Скачать или смотреть Formatting float in Pandas DataFrame with Lists for Better Readability

Learn how to format `float` values in a Pandas DataFrame, including lists, to achieve cleaner and more readable output when converting to string.
---
This video is based on the question https://stackoverflow.com/q/64971314/ asked by the user 'Odin' ( https://stackoverflow.com/u/5143653/ ) and on the answer https://stackoverflow.com/a/64971519/ provided by the user 'oskros' ( https://stackoverflow.com/u/9490769/ ) 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: Pandas format cells containing list of float in Pandas DataFrame to_string

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.
---
Formatting Float Values in Pandas DataFrame with List of Floats

When working with data, especially in scientific computing or data analysis, you might find yourself needing to present your data in a clean and understandable format. One common task is to display float values in a Pandas DataFrame, particularly when these floats are nested within lists. In this guide, we’ll explore how to format these float values in your DataFrame for better readability.

The Problem: Displaying Lists of Floats in Pandas DataFrame

Suppose you have a Pandas DataFrame that includes a column with complex data types—a list of float values. Here’s a quick look at our example DataFrame:

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

The challenge arises when you use the to_string() method, as it will format the floats in one of the columns correctly while leaving the list of floats unformatted.

Example Output Before Formatting

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

The Solution: Proper Formatting Using the float_format Argument

To format both individual float values and those contained within lists in a specific way, we can create a custom formatting function. Here’s how:

Step 1: Define the Formatting Function

We create a function called float2string that converts float values to a formatted string according to our requirements:

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

Step 2: Use the Custom Function in to_string()

Now, we utilize the float_format argument, alongside a specific formatter for col3, to properly format the output when calling to_string():

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

Example Output After Formatting

Running the above code will yield an output that looks like this:

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

Conclusion

Formatting float values in a Pandas DataFrame, especially when they exist within lists, can enhance the readability of your data presentation. By creating and utilizing a custom formatting function, you can achieve consistent output across your DataFrame, ensuring that both stand-alone floats and those in lists are formatted as desired.

This approach not only solves the problem at hand but also aligns your data presentation with best practices in data analysis and reporting. Whether you are preparing data for reports or further analysis, well-formatted data can make a significant difference!

Keep experimenting with your DataFrames, and happy coding!