How to Copy Values Between Columns in Pandas Based on Conditions Identifier1 and Identifier2 скачать в хорошем качестве

How to Copy Values Between Columns in Pandas Based on Conditions Identifier1 and Identifier2

Master the art of managing your pandas DataFrame and learn how to copy values between columns based on specific conditions in this detailed guide. --- This video is based on the question https://stackoverflow.com/q/68352573/ asked by the user 'GC2023' ( https://stackoverflow.com/u/16400244/ ) and on the answer https://stackoverflow.com/a/68352801/ provided by the user 'Nk03' ( https://stackoverflow.com/u/15438033/ ) 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: Copy values from one column to another column with different rows based on two conditions 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. --- How to Copy Values Between Columns in Pandas Based on Conditions Managing data in Pandas can sometimes feel daunting, especially when you need to perform specific operations on your DataFrame based on certain conditions. In this post, we will tackle a common problem: how to copy values from one column to another column with different rows based on two conditions. Specifically, we will look for values in one identifier column and use them to fill another column depending on dates. Let’s dive in! Understanding the Problem Imagine you have a DataFrame that looks like this: [[See Video to Reveal this Text or Code Snippet]] Your goal is to copy values from the price1 column to the price2 column based on the condition that Identifier2 matches Identifier1 and the dates align correctly. The resulting DataFrame should look like this: [[See Video to Reveal this Text or Code Snippet]] Step-by-Step Solution Here’s how you can achieve this in Pandas using a clear and straightforward approach. 1. Preparing Your DataFrame First, ensure you have your DataFrame set up correctly. You should have columns such as Identifier1, Identifier2, date, and price1. If you’re using the provided code snippet, you’ll initiate your DataFrame as follows: [[See Video to Reveal this Text or Code Snippet]] 2. Applying the Copy Logic To copy the values from price1 to price2 based on the conditions, you can utilize the following line of code: [[See Video to Reveal this Text or Code Snippet]] Breakdown of the Code: df[['Identifier2', 'date']].apply(tuple, 1) converts each row into tuples of Identifier2 and date. .map(df.set_index(['Identifier1', 'date'])['price1'].to_dict()) generates a dictionary that maps the odds of Date and Identifier1 to corresponding price1 values and then uses that mapping to fill in price2 accordingly. 3. Viewing the Result Once you run the above code, your DataFrame will now be updated as required. You can confirm the output by simply printing df: [[See Video to Reveal this Text or Code Snippet]] The updated DataFrame will reflect the changes: [[See Video to Reveal this Text or Code Snippet]] Conclusion By using the code snippets we provided, you can successfully copy values between columns in your DataFrame based on specific conditions using pandas. This technique can significantly streamline data manipulation tasks in your data processing pipeline. Now you're equipped to tackle similar challenges in the future! Happy coding!