Pandas is in a separate category from all of these, including polars. If you were to say “pandas in long format only” then yes that would be correct, but the po

Pandas is in a separate category from all of these, including polars. If you were to say “pandas in long format only” then yes that would be correct, but the power of pandas comes in its ability to work in a long relational or wide ndarray style. Pandas was originally written to replace excel in financial/econometric modeling, not as a replacement for sql. Models written solely in the long relational style are near unmaintainable for constantly evolving models with hundreds of data sources and thousands of interactions being developed and tuned by teams of analysts and engineers. For example, this is how some basic operations would look in pandas. Bump prices in 2020 up $1: prices_df.loc['2020'] += 1 Add expected temperature offsets to base temperature forecast: temp_df + offset_df Now imagine thousands of such operations, and you can see the necessity of pandas in models like this.