NumPy is for numbers. Pure numbers, same type, organized in grids. Fast, powerful, no labels. Real data is not like that.
Real data has column names. It has strings mixed with numbers. It has dates. It has missing values.
It has a mix of ages, salaries, cities, and booleans all in the same table. NumPy cannot handle that cleanly. Pandas was built specifically for it. If NumPy is a calculator, Pand