🚀 Supercharge your YouTube channel's growth with AI.
Try YTGrowAI Free
Understanding np.nan in NumPy and Pandas
`np.sum(values)` returns `nan`, while `np.nansum(values)` returns `80.0` for the same array. I find that contrast useful because it shows how skipping a missing value changes a reduction. You’ll be able to decide whether a calculation should keep or skip missing…








