Column-level Boolean summaries
Summarize flag columns in a DataFrame by checking whether each column has any true entry.
Polars · Function
pl.any
Reduces a Boolean column to whether it contains at least one True value. Nulls are ignored by default, or handled with Kleene logic when ignore_nulls=False.
How it works
Use this expression method on Boolean columns to reduce each column to one Boolean result. By default, nulls do not affect the result; setting ignore_nulls=False applies Kleene logic, which can produce null when no true value exists but a null is present.
Syntax
Expr.any(*, ignore_nulls: bool = True) → ExprParameters
| Name | Type | Description |
|---|---|---|
ignore_nulls | bool | Controls whether null values are ignored. Defaults to True; False enables Kleene logic. |
Returns
An Expr with Boolean data type.
Key points
- The method performs a column-wise existence check for true values.
- The default setting makes null entries irrelevant to the aggregation.
- Passing False changes null handling to three-valued Kleene logic.
- The resulting expression has Boolean data type.
- Use the keyword argument to explicitly request null-aware logical behavior.
Common mistakes
- The expression is restricted to Boolean columns; applying it to another data type is unsupported.
- With the default null-ignoring behavior, an entirely null column reduces to False.
- When ignore_nulls=False, a null result is possible if the column has nulls but no true values.
Example: Check whether columns contain any true values
import polars as pl
df = pl.DataFrame({
"a": [True, False],
"b": [False, False],
"c": [None, False],
})
result = df.select(pl.col("*").any())
print(result)Aggregates each Boolean column into one value indicating whether it contains any true value.
When to use it
Null-aware aggregation
Preserve uncertainty when missing Boolean values matter to downstream logic.
Expression-based feature checks
Use inside select or other expression contexts to create Boolean aggregate outputs.
Interview questions
QWhat does Expr.any return?
Expr.any reduces a Boolean column to an expression that reports whether at least one value is True. It returns an Expr whose data type is Boolean.
Follow-up: How does it behave with nulls? With ignore_nulls=True, nulls are skipped; with ignore_nulls=False, Kleene logic can return null.
QWhat is the default null behavior?
ignore_nulls defaults to True, so null values are ignored during aggregation. If no non-null values remain, the result is False.
Follow-up: What result does an all-null column produce by default? False, because nulls are ignored and no true value is found.
QWhen should ignore_nulls be set to False?
Set ignore_nulls=False to enable Kleene logic. In that mode, a column containing null and no True produces null rather than False.
Follow-up: What result does [True, null] produce with Kleene logic? True, because the presence of a true value determines the logical OR result.
Related
polars.Expr.and_polars.any_horizontalpolars.col