pandas.DataFrame.notnull — pandas 2.2.3 documentation (original) (raw)
DataFrame.notnull is an alias for DataFrame.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 '' or numpy.inf are not considered NA values (unless you set pandas.options.mode.use_inf_as_na = True). NA values, such as None or numpy.NaN, get mapped to False values.
Returns:
DataFrame
Mask of bool values for each element in DataFrame 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