Allow element wise computation based on another column in list.eval(pl.element() ... )

[lyngc]

Description

Would like to do computation on each element in a list based on some scalar stored in another column. Could not figure out if this is already possible.

Example:

import polars as pl

df = pl.DataFrame({
    "some_list": [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
    "scalar": [0.1, 0.2, 0.3]
})

df.with_columns(some_scaled_list=pl.col("some_list").list.eval(pl.element() * 0.2)) # Works
df.with_columns(some_scaled_list=pl.col("some_list").list.eval(pl.element() * pl.col("scalar"))) # Throws an error

[deanm0000]

semi similar to this

[cmdlineluser]

This can now be done outside of .list.eval #19162

df.with_columns(result = pl.col.some_list * pl.col.scalar)
# shape: (3, 3)
# ┌───────────┬────────┬─────────────────┐
# │ some_list ┆ scalar ┆ result          │
# │ ---       ┆ ---    ┆ ---             │
# │ list[i64] ┆ f64    ┆ list[f64]       │
# ╞═══════════╪════════╪═════════════════╡
# │ [1, 2, 3] ┆ 0.1    ┆ [0.1, 0.2, 0.3] │
# │ [4, 5, 6] ┆ 0.2    ┆ [0.8, 1.0, 1.2] │
# │ [7, 8, 9] ┆ 0.3    ┆ [2.1, 2.4, 2.7] │
# └───────────┴────────┴─────────────────┘

[lyngc]

That's nice, thank you!