pyspark.pandas.Series.mask¶
-
Series.mask(cond: pyspark.pandas.series.Series, other: Any = nan) → pyspark.pandas.series.Series¶ Replace values where the condition is True.
- Parameters
- condboolean Series
Where cond is False, keep the original value. Where True, replace with corresponding value from other.
- otherscalar, Series
Entries where cond is True are replaced with corresponding value from other.
- Returns
- Series
Examples
>>> from pyspark.pandas.config import set_option, reset_option >>> set_option("compute.ops_on_diff_frames", True) >>> s1 = ps.Series([0, 1, 2, 3, 4]) >>> s2 = ps.Series([100, 200, 300, 400, 500]) >>> s1.mask(s1 > 0).sort_index() 0 0.0 1 NaN 2 NaN 3 NaN 4 NaN dtype: float64
>>> s1.mask(s1 > 1, 10).sort_index() 0 0 1 1 2 10 3 10 4 10 dtype: int64
>>> s1.mask(s1 > 1, s1 + 100).sort_index() 0 0 1 1 2 102 3 103 4 104 dtype: int64
>>> s1.mask(s1 > 1, s2).sort_index() 0 0 1 1 2 300 3 400 4 500 dtype: int64
>>> reset_option("compute.ops_on_diff_frames")