pyspark.pandas.DataFrame.isna#

DataFrame.isna()#

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.

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