Iterating over Pandas DataFrames can cost you much performance.

Comparing iterrows() and itertuples() can help in some cases:


1. 𝗶𝘁𝗲𝗿𝗿𝗼𝘄𝘀():

Generates index and Series pairs for each row.

𝗣𝗿𝗼𝘀: Easy to use and intuitive. Suitable for small datasets.

𝗖𝗼𝗻𝘀: Slow for large datasets. Series conversion incurs additional overhead.

𝗨𝘀𝗲 𝗖𝗮𝘀𝗲: Quick data inspection and small-scale transformations.


2. 𝗶𝘁𝗲𝗿𝘁𝘂𝗽𝗹𝗲𝘀():

Returns namedtuples of the DataFrame rows.

𝗣𝗿𝗼𝘀: Much faster than iterrows(). More efficient for large datasets.

𝗖𝗼𝗻𝘀: Slightly less intuitive syntax. Avoid using when mutating DataFrames.

𝗨𝘀𝗲 𝗖𝗮𝘀𝗲: Large-scale data processing and read-only operations.


For optimal performance, use vectorized operations whenever possible! Iteration methods should be your last resort!