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BUG: fix raise of TypeError when subtracting timedelta array #22054

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Sep 18, 2018
Merged

BUG: fix raise of TypeError when subtracting timedelta array #22054

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.24.0.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -642,6 +642,7 @@ Timedelta
- Bug in :class:`Series` with numeric dtype when adding or subtracting an an array or ``Series`` with ``timedelta64`` dtype (:issue:`22390`)
- Bug in :class:`Index` with numeric dtype when multiplying or dividing an array with dtype ``timedelta64`` (:issue:`22390`)
- Bug in :class:`TimedeltaIndex` incorrectly allowing indexing with ``Timestamp`` object (:issue:`20464`)
- Fixed bug where subtracting :class:`Timedelta` from an object-dtyped array would raise ``TypeError`` (:issue:`21980`)
-
-

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8 changes: 5 additions & 3 deletions pandas/_libs/tslibs/timedeltas.pyx
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Expand Up @@ -541,10 +541,12 @@ def _binary_op_method_timedeltalike(op, name):

elif hasattr(other, 'dtype'):
# nd-array like
if other.dtype.kind not in ['m', 'M']:
# raise rathering than letting numpy return wrong answer
if other.dtype.kind in ['m', 'M']:
return op(self.to_timedelta64(), other)
elif other.dtype.kind == 'O':
return np.array([op(self, x) for x in other])
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@jbrockmendel I am a bit confused here why simply returning NotImplemented is not sufficient ?
(I tested it, and that doesn't seem to work. Although with a datetime.timedelta it does, and that one does return NotImplemented ..)

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The pd.Timedelta version fails because both arr.__add__(td) and td.__radd__(arr) return NotImplemented. arr.__add__(td.to_pytimedelta()) returns OK, so presumably it is something on the numpy implementation.

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Was playing a bit with it, and I think Timedelta behaves differently as datetime.timedelta because of the __array_priority__ we add to the _Timedelta class (by commenting it out, the simple example works), which is needed to get other behaviors working I suppose

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@jorisvandenbossche ok otherwise this PR looks ok, are you suggesting that we remove that?

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I'm also confused.

else:
return NotImplemented
return op(self.to_timedelta64(), other)

elif not _validate_ops_compat(other):
return NotImplemented
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65 changes: 65 additions & 0 deletions pandas/tests/scalar/timedelta/test_arithmetic.py
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Expand Up @@ -200,6 +200,57 @@ def test_td_rsub_numeric_raises(self):
with pytest.raises(TypeError):
2.0 - td

def test_td_sub_timedeltalike_object_dtype_array(self):
# GH 21980
arr = np.array([Timestamp('20130101 9:01'),
Timestamp('20121230 9:02')])
exp = np.array([Timestamp('20121231 9:01'),
Timestamp('20121229 9:02')])
res = arr - pd.Timedelta('1D')
tm.assert_numpy_array_equal(res, exp)

def test_td_sub_mixed_most_timedeltalike_object_dtype_array(self):
# GH 21980
now = pd.Timestamp.now()
arr = np.array([now,
pd.Timedelta('1D'),
np.timedelta64(2, 'h')])
exp = np.array([now - pd.Timedelta('1D'),
pd.Timedelta('0D'),
np.timedelta64(2, 'h') - pd.Timedelta('1D')])
res = arr - pd.Timedelta('1D')
tm.assert_numpy_array_equal(res, exp)

def test_td_rsub_mixed_most_timedeltalike_object_dtype_array(self):
# GH 21980
now = pd.Timestamp.now()
arr = np.array([now,
pd.Timedelta('1D'),
np.timedelta64(2, 'h')])
with pytest.raises(TypeError):
pd.Timedelta('1D') - arr

@pytest.mark.parametrize('op', [operator.add, ops.radd])
def test_td_add_timedeltalike_object_dtype_array(self, op):
# GH 21980
arr = np.array([Timestamp('20130101 9:01'),
Timestamp('20121230 9:02')])
exp = np.array([Timestamp('20130102 9:01'),
Timestamp('20121231 9:02')])
res = op(arr, pd.Timedelta('1D'))
tm.assert_numpy_array_equal(res, exp)

@pytest.mark.parametrize('op', [operator.add, ops.radd])
def test_td_add_mixed_timedeltalike_object_dtype_array(self, op):
# GH 21980
now = pd.Timestamp.now()
arr = np.array([now,
pd.Timedelta('1D')])
exp = np.array([now + pd.Timedelta('1D'),
pd.Timedelta('2D')])
res = op(arr, pd.Timedelta('1D'))
tm.assert_numpy_array_equal(res, exp)


class TestTimedeltaMultiplicationDivision(object):
"""
Expand Down Expand Up @@ -616,3 +667,17 @@ def test_rdivmod_invalid(self):

with pytest.raises(TypeError):
divmod(np.array([22, 24]), td)

@pytest.mark.parametrize('op', [
operator.mul,
ops.rmul,
operator.truediv,
ops.rdiv,
ops.rsub])
@pytest.mark.parametrize('arr', [
np.array([Timestamp('20130101 9:01'), Timestamp('20121230 9:02')]),
np.array([pd.Timestamp.now(), pd.Timedelta('1D')])
])
def test_td_op_timedelta_timedeltalike_array(self, op, arr):
with pytest.raises(TypeError):
op(arr, pd.Timedelta('1D'))