Скачать или смотреть How to Add Values in a Column Grouped by Rows using Python Pandas

Learn how to perform group-wise addition of values in a DataFrame column using Python's Pandas library. Explore a practical solution and achieve your desired results effortlessly!
---
This video is based on the question https://stackoverflow.com/q/73767413/ asked by the user 'bawa_91' ( https://stackoverflow.com/u/19828341/ ) and on the answer https://stackoverflow.com/a/73767449/ provided by the user 'BENY' ( https://stackoverflow.com/u/7964527/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Python Pandas : how to add values in column group by a particular row and put the result in a new column

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Mastering Groupwise Addition in Pandas DataFrames

Have you ever found yourself working with a DataFrame in Python Pandas and needed to group values by specific fields to compute sums? If yes, you’re not alone!

In this guide, we’ll walk through a common scenario where you have a DataFrame and you want to group values based on certain identifiers, calculate sums, and finally, present those sums in a new DataFrame format.

The Problem Setup

Consider the following DataFrame:

p_idb_idval1012019910120221012031110220111022025010220323From our DataFrame, we want to derive two sums for each unique p_id:

sum1, which is the sum of val for b_id 201 and 202.

sum2, which is the sum of val for b_id 201 and 203.

The desired output would look like this:

p_idsum_1sum_21011011101025124The Solution: Step-by-Step Guide

We’ll solve the above problem using a systematic approach that utilizes some powerful Pandas functions.

Step 1: Set Up Your DataFrame

First, ensure you have your DataFrame ready. Here’s how you can create it in Python:

[[See Video to Reveal this Text or Code Snippet]]

Step 2: Calculate the Sums

To calculate the required sums, we’ll follow these steps:

Add the first value of val to all rows in p_id group:

[[See Video to Reveal this Text or Code Snippet]]

Create a unique key for each row using cumcount:

[[See Video to Reveal this Text or Code Snippet]]

Pivot the DataFrame to reshape it:

[[See Video to Reveal this Text or Code Snippet]]

Clean up the DataFrame by dropping unnecessary rows:

[[See Video to Reveal this Text or Code Snippet]]

Step 3: Final Output

After performing these operations, you should get a DataFrame that looks like this:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

Now you have successfully calculated groupwise sums for each p_id in your DataFrame! This method is not only effective for this specific problem but can be adapted for various similar tasks in data manipulation.

Next time you encounter a similar requirement while using Pandas, you can efficiently implement these steps, simplifying your data handling and analysis processes.

Happy coding!