polars.Expr.arr.eval#

Expr.arr.eval(expr: Expr, *, as_list: bool = False) → Expr[source]#

Run any polars expression against the arrays’ elements.

Parameters:

expr: Expression to run. Note that you can select an element with pl.element()
as_list: Collect the resulting data as a list. This allows for expressions which output a variable amount of data.

See also

polars.Expr.arr.agg: Evaluate any expression and automatically explode.
polars.Expr.list.eval: Same for the List datatype.

Examples

>>> df = pl.DataFrame({"a": [1, 8, 3], "b": [4, 5, 2]})
>>> df.with_columns(rank=pl.concat_arr("a", "b").arr.eval(pl.element().rank()))
shape: (3, 3)
┌─────┬─────┬───────────────┐
│ a   ┆ b   ┆ rank          │
│ --- ┆ --- ┆ ---           │
│ i64 ┆ i64 ┆ array[f64, 2] │
╞═════╪═════╪═══════════════╡
│ 1   ┆ 4   ┆ [1.0, 2.0]    │
│ 8   ┆ 5   ┆ [2.0, 1.0]    │
│ 3   ┆ 2   ┆ [2.0, 1.0]    │
└─────┴─────┴───────────────┘