polars.Expr.drop_nans#
- Expr.drop_nans() Expr [source]#
Drop all floating point NaN values.
The original order of the remaining elements is preserved.
See also
Notes
A NaN value is not the same as a null value. To drop null values, use
drop_nulls()
.Examples
>>> df = pl.DataFrame({"a": [1.0, None, 3.0, float("nan")]}) >>> df.select(pl.col("a").drop_nans()) shape: (3, 1) ┌──────┐ │ a │ │ --- │ │ f64 │ ╞══════╡ │ 1.0 │ │ null │ │ 3.0 │ └──────┘