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

drop_nulls

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  │
└──────┘