polars.concat¶
- polars.concat(items: Sequence[polars.internals.frame.DataFrame], rechunk: bool = True, how: str = 'vertical') polars.internals.frame.DataFrame¶
- polars.concat(items: Sequence[polars.internals.series.Series], rechunk: bool = True, how: str = 'vertical') polars.internals.series.Series
- polars.concat(items: Sequence[polars.internals.lazy_frame.LazyFrame], rechunk: bool = True, how: str = 'vertical') polars.internals.lazy_frame.LazyFrame
Aggregate all the Dataframes/Series in a List of DataFrames/Series to a single DataFrame/Series.
- Parameters
- items
DataFrames/Series/LazyFrames to concatenate.
- rechunk
rechunk the final DataFrame/Series.
- how
Only used if the items are DataFrames.
One of {“vertical”, “diagonal”, “horizontal”}.
Vertical: Applies multiple vstack operations.
Diagonal: Finds a union between the column schemas and fills missing column values with null.
Horizontal: Stacks Series horizontally and fills with nulls if the lengths don’t match.
Examples
>>> df1 = pl.DataFrame({"a": [1], "b": [3]}) >>> df2 = pl.DataFrame({"a": [2], "b": [4]}) >>> pl.concat([df1, df2]) shape: (2, 2) ┌─────┬─────┐ │ a ┆ b │ │ --- ┆ --- │ │ i64 ┆ i64 │ ╞═════╪═════╡ │ 1 ┆ 3 │ ├╌╌╌╌╌┼╌╌╌╌╌┤ │ 2 ┆ 4 │ └─────┴─────┘