pandas.Series.isnull — pandas 0.24.0rc1 documentation (original) (raw)
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 not an NA value. |
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Examples
Show which entries in a DataFrame are NA.
df = pd.DataFrame({'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