Given a Polars df like below, how can I call explode() on both columns while expanding the null entry to the correct length to match up with its row?

shape: (3, 2)
┌───────────┬─────────────────────┐
│ x         ┆ y                   │
│ ---       ┆ ---                 │
│ list[i64] ┆ list[bool]          │
╞═══════════╪═════════════════════╡
│ [1]       ┆ [true]              │
│ [1, 2]    ┆ null                │
│ [1, 2, 3] ┆ [true, false, true] │
└───────────┴─────────────────────┘

Currently calling df.explode([“x”, “y”]) will result in this error:

polars.exceptions.ShapeError: exploded columns must have matching element counts

I’m assuming there’s not a built in way. But I can’t find/think of a way to convert that null into a list with the correct length so the explode will work (assuming I don’t statically know the required length beforehand).

I looked into passing list.lengths into repeat_by(), but repeat_by() doesn’t support null.