pyspark.pandas.Series.where#
- Series.where(cond, other=nan)[source]#
Replace values where the condition is False.
- Parameters
- condboolean Series
Where cond is True, keep the original value. Where False, replace with corresponding value from other.
- otherscalar, Series
Entries where cond is False 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.where(s1 > 0).sort_index() 0 NaN 1 1.0 2 2.0 3 3.0 4 4.0 dtype: float64
>>> s1.where(s1 > 1, 10).sort_index() 0 10 1 10 2 2 3 3 4 4 dtype: int64
>>> s1.where(s1 > 1, s1 + 100).sort_index() 0 100 1 101 2 2 3 3 4 4 dtype: int64
>>> s1.where(s1 > 1, s2).sort_index() 0 100 1 200 2 2 3 3 4 4 dtype: int64
>>> reset_option("compute.ops_on_diff_frames")