Скачать с ютуб How to Alter Each Cell in a Pandas Column Based on Another Column в хорошем качестве

How to Alter Each Cell in a Pandas Column Based on Another Column

Learn how to effectively modify each cell in a Pandas DataFrame column using values from another column. This guide will break down the process step-by-step. --- This video is based on the question https://stackoverflow.com/q/71790925/ asked by the user 'JoshAsh' ( https://stackoverflow.com/u/15465797/ ) and on the answer https://stackoverflow.com/a/71790961/ provided by the user 'Hamzah' ( https://stackoverflow.com/u/16733101/ ) 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: alter each cell in column based on its row 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. --- Working with Pandas: Altering a Column Based on Another Column's Values Pandas is one of the most popular libraries in Python for data manipulation and analysis. It provides powerful data structures, making it easier to work with structured data. A common task when using Pandas is to modify the values in one column based on the values in another column. This guide will guide you through how to achieve this effectively. The Problem Suppose you have a DataFrame that looks like this: wordposnegunsup0poker-fac1111giggler1112pre-cod1113single-hand1114correctly.it111The question arises: How can you modify the ‘pos’ column using the values from the ‘word’ column? Specifically, you might want to count how many times a particular character or substring appears in each entry of the ‘word’ column, and use that count to set the corresponding value in the ‘pos’ column. The Solution Pandas offers a straightforward way to manipulate DataFrame columns with vectorized operations. In this case, you can use the .str.count() method to count occurrences of a substring in each entry of the 'word' column and assign that count directly to the 'pos' column. Step-by-Step Breakdown Access the DataFrame: First, make sure you have the DataFrame loaded. The example shown above is what we will be using. Use the .str.count() Method: This method allows you to count the instances of a substring within each string in the specified column. It returns a Series object that contains the count for each corresponding row. Assign the Count to Another Column: You can directly assign the resulting Series to the target column ('pos' in this case). Example Code Below is a simple code snippet demonstrating how to apply the above steps: [[See Video to Reveal this Text or Code Snippet]] Expected Output When you run the code above, you will modify the 'pos' column to reflect the count of the letter 'g' in each corresponding entry in the 'word' column: wordposnegunsup0poker-fac0111giggler1112pre-cod0113single-hand0114correctly.it011Conclusion In this post, we discussed how to alter a specific column in a Pandas DataFrame based on the values of another column. By utilizing the .str.count() method, you can efficiently manipulate your data and derive meaningful insights. Whether you're counting characters, phrases, or anything else within your string data, Pandas provides the tools necessary to accomplish this seamlessly. Happy coding!