pandas.Series.notna — pandas 3.0.0.dev0+2102.g839747c3f6 documentation (original) (raw)

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 empty strings '' or numpy.inf are not considered NA values. NA values, such as None or numpy.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.

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