[Python] Shorter / better way to simulate dropWhile in polars

Say I have this:

>>> df = polars.DataFrame(dict(j=[1,1,1,2,1,2,1,2,2], k=[1,2,3,4,5,6,7,8,9]))
>>> df
shape: (9, 2)
┌─────┬─────┐
│ j ┆ k │
│ --- ┆ --- │
│ i64 ┆ i64 │
╞═════╪═════╡
│ 1 ┆ 1 │
│ 1 ┆ 2 │
│ 1 ┆ 3 │
│ 2 ┆ 4 │
│ 1 ┆ 5 │
│ 2 ┆ 6 │
│ 1 ┆ 7 │
│ 2 ┆ 8 │
│ 2 ┆ 9 │
└─────┴─────┘


Is there a shorter / better way to simulate dropWhile (i.e. remove all the rows at the top of the DataFrame that satisfy a certain condition) than this (which removes all initial rows that have j == 1):

>>> df.slice(df.with_row_index().filter(polars.col('j') != 1).select('index').head(1).item())
shape: (6, 2)
┌─────┬─────┐
│ j ┆ k │
│ --- ┆ --- │
│ i64 ┆ i64 │
╞═════╪═════╡
│ 2 ┆ 4 │
│ 1 ┆ 5 │
│ 2 ┆ 6 │
│ 1 ┆ 7 │
│ 2 ┆ 8 │
│ 2 ┆ 9 │
└─────┴─────┘

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