Скачать или смотреть How to Export Multiple Excel Files with Conditional Formatting Using Pandas

Learn how to easily export multiple Excel files from a Pandas DataFrame while maintaining desired conditional formatting. Discover efficient methods and tips to enhance your data presentation!
---
This video is based on the question https://stackoverflow.com/q/66163955/ asked by the user 'StephenD' ( https://stackoverflow.com/u/9872821/ ) and on the answer https://stackoverflow.com/a/66246085/ provided by the user 'StephenD' ( https://stackoverflow.com/u/9872821/ ) 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: Exporting many excel files based on column value in pandas dataframe while maintaining formatting?

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 Export Multiple Excel Files with Conditional Formatting Using Pandas

If you're working with large datasets in Python, particularly using the Pandas library, you may encounter a situation where you need to export portions of your DataFrame to separate Excel files based on unique values in a column. But what if you want to ensure that these files not only contain the right data but also maintain specific formatting? In this post, we will address this common problem and showcase a streamlined solution that combines data separation and conditional formatting.

The Problem: Exporting Data with Formatting

You have a DataFrame that contains data under a column named "names," and you wish to create individual Excel files for each unique name while preserving desired formatting for ease of review and analysis. However, achieving this can be tricky, particularly if you're unsure how to apply conditional formatting during the export process.

Example Problem Setup

Suppose you have the following DataFrame:

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

Your goal is to export this DataFrame into separate Excel files for "Alice," "Bob," and "Charlie," with each file featuring conditional formatting based on the 'status' column.

The Solution: Combining Grouping and Formatting

Here’s a step-by-step solution to achieve this using Pandas and the xlsxwriter engine to set up the conditional formatting.

Step 1: Define a Function to Process Each Group

The first step involves defining a function that will handle exporting and formatting for each group in the DataFrame:

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

Step 2: Group and Apply the Function

Next, you can take advantage of Pandas' groupby method and call the previously defined function for each unique name in the DataFrame:

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

Explanation of Key Components

ExcelWriter: A context manager used for writing to Excel files.

Conditional Formatting: Styles applied to cells based on conditions (e.g., values in the 'status' column).

Grouping: Efficiently managing separate data subsets with the groupby() method allows you to iterate through unique names intuitively.

Conclusion

By following these steps, you can effectively export multiple Excel files from your Pandas DataFrame while ensuring that each file retains the appropriate formatting. This helps enhance data readability and presentation, making it easier for you and others to make informed decisions based on your exported data.

Try implementing this method for your own projects and customize the conditions and formatting styles as needed. Happy coding!