pandas.Series.notnull#
- Series.notnull()[source]#
Series.notnull is an alias for Series.notna.
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.- Returns
- Series
Mask of bool values for each element in Series that indicates whether an element is not an NA value.
See also
Series.notnull
Alias of notna.
Series.isna
Boolean inverse of notna.
Series.dropna
Omit axes labels with missing values.
notna
Top-level notna.
Examples
Show which entries in a DataFrame are not NA.
>>> df = pd.DataFrame(dict(age=[5, 6, np.NaN], ... born=[pd.NaT, pd.Timestamp('1939-05-27'), ... pd.Timestamp('1940-04-25')], ... name=['Alfred', 'Batman', ''], ... toy=[None, 'Batmobile', 'Joker'])) >>> df 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() 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 = pd.Series([5, 6, np.NaN]) >>> ser 0 5.0 1 6.0 2 NaN dtype: float64
>>> ser.notna() 0 True 1 True 2 False dtype: bool