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, Pandas is the spreadsheet. And in AI and data science, you will spend more time in that spreadsheet than anywhere else. What a DataFrame Actually Is A DataFrame is a table with labeled rows and columns. Think of it as a dictionary of arrays, all sharing the same index.…