cudf.Series.mask#
- Series.mask(cond, other=None, inplace: bool = False, axis=None, level=None) Self | None [source]#
Replace values where the condition is True.
- Parameters:
- condbool Series/DataFrame, array-like
Where cond is False, keep the original value. Where True, replace with corresponding value from other. Callables are not supported.
- other: scalar, list of scalars, Series/DataFrame
Entries where cond is True are replaced with corresponding value from other. Callables are not supported. Default is None.
DataFrame expects only Scalar or array like with scalars or dataframe with same dimension as self.
Series expects only scalar or series like with same length
- inplacebool, default False
Whether to perform the operation in place on the data.
- Returns:
- Same type as caller
Examples
>>> import cudf >>> df = cudf.DataFrame({"A":[1, 4, 5], "B":[3, 5, 8]}) >>> df.mask(df % 2 == 0, [-1, -1]) A B 0 1 3 1 -1 5 2 5 -1
>>> ser = cudf.Series([4, 3, 2, 1, 0]) >>> ser.mask(ser > 2, 10) 0 10 1 10 2 2 3 1 4 0 dtype: int64 >>> ser.mask(ser > 2) 0 <NA> 1 <NA> 2 2 3 1 4 0 dtype: int64