[Python] Pandas isin function in polars

Once in a while I get to the point where I need to run the following line:

DF['is_flagged'] = DF['id'].isin(DF2[DF2['flag']==1]['id'])


Lately I started using polars, and I wonder how to convert it easily to polars.

For example:

df1 = pl.DataFrame({
'Animal_id': [1, 2, 3, 4, 5, 6, 7],
'age': [4, 6, 3, 8, 3, 8, 9] })

df2 = pl.DataFrame({
'Animal_id': [1, 2, 3, 4, 5, 6, 7],
'Animal_type': ['cat', 'dog', 'cat', 'cat', 'dog', 'dog', 'cat'] })


Expected output:

shape: (7, 3)
┌───────────┬─────┬────────┐
│ animal_id ┆ age ┆ is_dog │
│ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ i64 │
╞═══════════╪═════╪════════╡
│ 1 ┆ 4 ┆ 0 │
│ 2 ┆ 6 ┆ 1 │
│ 3 ┆ 3 ┆ 0 │
│ 4 ┆ 8 ┆ 0 │
│ 5 ┆ 3 ┆ 1 │
│ 6 ┆ 8 ┆ 1 │
│ 7 ┆ 9 ┆ 0 │
└───────────┴─────┴────────┘


Without using flag and then join

I tried to use the is_in() function but this didn’t worked.

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