How to filter df by value list with Polars?

I have Polars df from a csv and I try to filter it by value list:

list = [1, 2, 4, 6, 48]

df = (
    pl.read_csv("bm.dat", separator=';', new_columns=["cid1", "cid2", "cid3"])
    .lazy()
    .filter((pl.col("cid1") in list) & (pl.col("cid2") in list))
    .collect()
)

I receive an error:

ValueError: Since Expr are lazy, the truthiness of an Expr is ambiguous. Hint: use '&' or '|' to chain Expr together, not and/or.

But when I comment #.lazy() and #.collect(), I receive this error again.

I tried only one filter .filter(pl.col("cid1") in list, and received the error again.

How to filter df by value list with Polars?

Your error relates to using the in operator. In Polars, you want to use the is_in Expression.

For example:

df = pl.DataFrame(
    {
        "cid1": [1, 2, 3],
        "cid2": [4, 5, 6],
        "cid3": [7, 8, 9],
    }
)


list = [1, 2, 4, 6, 48]
(
    df.lazy()
    .filter((pl.col("cid1").is_in(list)) & (pl.col("cid2").is_in(list)))
    .collect()
)

shape: (1, 3)
┌──────┬──────┬──────┐
│ cid1 ┆ cid2 ┆ cid3 │
│ ---  ┆ ---  ┆ ---  │
│ i64  ┆ i64  ┆ i64  │
╞══════╪══════╪══════╡
│ 1    ┆ 4    ┆ 7    │
└──────┴──────┴──────┘

But if we attempt to use the in operator instead, we get our error again.

(
    df.lazy()
    .filter((pl.col("cid1") in list) & (pl.col("cid2") in list))
    .collect()
)

Traceback (most recent call last):
  File "<stdin>", line 3, in <module>
  File "/home/corey/.virtualenvs/StackOverflow/lib/python3.10/site-packages/polars/internals/expr/expr.py", line 155, in __bool__
    raise ValueError(
ValueError: Since Expr are lazy, the truthiness of an Expr is ambiguous. Hint: use '&' or '|' to chain Expr together, not and/or.