polars.from_arrow¶
- polars.from_arrow(a: Union[pyarrow.lib.Table, pyarrow.lib.Array, pyarrow.lib.ChunkedArray], rechunk: bool = True) Union[polars.internals.frame.DataFrame, polars.internals.series.Series]¶
Create a DataFrame or Series from an Arrow Table or Array.
This operation will be zero copy for the most part. Types that are not supported by Polars may be cast to the closest supported type.
- Parameters
- aArrow Table or Array
Data represented as Arrow Table or Array.
- rechunkbool, default True
Make sure that all data is contiguous.
- Returns
- DataFrame or Series
Examples
Constructing a DataFrame from an Arrow Table:
>>> import pyarrow as pa >>> data = pa.table({"a": [1, 2, 3], "b": [4, 5, 6]}) >>> df = pl.from_arrow(data) >>> df shape: (3, 2) ┌─────┬─────┐ │ a ┆ b │ │ --- ┆ --- │ │ i64 ┆ i64 │ ╞═════╪═════╡ │ 1 ┆ 4 │ ├╌╌╌╌╌┼╌╌╌╌╌┤ │ 2 ┆ 5 │ ├╌╌╌╌╌┼╌╌╌╌╌┤ │ 3 ┆ 6 │ └─────┴─────┘
Constructing a Series from an Arrow Array:
>>> import pyarrow as pa >>> data = pa.array([1, 2, 3]) >>> series = pl.from_arrow(data) >>> series shape: (3,) Series: '' [i64] [ 1 2 3 ]