pandas.Index.notna#

final Index.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:

numpy.ndarray[bool]: Boolean array to indicate which entries are not NA.

See also

Index.notnull: Alias of notna.
Index.isna: Inverse of notna.
notna: Top-level notna.

Examples

Show which entries in an Index are not NA. The result is an array.

>>> idx = pd.Index([5.2, 6.0, np.NaN])
>>> idx
Index([5.2, 6.0, nan], dtype='float64')
>>> idx.notna()
array([ True,  True, False])

Empty strings are not considered NA values. None is considered a NA value.

>>> idx = pd.Index(['black', '', 'red', None])
>>> idx
Index(['black', '', 'red', None], dtype='object')
>>> idx.notna()
array([ True,  True,  True, False])