Groupby vs Crosstab

In pandas, Groupby and Crosstab serve related but distinct purposes for data aggregation and summarization.

• groupby is more flexible for aggregation and transformations,
• whereas crosstab is specifically designed for creating frequency tables and exploring the relationship between categorical variables.

In DE_Tools see:

• https://github.com/rhyslwells/DE_Tools/blob/main/Explorations/Transformation/reshaping.ipynb

Key Differences

1. Purpose:

   • groupby: Used for performing aggregate functions (sum, mean, count, etc.) on grouped data.
   • crosstab: Used for generating frequency tables or contingency tables.

2. Output:

   • groupby: Returns a DataFrame with aggregated values.
   • crosstab: Returns a DataFrame with counts or specified aggregation functions applied across two or more columns.

3. Usage:

   • groupby: Can be used with multiple aggregation functions and complex groupings.
   • crosstab: Typically used for counting occurrences and exploring the relationship between two categorical variables.