is_in for bool dtype

[Gabriel-ROBIN]

Problem description

I wish I could use polars to filter a Boolean column with the is_in function

Example:

import polars as pl

bool_value_to_filter_on = [True, None]

df = pl.DataFrame({'A' : [True, False, None]})
df.filter(pl.col('A').is_in(bool_value_to_filter_on))

Of course for this specific use case I could use df.filter(pl.col('A') | pl.col('A').is_null()), but in this case I can not work with a generic list of values.

[mkleinbort-ic]

A quick hack while a full solution is found:

df.filter(pl.col('A').cast(int).is_in(bool_value_to_filter_on))

# Or 
df.filter(pl.col('A').cast(pl.Int8()).is_in(bool_value_to_filter_on))