polars.Expr.is_not_nan#
- Expr.is_not_nan() Expr [source]#
Returns a boolean Series indicating which values are not NaN.
Notes
Floating point
NaN
(Not A Number) should not be confused with missing data represented asNull/None
.Examples
>>> df = pl.DataFrame( ... { ... "a": [1, 2, None, 1, 5], ... "b": [1.0, 2.0, float("nan"), 1.0, 5.0], ... } ... ) >>> df.with_columns(pl.col(pl.Float64).is_not_nan().name.suffix("_is_not_nan")) shape: (5, 3) ┌──────┬─────┬──────────────┐ │ a ┆ b ┆ b_is_not_nan │ │ --- ┆ --- ┆ --- │ │ i64 ┆ f64 ┆ bool │ ╞══════╪═════╪══════════════╡ │ 1 ┆ 1.0 ┆ true │ │ 2 ┆ 2.0 ┆ true │ │ null ┆ NaN ┆ false │ │ 1 ┆ 1.0 ┆ true │ │ 5 ┆ 5.0 ┆ true │ └──────┴─────┴──────────────┘