pandas.Index.notnull¶
- Index.notnull()[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''
ornumpy.inf
are not considered NA values (unless you setpandas.options.mode.use_inf_as_na = True
). NA values, such as None ornumpy.NaN
, get mapped toFalse
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])