mars.dataframe.isnull#
- mars.dataframe.isnull(df)#
Detect missing values.
Return a boolean same-sized object 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. Characters such as empty strings
''
ornumpy.inf
are not considered NA values (unless you setpandas.options.mode.use_inf_as_na = True
).- Returns
Mask of bool values for each element in DataFrame that indicates whether an element is not an NA value.
- Return type
See also
DataFrame.isnull
Alias of isna.
DataFrame.notna
Boolean inverse of isna.
DataFrame.dropna
Omit axes labels with missing values.
isna
Top-level isna.
Examples
Show which entries in a DataFrame are NA.
>>> import numpy as np >>> import mars.dataframe as md >>> df = md.DataFrame({'age': [5, 6, np.NaN], ... 'born': [md.NaT, md.Timestamp('1939-05-27'), ... md.Timestamp('1940-04-25')], ... 'name': ['Alfred', 'Batman', ''], ... 'toy': [None, 'Batmobile', 'Joker']}) >>> df.execute() age born name toy 0 5.0 NaT Alfred None 1 6.0 1939-05-27 Batman Batmobile 2 NaN 1940-04-25 Joker
>>> df.isna().execute() age born name toy 0 False True False True 1 False False False False 2 True False False False
Show which entries in a Series are NA.
>>> ser = md.Series([5, 6, np.NaN]) >>> ser.execute() 0 5.0 1 6.0 2 NaN dtype: float64
>>> ser.isna().execute() 0 False 1 False 2 True dtype: bool