add GH references

pandas-dev · jreback · Aug 23, 2018 · Aug 16, 2018 · Aug 16, 2018 · Aug 16, 2018
commit c493b237709c995c6e17cd7fd0bd6d102321f624
diff --git a/doc/source/whatsnew/v0.24.0.txt b/doc/source/whatsnew/v0.24.0.txt
@@ -576,10 +576,10 @@ Datetimelike
 - Bug in :class:`DataFrame` with mixed dtypes including ``datetime64[ns]`` incorrectly raising ``TypeError`` on equality comparisons (:issue:`13128`,:issue:`22163`)
 - Bug in :meth:`DataFrame.eq` comparison against ``NaT`` incorrectly returning ``True`` or ``NaN`` (:issue:`15697`,:issue:`22163`)
 - Bug in :class:`DataFrame` with ``timedelta64[ns]`` dtype division by ``Timedelta``-like scalar incorrectly returning ``timedelta64[ns]`` dtype instead of ``float64`` dtype (:issue:`20088`,:issue:`22163`)
-- Bug in adding a :class:`Index` with object dtype to a :class:`Series` with ``timedelta64[ns]`` dtype incorrectly raising (:issue:`?????`)
-- Bug in multiplying a :class:`Series` with numeric dtype against a ``timedelta`` object (:issue:`?????`)
-- Bug in :class:`Series` with numeric dtype when adding or subtracting an an array or ``Series`` with ``timedelta64`` dtype (:issue:`?????`)
-- Bug in :class:`Index` with numeric dtype when multiplying or dividing an array with dtype ``timedelta64`` (:issue:`????`)
+- Bug in adding a :class:`Index` with object dtype to a :class:`Series` with ``timedelta64[ns]`` dtype incorrectly raising (:issue:`22390`)
+- Bug in multiplying a :class:`Series` with numeric dtype against a ``timedelta`` object (:issue:`22390`)
+- 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`)
 
 Timedelta
 ^^^^^^^^^

diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
@@ -123,9 +123,9 @@ def index_arithmetic_method(self, other):
             # Defer to subclass implementation
             return NotImplemented
         elif isinstance(other, np.ndarray) and is_timedelta64_dtype(other):
-            # wrap in Series for op, this will in turn wrap in TimedeltaIndex,
-            # but will correctly raise TypeError instead of NullFrequencyError
-            # for add/sub ops
+            # GH#22390; wrap in Series for op, this will in turn wrap in
+            # TimedeltaIndex, but will correctly raise TypeError instead of
+            # NullFrequencyError for add/sub ops
             from pandas import Series
             other = Series(other)
             out = op(self, other)

diff --git a/pandas/core/indexes/range.py b/pandas/core/indexes/range.py
@@ -598,7 +598,7 @@ def _evaluate_numeric_binop(self, other):
                     # so we need to catch these explicitly
                     return op(self._int64index, other)
                 elif is_timedelta64_dtype(other):
-                    # Must be an np.ndarray
+                    # Must be an np.ndarray; GH#22390
                     return op(self._int64index, other)
 
                 other = self._validate_for_numeric_binop(other, op)

diff --git a/pandas/core/ops.py b/pandas/core/ops.py
@@ -1246,9 +1246,9 @@ def wrapper(left, right):
 
         elif is_timedelta64_dtype(right) and not is_scalar(right):
             # i.e. exclude np.timedelta64 object
-            # Unfortunately we need to special-case right-hand timedelta64
-            # dtypes because numpy casts integer dtypes to timedelta64 when
-            # operating with timedelta64
+            # GH#22390 Unfortunately we need to special-case right-hand
+            # timedelta64 dtypes because numpy casts integer dtypes to
+            # timedelta64 when operating with timedelta64
             if isinstance(right, np.ndarray):
                 # upcast to TimedeltaIndex before dispatching
                 right = pd.TimedeltaIndex(right)
@@ -1264,8 +1264,9 @@ def wrapper(left, right):
                                     dtype=result.dtype)
 
         elif type(right) is datetime.timedelta:
-            # cast up to Timedelta to rely on Timedelta implementation;
-            # otherwise operation against numeric-dtype raises TypeError
+            # GH#22390  cast up to Timedelta to rely on Timedelta
+            # implementation; otherwise operation against numeric-dtype
+            # raises TypeError
             right = pd.Timedelta(right)
             return op(left, right)
 

diff --git a/pandas/tests/arithmetic/test_numeric.py b/pandas/tests/arithmetic/test_numeric.py
@@ -59,6 +59,7 @@ class TestNumericArraylikeArithmeticWithTimedeltaLike(object):
                                       for cls in [pd.Series, pd.Index]],
         ids=lambda x: type(x).__name__ + str(x.dtype))
     def test_mul_td64arr(self, left, box_cls):
+        # GH#22390
         right = np.array([1, 2, 3], dtype='m8[s]')
         right = box_cls(right)
 
@@ -82,6 +83,7 @@ def test_mul_td64arr(self, left, box_cls):
                                       for cls in [pd.Series, pd.Index]],
         ids=lambda x: type(x).__name__ + str(x.dtype))
     def test_div_td64arr(self, left, box_cls):
+        # GH#22390
         right = np.array([10, 40, 90], dtype='m8[s]')
         right = box_cls(right)