polars.Series.nan_max#
- Series.nan_max() int | float | date | datetime | timedelta | str [source]#
Get maximum value, but propagate/poison encountered NaN values.
This differs from numpy’s
nanmax
as numpy defaults to propagating NaN values, whereas polars defaults to ignoring them.Examples
>>> s = pl.Series("a", [1, 3, 4]) >>> s.nan_max() 4
>>> s = pl.Series("a", [1.0, float("nan"), 4.0]) >>> s.nan_max() nan