polars.LazyFrame.join_where#

LazyFrame.join_where( other: LazyFrame, *predicates: Expr | Iterable[Expr], suffix: str = '_right', ) → LazyFrame[source]#

Perform a join based on one or multiple (in)equality predicates.

This performs an inner join, so only rows where all predicates are true are included in the result, and a row from either DataFrame may be included multiple times in the result.

Note

The row order of the input DataFrames is not preserved.

Warning

This functionality is experimental. It may be changed at any point without it being considered a breaking change.

Parameters:

other: DataFrame to join with.
*predicates: (In)Equality condition to join the two tables on. When a column name occurs in both tables, the proper suffix must be applied in the predicate.
suffix: Suffix to append to columns with a duplicate name.

Examples

>>> east = pl.LazyFrame(
...     {
...         "id": [100, 101, 102],
...         "dur": [120, 140, 160],
...         "rev": [12, 14, 16],
...         "cores": [2, 8, 4],
...     }
... )
>>> west = pl.LazyFrame(
...     {
...         "t_id": [404, 498, 676, 742],
...         "time": [90, 130, 150, 170],
...         "cost": [9, 13, 15, 16],
...         "cores": [4, 2, 1, 4],
...     }
... )
>>> east.join_where(
...     west,
...     pl.col("dur") < pl.col("time"),
...     pl.col("rev") < pl.col("cost"),
... ).collect()
shape: (5, 8)
┌─────┬─────┬─────┬───────┬──────┬──────┬──────┬─────────────┐
│ id  ┆ dur ┆ rev ┆ cores ┆ t_id ┆ time ┆ cost ┆ cores_right │
│ --- ┆ --- ┆ --- ┆ ---   ┆ ---  ┆ ---  ┆ ---  ┆ ---         │
│ i64 ┆ i64 ┆ i64 ┆ i64   ┆ i64  ┆ i64  ┆ i64  ┆ i64         │
╞═════╪═════╪═════╪═══════╪══════╪══════╪══════╪═════════════╡
│ 100 ┆ 120 ┆ 12  ┆ 2     ┆ 498  ┆ 130  ┆ 13   ┆ 2           │
│ 100 ┆ 120 ┆ 12  ┆ 2     ┆ 676  ┆ 150  ┆ 15   ┆ 1           │
│ 100 ┆ 120 ┆ 12  ┆ 2     ┆ 742  ┆ 170  ┆ 16   ┆ 4           │
│ 101 ┆ 140 ┆ 14  ┆ 8     ┆ 676  ┆ 150  ┆ 15   ┆ 1           │
│ 101 ┆ 140 ┆ 14  ┆ 8     ┆ 742  ┆ 170  ┆ 16   ┆ 4           │
└─────┴─────┴─────┴───────┴──────┴──────┴──────┴─────────────┘