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Replace the column contains the values 'yes' and 'no' with True and False In Python-Pandas

Last Updated : 15 Jul, 2025


Let’s discuss a program To change the values from a column that contains the values 'YES' and 'NO' with TRUE and FALSE
 

First, Let's see a dataset.

Code:

Output : 

👁 Dataframe with yes and no


For downloading the used csv file Click Here.


Now, Let's see the multiple ways to do this task:


Method 1: Using Series.map()
This method is used to map values from two series having one column the same. 

Syntax: Series.map(arg, na_action=None). 
Return type: Pandas Series with the same as an index as a caller. 

Example: Replace the ‘commissioned' column contains the values 'yes' and 'no' with True and False.
Code:

Output : 

👁 Dataframe with true and false


Method 2: Using DataFrame.replace()
This method is used to replace a string, regex, list, dictionary, series, number, etc. from a data frame. 

Syntax: DataFrame.replace(to_replace=None, value=None, inplace=False, limit=None, regex=False, method=’pad’, axis=None) 
Return type: Updated Data frame 

Example: Replace the ‘commissioned' column contains the values 'yes' and 'no' with True and False.
Code:

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