pandas.Series.isna — pandas 2.2.3 documentation (original) (raw)

Series.isna()[source]#

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 '' or numpy.inf are not considered NA values (unless you set pandas.options.mode.use_inf_as_na = True).

Returns:

Series

Mask of bool values for each element in Series that indicates whether an element is an NA value.

Examples

Show which entries in a DataFrame are 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.isna() 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 = pd.Series([5, 6, np.nan]) ser 0 5.0 1 6.0 2 NaN dtype: float64

ser.isna() 0 False 1 False 2 True dtype: bool