How to Change a Value in One Column based on Another Pandas

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by Abdul Rawoof A R dot icon Updated: Jan 31, 2023

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There are several ways to change values in a column of a pandas DataFrame using pandas: by changing the values in a column, you can prepare the data for further analysis, visualization, or modeling. It is an important step in the data preprocessing process and is crucial to the accuracy of any insights or predictions derived from the data.

  •  Using the loc indexer: You can use the loc indexer to change the values of a specific column by specifying the column name and a Boolean mask that selects the rows to change. 
  • Using the numpy.where() function: You can use the numpy.where() functions to change the values of a specific column based on a condition. 
  • Using the map() method: You can use the map() method to change the values of a specific column based on a dictionary of key-value pairs. 
  • Using the replace() method: You can use the replace() method to change the values of a specific column based on a dictionary of key-value pairs. 
  • Using the apply() method: You can use the apply() method to apply a custom function to a specific column. 


For better knowledge of changing values in a column using Pandas, you may have a look at the code below 

Fig : Preview of the output that you will get on running this code from your IDE.

Code

In this solution we're using Pandas library.

Instructions

Follow the steps carefully to get the output easily.

  1. Install pandas on your IDE(Any of your favorite IDE).
  2. Copy the snippet using the 'copy' and paste it in your IDE.
  3. Add required dependencies and import them in Python file.
  4. Run the file to generate the output.


I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.


I found this code snippet by searching for 'Changing the values in a column using pyhton' in kandi. You can try any such use case!

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

  1. The solution is created in PyCharm 2021.3.
  2. The solution is tested on Python 3.9.7.
  3. Pandas version-v1.5.2.


Using this solution, we are able to change values in a column using pandas with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to change values in a column using pandas.

Dependent Library

pandasby pandas-dev

Python doticonstar image 38689 doticonVersion:v2.0.2doticon
License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Support
    Quality
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            pandasby pandas-dev

            Python doticon star image 38689 doticonVersion:v2.0.2doticon License: Permissive (BSD-3-Clause)

            Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
            Support
              Quality
                Security
                  License
                    Reuse

                      You can also search for any dependent libraries on kandi like 'pandas'.

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