pyspark.pandas.DataFrame.isnull#

DataFrame.isnull()[source]#

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

DataFrame.notnull

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