polars.LazyFrame.filter

LazyFrame.filter(

*predicates: IntoExprColumn | Iterable[IntoExprColumn] | bool | list[bool] | np.ndarray[Any, Any],

**constraints: Any,

) → Self

Filter the rows in the LazyFrame based on a predicate expression.

The original order of the remaining rows is preserved.

Parameters:

predicates

Expression that evaluates to a boolean Series.

constraints

Column filters. Use name=value to filter column name by the supplied value.

Examples

>>> lf = pl.LazyFrame(
...     {
...         "foo": [1, 2, 3],
...         "bar": [6, 7, 8],
...         "ham": ["a", "b", "c"],
...     }
... )

Filter on one condition:

>>> lf.filter(pl.col("foo") > 1).collect()
shape: (2, 3)
┌─────┬─────┬─────┐
│ foo ┆ bar ┆ ham │
│ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ str │
╞═════╪═════╪═════╡
│ 2   ┆ 7   ┆ b   │
│ 3   ┆ 8   ┆ c   │
└─────┴─────┴─────┘

Filter on multiple conditions:

>>> lf.filter((pl.col("foo") < 3) & (pl.col("ham") == "a")).collect()
shape: (1, 3)
┌─────┬─────┬─────┐
│ foo ┆ bar ┆ ham │
│ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ str │
╞═════╪═════╪═════╡
│ 1   ┆ 6   ┆ a   │
└─────┴─────┴─────┘

Provide multiple filters using *args syntax:

>>> lf.filter(
...     pl.col("foo") == 1,
...     pl.col("ham") == "a",
... ).collect()
shape: (1, 3)
┌─────┬─────┬─────┐
│ foo ┆ bar ┆ ham │
│ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ str │
╞═════╪═════╪═════╡
│ 1   ┆ 6   ┆ a   │
└─────┴─────┴─────┘

Provide multiple filters using **kwargs syntax:

>>> lf.filter(foo=1, ham="a").collect()
shape: (1, 3)
┌─────┬─────┬─────┐
│ foo ┆ bar ┆ ham │
│ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ str │
╞═════╪═════╪═════╡
│ 1   ┆ 6   ┆ a   │
└─────┴─────┴─────┘

Filter on an OR condition:

>>> lf.filter((pl.col("foo") == 1) | (pl.col("ham") == "c")).collect()
shape: (2, 3)
┌─────┬─────┬─────┐
│ foo ┆ bar ┆ ham │
│ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ str │
╞═════╪═════╪═════╡
│ 1   ┆ 6   ┆ a   │
│ 3   ┆ 8   ┆ c   │
└─────┴─────┴─────┘