Arik Chakma
274082fd77
* refactor: clean to roadmap content * refactor: move shared helpers into scripts/lib
9 lines
783 B
Markdown
9 lines
783 B
Markdown
# Groupby & Aggregation
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`groupby()` splits a DataFrame into groups based on one or more columns, applies a function to each group, and combines the results. Common aggregation functions include `sum()`, `mean()`, `count()`, `min()`, `max()`, and custom functions via `agg()`. This split-apply-combine pattern is one of the most powerful features of Pandas.
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Visit the following resources to learn more:
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- [@official@pandas.DataFrame.groupby](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.groupby.html)
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- [@article@All About Pandas Groupby Explained with 25 Examples](https://towardsdatascience.com/all-about-pandas-groupby-explained-with-25-examples-494e04a8ef56/)
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- [@video@Group By and Aggregate Functions in Pandas |](https://www.youtube.com/watch?v=VRmXto2YA2I) |