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 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:

Series

Mask of bool values for each element in Series that indicates 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年05月27日'),
...  pd.Timestamp('1940年04月25日')],
...  name=['Alfred', 'Batman', ''],
...  toy=[None, 'Batmobile', 'Joker']))
>>> df
 age born name toy
0 5.0 NaT Alfred None
1 6.0 1939年05月27日 Batman Batmobile
2 NaN 1940年04月25日 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