  pete
bird  yellow  pete
bird  red     tom

I know that there is a replace function but it works like the following:

df[col1].replace('old_val', 'new_val')

I want to do something like this (similar to the assign method where I can just keep adding new columns in the method):

#pseudocode
df.replace(col1 = mapping1, col2 = mapping2, col3 = mapping3)

How can I do this in pandas?

RomanPerekhrest · Accepted Answer · 2023-02-24 21:36:14Z

2

Use pd.Series.map function:

df.assign(col1=df['col1'].map(mapping1), col2=df['col2'].map(mapping2), col3=df['col3'].map(mapping3))

answered Feb 24, 2023 at 21:36

RomanPerekhrest

93.1k4 gold badges75 silver badges112 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

wjandrea · Accepted Answer · 2023-02-24 21:44:07Z

1

Use DataFrame.replace:

d = {'col1': {1: 'dog', 2: 'cat', 3: 'bird'},
     'col2': {1: 'yellow', 2: 'orange', 3: 'red'},
     'col3': {1: 'dave', 2: 'pete', 3: 'tom'}}

out = df.replace(d)

Output:

   col1    col2  col3
0   dog  yellow  dave
1   cat  orange  pete
2  bird  yellow  pete
3  bird     red   tom

edited Feb 24, 2023 at 21:44

wjandrea

34k10 gold badges69 silver badges106 bronze badges

answered Feb 24, 2023 at 21:41

mozway

267k13 gold badges56 silver badges106 bronze badges

Comments

Deep Bhatt · Accepted Answer · 2023-02-24 21:38:33Z

You can use the replace() method of the Pandas DataFrame in combination with method chaining to replace the numerical values in the data frame with the corresponding string values based on the given mappings. Here's an example code:

import pandas as pd

# Create the data frame
df = pd.DataFrame({
    'col1': [1, 2, 3, 3],
    'col2': [1, 2, 1, 3],
    'col3': [1, 2, 2, 3]
})

# Define the mappings
mapping_col1 = {1: 'dog', 2: 'cat', 3: 'bird'}
mapping_col2 = {1: 'yellow', 2: 'orange', 3: 'red'}
mapping_col3 = {1: 'dave', 2: 'pete', 3: 'tom'}

# Use method chaining to replace the numerical values with string values
df = df.replace({'col1': mapping_col1}).replace({'col2': mapping_col2}).replace({'col3': mapping_col3})

# Print the updated data frame
print(df)

This will output the following data frame with the numerical values replaced by the corresponding string values based on the given mappings:

   col1    col2  col3
0   dog  yellow  dave
1   cat  orange  pete
2  bird  yellow  pete
3  bird     red   tom

Collectives™ on Stack Overflow

Replace values for multiple columns in pandas

3 Answers 3

Comments

Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

3 Answers 3

Comments

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related