polars.DataFrame.join#
- DataFrame.join(other: DataFrame, *, left_on: str | Expr | Sequence[str | Expr] | None = None, right_on: str | Expr | Sequence[str | Expr] | None = None, on: str | Expr | Sequence[str | Expr] | None = None, how: JoinStrategy = 'inner', suffix: str = '_right') Self [source]#
Join in SQL-like fashion.
- Parameters:
- other
DataFrame to join with.
- left_on
Name(s) of the left join column(s).
- right_on
Name(s) of the right join column(s).
- on
Name(s) of the join columns in both DataFrames.
- how{‘inner’, ‘left’, ‘outer’, ‘semi’, ‘anti’, ‘cross’}
Join strategy.
- suffix
Suffix to append to columns with a duplicate name.
- Returns:
- Joined DataFrame
See also
Notes
For joining on columns with categorical data, see
pl.StringCache()
.Examples
>>> df = pl.DataFrame( ... { ... "foo": [1, 2, 3], ... "bar": [6.0, 7.0, 8.0], ... "ham": ["a", "b", "c"], ... } ... ) >>> other_df = pl.DataFrame( ... { ... "apple": ["x", "y", "z"], ... "ham": ["a", "b", "d"], ... } ... ) >>> df.join(other_df, on="ham") shape: (2, 4) ┌─────┬─────┬─────┬───────┐ │ foo ┆ bar ┆ ham ┆ apple │ │ --- ┆ --- ┆ --- ┆ --- │ │ i64 ┆ f64 ┆ str ┆ str │ ╞═════╪═════╪═════╪═══════╡ │ 1 ┆ 6.0 ┆ a ┆ x │ │ 2 ┆ 7.0 ┆ b ┆ y │ └─────┴─────┴─────┴───────┘
>>> df.join(other_df, on="ham", how="outer") shape: (4, 4) ┌──────┬──────┬─────┬───────┐ │ foo ┆ bar ┆ ham ┆ apple │ │ --- ┆ --- ┆ --- ┆ --- │ │ i64 ┆ f64 ┆ str ┆ str │ ╞══════╪══════╪═════╪═══════╡ │ 1 ┆ 6.0 ┆ a ┆ x │ │ 2 ┆ 7.0 ┆ b ┆ y │ │ null ┆ null ┆ d ┆ z │ │ 3 ┆ 8.0 ┆ c ┆ null │ └──────┴──────┴─────┴───────┘
>>> df.join(other_df, on="ham", how="left") shape: (3, 4) ┌─────┬─────┬─────┬───────┐ │ foo ┆ bar ┆ ham ┆ apple │ │ --- ┆ --- ┆ --- ┆ --- │ │ i64 ┆ f64 ┆ str ┆ str │ ╞═════╪═════╪═════╪═══════╡ │ 1 ┆ 6.0 ┆ a ┆ x │ │ 2 ┆ 7.0 ┆ b ┆ y │ │ 3 ┆ 8.0 ┆ c ┆ null │ └─────┴─────┴─────┴───────┘
>>> df.join(other_df, on="ham", how="semi") shape: (2, 3) ┌─────┬─────┬─────┐ │ foo ┆ bar ┆ ham │ │ --- ┆ --- ┆ --- │ │ i64 ┆ f64 ┆ str │ ╞═════╪═════╪═════╡ │ 1 ┆ 6.0 ┆ a │ │ 2 ┆ 7.0 ┆ b │ └─────┴─────┴─────┘
>>> df.join(other_df, on="ham", how="anti") shape: (1, 3) ┌─────┬─────┬─────┐ │ foo ┆ bar ┆ ham │ │ --- ┆ --- ┆ --- │ │ i64 ┆ f64 ┆ str │ ╞═════╪═════╪═════╡ │ 3 ┆ 8.0 ┆ c │ └─────┴─────┴─────┘