def notna(self) -> 'Series':
'''
Return a same-indexed, Boolean Series indicating which values are NaN or None.
'''
values = np.logical_not(_isna(self.values))
values.flags.writeable = False
return self.__class__(values, index=self._index)
def fillna(self, value) -> 'Series':
'''Return a new Series after replacing NaN or None values with the supplied value.
'''
sel = _isna(self.values)
if not np.any(sel):
return self
if isinstance(value, np.ndarray):
raise Exception('cannot assign an array to fillna')
else:
value_dtype = np.array(value).dtype
assigned_dtype = _resolve_dtype(value_dtype, self.values.dtype)
if self.values.dtype == assigned_dtype:
assigned = self.values.copy()
else:
assigned = self.values.astype(assigned_dtype)
assigned[sel] = value
assigned.flags.writeable = False
return self.__class__(assigned,
index=self._index,
name=self._name)
def isna(self) -> 'Series':
'''
Return a same-indexed, Boolean Series indicating which values are NaN or None.
'''
# consider returning self if not values.any()?
values = _isna(self.values)
values.flags.writeable = False
return self.__class__(values, index=self._index)
def dropna(self) -> 'Series':
'''
Return a new Series after removing values of NaN or None.
'''
sel = np.logical_not(_isna(self.values))
if not np.any(sel):
return self
values = self.values[sel]
values.flags.writeable = False
return self.__class__(values, index=self._index.loc[sel])
def test_isna_array_b(self):
a1 = np.array([[1, 2], [3, 4]])
a2 = np.array([[False, True, False], [False, True, False]])
a3 = np.array([['b', 'c', 'd'], ['b', 'c', 'd']])
a4 = np.array([[2.3, 3.2, np.nan], [2.3, 3.2, np.nan]])
a5 = np.array(
[['test', 'test again', np.nan], ['test', 'test again', np.nan]],
dtype=object)
a6 = np.array([[2.3, 5.4, np.nan], [2.3, 5.4, np.nan]],
dtype='float32')
self.assertEqual(_isna(a1).tolist(), [[False, False], [False, False]])
self.assertEqual(
_isna(a2).tolist(), [[False, False, False], [False, False, False]])
self.assertEqual(
_isna(a3).tolist(), [[False, False, False], [False, False, False]])
self.assertEqual(
_isna(a4).tolist(), [[False, False, True], [False, False, True]])
self.assertEqual(
_isna(a5).tolist(), [[False, False, True], [False, False, True]])
self.assertEqual(
_isna(a6).tolist(), [[False, False, True], [False, False, True]])
def dropna(self) -> 'Series':
'''
Return a new Series after removing values of NaN or None.
'''
# get positions that we want to keep
sel = np.logical_not(_isna(self.values))
if not np.any(sel):
return self.__class__(())
values = self.values[sel]
values.flags.writeable = False
return self.__class__(values,
index=self._index.loc[sel],
name=self._name)
def test_isna_array_a(self):
a1 = np.array([1, 2, 3])
a2 = np.array([False, True, False])
a3 = np.array(['b', 'c', 'd'])
a4 = np.array([2.3, 3.2])
a5 = np.array(['test', 'test again'], dtype='S')
a6 = np.array([2.3, 5.4], dtype='float32')
self.assertEqual(_isna(a1).tolist(), [False, False, False])
self.assertEqual(_isna(a2).tolist(), [False, False, False])
self.assertEqual(_isna(a3).tolist(), [False, False, False])
self.assertEqual(_isna(a4).tolist(), [False, False])
self.assertEqual(_isna(a5).tolist(), [False, False])
self.assertEqual(_isna(a6).tolist(), [False, False])
a1 = np.array([1, 2, 3, None])
a2 = np.array([False, True, False, None])
a3 = np.array(['b', 'c', 'd', None])
a4 = np.array([2.3, 3.2, None])
a5 = np.array(['test', 'test again', None])
a6 = np.array([2.3, 5.4, None])
self.assertEqual(_isna(a1).tolist(), [False, False, False, True])
self.assertEqual(_isna(a2).tolist(), [False, False, False, True])
self.assertEqual(_isna(a3).tolist(), [False, False, False, True])
self.assertEqual(_isna(a4).tolist(), [False, False, True])
self.assertEqual(_isna(a5).tolist(), [False, False, True])
self.assertEqual(_isna(a6).tolist(), [False, False, True])
a1 = np.array([1, 2, 3, np.nan])
a2 = np.array([False, True, False, np.nan])
a3 = np.array(['b', 'c', 'd', np.nan], dtype=object)
a4 = np.array([2.3, 3.2, np.nan], dtype=object)
a5 = np.array(['test', 'test again', np.nan], dtype=object)
a6 = np.array([2.3, 5.4, np.nan], dtype='float32')
self.assertEqual(_isna(a1).tolist(), [False, False, False, True])
self.assertEqual(_isna(a2).tolist(), [False, False, False, True])
self.assertEqual(_isna(a3).tolist(), [False, False, False, True])
self.assertEqual(_isna(a4).tolist(), [False, False, True])
self.assertEqual(_isna(a5).tolist(), [False, False, True])
self.assertEqual(_isna(a6).tolist(), [False, False, True])
