polars.Expr.all#

Expr.all(*, ignore_nulls: bool = True) → Expr[source]#

Return whether all values in the column are True.

Only works on columns of data type Boolean.

Note

This method is not to be confused with the function polars.all(), which can be used to select all columns.

Parameters:

ignore_nulls

If set to True (default), null values are ignored. If there are no non-null values, the output is True.
If set to False, Kleene logic is used to deal with nulls: if the column contains any null values and no False values, the output is null.

Returns:

Expr: Expression of data type Boolean.

Examples

>>> df = pl.DataFrame(
...     {
...         "a": [True, True],
...         "b": [False, True],
...         "c": [None, True],
...     }
... )
>>> df.select(pl.col("*").all())
shape: (1, 3)
┌──────┬───────┬──────┐
│ a    ┆ b     ┆ c    │
│ ---  ┆ ---   ┆ ---  │
│ bool ┆ bool  ┆ bool │
╞══════╪═══════╪══════╡
│ true ┆ false ┆ true │
└──────┴───────┴──────┘

Enable Kleene logic by setting ignore_nulls=False.

>>> df.select(pl.col("*").all(ignore_nulls=False))
shape: (1, 3)
┌──────┬───────┬──────┐
│ a    ┆ b     ┆ c    │
│ ---  ┆ ---   ┆ ---  │
│ bool ┆ bool  ┆ bool │
╞══════╪═══════╪══════╡
│ true ┆ false ┆ null │
└──────┴───────┴──────┘