polars.DataFrame.extend

DataFrame.extend(other: DataFrame) → Self

Extend the memory backed by this DataFrame with the values from other.

Different from vstack which adds the chunks from other to the chunks of this DataFrame, extend appends the data from other to the underlying memory locations and thus may cause a reallocation.

If this does not cause a reallocation, the resulting data structure will not have any extra chunks and thus will yield faster queries.

Prefer extend over vstack when you want to do a query after a single append. For instance, during online operations where you add n rows and rerun a query.

Prefer vstack over extend when you want to append many times before doing a query. For instance, when you read in multiple files and want to store them in a single DataFrame. In the latter case, finish the sequence of vstack operations with a rechunk.

Parameters:

other

DataFrame to vertically add.

Warning

This method modifies the dataframe in-place. The dataframe is returned for convenience only.

See also

vstack

Examples

>>> df1 = pl.DataFrame({"foo": [1, 2, 3], "bar": [4, 5, 6]})
>>> df2 = pl.DataFrame({"foo": [10, 20, 30], "bar": [40, 50, 60]})
>>> df1.extend(df2)
shape: (6, 2)
┌─────┬─────┐
│ foo ┆ bar │
│ --- ┆ --- │
│ i64 ┆ i64 │
╞═════╪═════╡
│ 1   ┆ 4   │
│ 2   ┆ 5   │
│ 3   ┆ 6   │
│ 10  ┆ 40  │
│ 20  ┆ 50  │
│ 30  ┆ 60  │
└─────┴─────┘