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 (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:

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
Float64Index([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])

pandas.Index.min

pandas.Index.notnull