polars.LazyFrame.groupby¶
- LazyFrame.groupby(by: Union[str, List[str], polars.internals.expr.Expr, List[polars.internals.expr.Expr]], maintain_order: bool = False) polars.internals.lazy_frame.LazyGroupBy[polars.internals.lazy_frame.LDF]¶
Start a groupby operation.
- Parameters
- by
Column(s) to group by.
- maintain_order
Make sure that the order of the groups remain consistent. This is more expensive than a default groupby.
Examples
>>> df = pl.DataFrame( ... { ... "a": ["a", "b", "a", "b", "b", "c"], ... "b": [1, 2, 3, 4, 5, 6], ... "c": [6, 5, 4, 3, 2, 1], ... } ... ).lazy() # does NOT work: # df.groupby("a")["b"].sum().collect() # ^^^^ TypeError: 'LazyGroupBy' object is not subscriptable # instead, use .agg(): >>> df.groupby("a").agg(pl.col("b").sum()).collect() shape: (3, 2) ┌─────┬─────┐ │ a ┆ b │ │ --- ┆ --- │ │ str ┆ i64 │ ╞═════╪═════╡ │ c ┆ 6 │ ├╌╌╌╌╌┼╌╌╌╌╌┤ │ b ┆ 11 │ ├╌╌╌╌╌┼╌╌╌╌╌┤ │ a ┆ 4 │ └─────┴─────┘