pandas.Series.notna#

Series.notna()[source]#

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 emptystrings'' 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 Falsevalues.

Returns:

Series

Mask of bool values for each element in Series thatindicates 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        toy0  5.0        NaT  Alfred       None1  6.0 1939-05-27  Batman  Batmobile2  NaN 1940-04-25              Joker

>>>df.notna()     age   born  name    toy0   True  False  True  False1   True   True  True   True2  False   True  True   True

Show which entries in a Series are not NA.

>>>ser=pd.Series([5,6,np.nan])>>>ser0    5.01    6.02    NaNdtype: float64

>>>ser.notna()0     True1     True2    Falsedtype: bool