polars.DataFrame.update#

DataFrame.update( other: DataFrame, on: str | Sequence[str] | None = None, how: Literal['left', 'inner'] = 'left', ) → DataFrame[source]#

Update the values in this DataFrame with the non-null values in other.

Parameters:

other: DataFrame that will be used to update the values
on: Column names that will be joined on. If none given the row count is used.
how{‘left’, ‘inner’}: ‘left’ will keep the left table rows as is. ‘inner’ will remove rows that are not found in other

Warning

This functionality is experimental and may change without it being considered a breaking change.

Notes

This is syntactic sugar for a left/inner join + coalesce

Examples

>>> df = pl.DataFrame(
...     {
...         "A": [1, 2, 3, 4],
...         "B": [400, 500, 600, 700],
...     }
... )
>>> df
shape: (4, 2)
┌─────┬─────┐
│ A   ┆ B   │
│ --- ┆ --- │
│ i64 ┆ i64 │
╞═════╪═════╡
│ 1   ┆ 400 │
│ 2   ┆ 500 │
│ 3   ┆ 600 │
│ 4   ┆ 700 │
└─────┴─────┘
>>> new_df = pl.DataFrame(
...     {
...         "B": [4, None, 6],
...         "C": [7, 8, 9],
...     }
... )
>>> new_df
shape: (3, 2)
┌──────┬─────┐
│ B    ┆ C   │
│ ---  ┆ --- │
│ i64  ┆ i64 │
╞══════╪═════╡
│ 4    ┆ 7   │
│ null ┆ 8   │
│ 6    ┆ 9   │
└──────┴─────┘
>>> df.update(new_df)
shape: (4, 2)
┌─────┬─────┐
│ A   ┆ B   │
│ --- ┆ --- │
│ i64 ┆ i64 │
╞═════╪═════╡
│ 1   ┆ 4   │
│ 2   ┆ 500 │
│ 3   ┆ 6   │
│ 4   ┆ 700 │
└─────┴─────┘