pyspark.pandas.DataFrame.isna¶
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DataFrame.isna() → pyspark.pandas.frame.DataFrame¶ Detects missing values for items in the current Dataframe.
Return a boolean same-sized Dataframe indicating if the values are NA. NA values, such as None or numpy.NaN, gets mapped to True values. Everything else gets mapped to False values.
See also
Examples
>>> df = ps.DataFrame([(.2, .3), (.0, None), (.6, None), (.2, .1)]) >>> df.isnull() 0 1 0 False False 1 False True 2 False True 3 False False
>>> df = ps.DataFrame([[None, 'bee', None], ['dog', None, 'fly']]) >>> df.isnull() 0 1 2 0 True False True 1 False True False