Slicing Pandas DataFrames Based on Number of Lines in Each Group

Understanding Dataframe Modifications in Pandas: Best Practices for Handling Changes in Original Dataframe

Looping Through Sections of a Data Frame in R: A More Efficient Approach Using Data Tables

Calculating the Average of Every x Rows in a Table Using Python and Pandas

Modifying Pandas Columns Without Changing Underlying Numpy Arrays: A Comprehensive Guide

Understanding np.select and NaN Values in Pandas DataFrames: A Guide to Working with Missing Values

Understanding Pandas Crosstabulations: Handling Missing Values and Custom Indexes

Reversing Column Order in Pandas DataFrames after Splitting String Values at Delimiters

Understanding the Pandas `drop` Function and Common Pitfalls

Here's a refactored version of the code with proper indentation, comments, and a clear structure: