mars.dataframe.notnull#
- mars.dataframe.notnull(df)#
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
''
ornumpy.inf
are not considered NA values (unless you setpandas.options.mode.use_inf_as_na = True
). NA values, such as None ornumpy.NaN
, get mapped to False values.- 返回
Mask of bool values for each element in DataFrame that indicates whether an element is not an NA value.
- 返回类型
参见
DataFrame.notnull
Alias of notna.
DataFrame.isna
Boolean inverse of notna.
DataFrame.dropna
Omit axes labels with missing values.
notna
Top-level notna.
实际案例
Show which entries in a DataFrame are not 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.notna().execute() age born name toy 0 True False True False 1 True True True True 2 False True True True
Show which entries in a Series are not NA.
>>> ser = md.Series([5, 6, np.NaN]) >>> ser.execute() 0 5.0 1 6.0 2 NaN dtype: float64
>>> ser.notna().execute() 0 True 1 True 2 False dtype: bool