pyspark.pandas.Series.notna¶
-
Series.notna() → IndexOpsLike¶ Detect existing (non-missing) values. Return a boolean same-sized object indicating if the values are not NA. Non-missing values get mapped to True. Characters such as empty strings ‘’ or numpy.inf are not considered NA values (unless you set pandas.options.mode.use_inf_as_na = True). NA values, such as None or numpy.NaN, get mapped to False values.
- Returns
- Series or IndexMask of bool values for each element in Series
that indicates whether an element is not an NA value.
Examples
Show which entries in a Series are not NA.
>>> ser = ps.Series([5, 6, np.NaN]) >>> ser 0 5.0 1 6.0 2 NaN dtype: float64
>>> ser.notna() 0 True 1 True 2 False dtype: bool
>>> ser.rename("a").to_frame().set_index("a").index.notna() Index([True, True, False], dtype='bool', name='a')