polars.LazyFrame.drop_nulls#
- LazyFrame.drop_nulls(
- subset: ColumnNameOrSelector | Collection[ColumnNameOrSelector] | None = None,
Drop all rows that contain null values.
The original order of the remaining rows is preserved.
- Parameters:
- subset
Column name(s) for which null values are considered. If set to
None
(default), use all columns.
Examples
>>> lf = pl.LazyFrame( ... { ... "foo": [1, 2, 3], ... "bar": [6, None, 8], ... "ham": ["a", "b", None], ... } ... )
The default behavior of this method is to drop rows where any single value of the row is null.
>>> lf.drop_nulls().collect() shape: (1, 3) ┌─────┬─────┬─────┐ │ foo ┆ bar ┆ ham │ │ --- ┆ --- ┆ --- │ │ i64 ┆ i64 ┆ str │ ╞═════╪═════╪═════╡ │ 1 ┆ 6 ┆ a │ └─────┴─────┴─────┘
This behaviour can be constrained to consider only a subset of columns, as defined by name or with a selector. For example, dropping rows if there is a null in any of the integer columns:
>>> import polars.selectors as cs >>> lf.drop_nulls(subset=cs.integer()).collect() shape: (2, 3) ┌─────┬─────┬──────┐ │ foo ┆ bar ┆ ham │ │ --- ┆ --- ┆ --- │ │ i64 ┆ i64 ┆ str │ ╞═════╪═════╪══════╡ │ 1 ┆ 6 ┆ a │ │ 3 ┆ 8 ┆ null │ └─────┴─────┴──────┘
This method drops a row if any single value of the row is null.
Below are some example snippets that show how you could drop null values based on other conditions:
>>> lf = pl.LazyFrame( ... { ... "a": [None, None, None, None], ... "b": [1, 2, None, 1], ... "c": [1, None, None, 1], ... } ... ) >>> lf.collect() shape: (4, 3) ┌──────┬──────┬──────┐ │ a ┆ b ┆ c │ │ --- ┆ --- ┆ --- │ │ null ┆ i64 ┆ i64 │ ╞══════╪══════╪══════╡ │ null ┆ 1 ┆ 1 │ │ null ┆ 2 ┆ null │ │ null ┆ null ┆ null │ │ null ┆ 1 ┆ 1 │ └──────┴──────┴──────┘
Drop a row only if all values are null:
>>> lf.filter(~pl.all_horizontal(pl.all().is_null())).collect() shape: (3, 3) ┌──────┬─────┬──────┐ │ a ┆ b ┆ c │ │ --- ┆ --- ┆ --- │ │ null ┆ i64 ┆ i64 │ ╞══════╪═════╪══════╡ │ null ┆ 1 ┆ 1 │ │ null ┆ 2 ┆ null │ │ null ┆ 1 ┆ 1 │ └──────┴─────┴──────┘