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.

engine:In MemoryStreamingDistributed

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 │
└──────┴───────┴──────┘