*
* A horizontal rank computation by taking the elements of a list
*
* >df = pl.DataFrame({"a": [1, 8, 3], "b": [4, 5, 2]})
* >df.withColumn(
* ... pl.concatList(["a", "b"]).arr.eval(pl.element().rank()).alias("rank")
* ... )
* shape: (3, 3)
* ┌─────┬─────┬────────────┐
* │ a ┆ b ┆ rank │
* │ --- ┆ --- ┆ --- │
* │ i64 ┆ i64 ┆ list[f32] │
* ╞═════╪═════╪════════════╡
* │ 1 ┆ 4 ┆ [1.0, 2.0] │
* ├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤
* │ 8 ┆ 5 ┆ [2.0, 1.0] │
* ├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌┤
* │ 3 ┆ 2 ┆ [2.0, 1.0] │
* └─────┴─────┴────────────┘
*
* A mathematical operation on array elements
*
* >df = pl.DataFrame({"a": [1, 8, 3], "b": [4, 5, 2]})
* >df.withColumn(
* ... pl.concatList(["a", "b"]).arr.eval(pl.element().multiplyBy(2)).alias("a_b_doubled")
* ... )
* shape: (3, 3)
* ┌─────┬─────┬─────────────┐
* │ a ┆ b ┆ a_b_doubled │
* │ --- ┆ --- ┆ --- │
* │ i64 ┆ i64 ┆ list[i64] │
* ╞═════╪═════╪═════════════╡
* │ 1 ┆ 4 ┆ [2, 8] │
* ├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
* │ 8 ┆ 5 ┆ [16, 10] │
* ├╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
* │ 3 ┆ 2 ┆ [6, 4] │
* └─────┴─────┴─────────────┘
Alias for an element in evaluated in an
eval
expression.