From 7ce722c83afd984312f744ee78e7a6a069e6dcbd Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Wed, 12 Sep 2018 04:28:47 -0700
Subject: [PATCH] TST: Collect/Use arithmetic test fixtures (#22645)

---
 pandas/tests/arithmetic/conftest.py         | 100 +++++++++-
 pandas/tests/arithmetic/test_datetime64.py  | 156 ++++++----------
 pandas/tests/arithmetic/test_numeric.py     | 103 ++++++-----
 pandas/tests/arithmetic/test_period.py      |  93 ++--------
 pandas/tests/arithmetic/test_timedelta64.py | 192 ++++++--------------
 5 files changed, 279 insertions(+), 365 deletions(-)

diff --git a/pandas/tests/arithmetic/conftest.py b/pandas/tests/arithmetic/conftest.py
index 844472b8bcf0d..b800b66e8edea 100644
--- a/pandas/tests/arithmetic/conftest.py
+++ b/pandas/tests/arithmetic/conftest.py
@@ -28,14 +28,32 @@ def zero(request):
     return request.param
 
 
+# ------------------------------------------------------------------
+# Vector Fixtures
+
 @pytest.fixture(params=[pd.Float64Index(np.arange(5, dtype='float64')),
                         pd.Int64Index(np.arange(5, dtype='int64')),
-                        pd.UInt64Index(np.arange(5, dtype='uint64'))],
+                        pd.UInt64Index(np.arange(5, dtype='uint64')),
+                        pd.RangeIndex(5)],
                 ids=lambda x: type(x).__name__)
-def idx(request):
+def numeric_idx(request):
+    """
+    Several types of numeric-dtypes Index objects
+    """
     return request.param
 
 
+@pytest.fixture
+def tdser():
+    """
+    Return a Series with dtype='timedelta64[ns]', including a NaT.
+    """
+    return pd.Series(['59 Days', '59 Days', 'NaT'], dtype='timedelta64[ns]')
+
+
+# ------------------------------------------------------------------
+# Scalar Fixtures
+
 @pytest.fixture(params=[pd.Timedelta('5m4s').to_pytimedelta(),
                         pd.Timedelta('5m4s'),
                         pd.Timedelta('5m4s').to_timedelta64()],
@@ -47,6 +65,72 @@ def scalar_td(request):
     return request.param
 
 
+@pytest.fixture(params=[pd.offsets.Day(3),
+                        pd.offsets.Hour(72),
+                        pd.Timedelta(days=3).to_pytimedelta(),
+                        pd.Timedelta('72:00:00'),
+                        np.timedelta64(3, 'D'),
+                        np.timedelta64(72, 'h')])
+def three_days(request):
+    """
+    Several timedelta-like and DateOffset objects that each represent
+    a 3-day timedelta
+    """
+    return request.param
+
+
+@pytest.fixture(params=[pd.offsets.Hour(2),
+                        pd.offsets.Minute(120),
+                        pd.Timedelta(hours=2).to_pytimedelta(),
+                        pd.Timedelta(seconds=2 * 3600),
+                        np.timedelta64(2, 'h'),
+                        np.timedelta64(120, 'm')])
+def two_hours(request):
+    """
+    Several timedelta-like and DateOffset objects that each represent
+    a 2-hour timedelta
+    """
+    return request.param
+
+
+_common_mismatch = [pd.offsets.YearBegin(2),
+                    pd.offsets.MonthBegin(1),
+                    pd.offsets.Minute()]
+
+
+@pytest.fixture(params=[pd.Timedelta(minutes=30).to_pytimedelta(),
+                        np.timedelta64(30, 's'),
+                        pd.Timedelta(seconds=30)] + _common_mismatch)
+def not_hourly(request):
+    """
+    Several timedelta-like and DateOffset instances that are _not_
+    compatible with Hourly frequencies.
+    """
+    return request.param
+
+
+@pytest.fixture(params=[np.timedelta64(4, 'h'),
+                        pd.Timedelta(hours=23).to_pytimedelta(),
+                        pd.Timedelta('23:00:00')] + _common_mismatch)
+def not_daily(request):
+    """
+    Several timedelta-like and DateOffset instances that are _not_
+    compatible with Daily frequencies.
+    """
+    return request.param
+
+
+@pytest.fixture(params=[np.timedelta64(365, 'D'),
+                        pd.Timedelta(days=365).to_pytimedelta(),
+                        pd.Timedelta(days=365)] + _common_mismatch)
+def mismatched_freq(request):
+    """
+    Several timedelta-like and DateOffset instances that are _not_
+    compatible with Monthly or Annual frequencies.
+    """
+    return request.param
+
+
 # ------------------------------------------------------------------
 
 @pytest.fixture(params=[pd.Index, pd.Series, pd.DataFrame],
@@ -59,6 +143,18 @@ def box(request):
     return request.param
 
 
+@pytest.fixture(params=[pd.Index,
+                        pd.Series,
+                        pytest.param(pd.DataFrame,
+                                     marks=pytest.mark.xfail(strict=True))],
+                ids=lambda x: x.__name__)
+def box_df_fail(request):
+    """
+    Fixture equivalent to `box` fixture but xfailing the DataFrame case.
+    """
+    return request.param
+
+
 @pytest.fixture(params=[
     pd.Index,
     pd.Series,
diff --git a/pandas/tests/arithmetic/test_datetime64.py b/pandas/tests/arithmetic/test_datetime64.py
index d597ea834f097..a3fa4e6b88256 100644
--- a/pandas/tests/arithmetic/test_datetime64.py
+++ b/pandas/tests/arithmetic/test_datetime64.py
@@ -27,29 +27,6 @@
     DatetimeIndex, TimedeltaIndex)
 
 
-# ------------------------------------------------------------------
-# Fixtures
-
-@pytest.fixture(params=[pd.offsets.Hour(2), timedelta(hours=2),
-                        np.timedelta64(2, 'h'), Timedelta(hours=2)],
-                ids=str)
-def delta(request):
-    # Several ways of representing two hours
-    return request.param
-
-
-@pytest.fixture(
-    params=[
-        datetime(2011, 1, 1),
-        DatetimeIndex(['2011-01-01', '2011-01-02']),
-        DatetimeIndex(['2011-01-01', '2011-01-02']).tz_localize('US/Eastern'),
-        np.datetime64('2011-01-01'),
-        Timestamp('2011-01-01')],
-    ids=lambda x: type(x).__name__)
-def addend(request):
-    return request.param
-
-
 # ------------------------------------------------------------------
 # Comparisons
 
@@ -697,23 +674,20 @@ def test_dt64ser_sub_datetime_dtype(self):
     # TODO: This next block of tests came from tests.series.test_operators,
     # needs to be de-duplicated and parametrized over `box` classes
 
-    @pytest.mark.parametrize(
-        'box, assert_func',
-        [(Series, tm.assert_series_equal),
-         (pd.Index, tm.assert_index_equal)])
-    def test_sub_datetime64_not_ns(self, box, assert_func):
+    @pytest.mark.parametrize('klass', [Series, pd.Index])
+    def test_sub_datetime64_not_ns(self, klass):
         # GH#7996
         dt64 = np.datetime64('2013-01-01')
         assert dt64.dtype == 'datetime64[D]'
 
-        obj = box(date_range('20130101', periods=3))
+        obj = klass(date_range('20130101', periods=3))
         res = obj - dt64
-        expected = box([Timedelta(days=0), Timedelta(days=1),
-                        Timedelta(days=2)])
-        assert_func(res, expected)
+        expected = klass([Timedelta(days=0), Timedelta(days=1),
+                          Timedelta(days=2)])
+        tm.assert_equal(res, expected)
 
         res = dt64 - obj
-        assert_func(res, -expected)
+        tm.assert_equal(res, -expected)
 
     def test_sub_single_tz(self):
         # GH12290
@@ -1113,40 +1087,40 @@ def test_dti_add_intarray_no_freq(self, box):
     # -------------------------------------------------------------
     # Binary operations DatetimeIndex and timedelta-like
 
-    def test_dti_add_timedeltalike(self, tz_naive_fixture, delta, box):
+    def test_dti_add_timedeltalike(self, tz_naive_fixture, two_hours, box):
         # GH#22005, GH#22163 check DataFrame doesn't raise TypeError
         tz = tz_naive_fixture
         rng = pd.date_range('2000-01-01', '2000-02-01', tz=tz)
         rng = tm.box_expected(rng, box)
 
-        result = rng + delta
+        result = rng + two_hours
         expected = pd.date_range('2000-01-01 02:00',
                                  '2000-02-01 02:00', tz=tz)
         expected = tm.box_expected(expected, box)
         tm.assert_equal(result, expected)
 
-    def test_dti_iadd_timedeltalike(self, tz_naive_fixture, delta):
+    def test_dti_iadd_timedeltalike(self, tz_naive_fixture, two_hours):
         tz = tz_naive_fixture
         rng = pd.date_range('2000-01-01', '2000-02-01', tz=tz)
         expected = pd.date_range('2000-01-01 02:00',
                                  '2000-02-01 02:00', tz=tz)
-        rng += delta
+        rng += two_hours
         tm.assert_index_equal(rng, expected)
 
-    def test_dti_sub_timedeltalike(self, tz_naive_fixture, delta):
+    def test_dti_sub_timedeltalike(self, tz_naive_fixture, two_hours):
         tz = tz_naive_fixture
         rng = pd.date_range('2000-01-01', '2000-02-01', tz=tz)
         expected = pd.date_range('1999-12-31 22:00',
                                  '2000-01-31 22:00', tz=tz)
-        result = rng - delta
+        result = rng - two_hours
         tm.assert_index_equal(result, expected)
 
-    def test_dti_isub_timedeltalike(self, tz_naive_fixture, delta):
+    def test_dti_isub_timedeltalike(self, tz_naive_fixture, two_hours):
         tz = tz_naive_fixture
         rng = pd.date_range('2000-01-01', '2000-02-01', tz=tz)
         expected = pd.date_range('1999-12-31 22:00',
                                  '2000-01-31 22:00', tz=tz)
-        rng -= delta
+        rng -= two_hours
         tm.assert_index_equal(rng, expected)
 
     # -------------------------------------------------------------
@@ -1252,27 +1226,23 @@ def test_dti_isub_tdi(self, tz_naive_fixture):
     # TODO: A couple other tests belong in this section.  Move them in
     # A PR where there isn't already a giant diff.
 
-    def test_add_datetimelike_and_dti(self, addend):
+    @pytest.mark.parametrize('addend', [
+        datetime(2011, 1, 1),
+        DatetimeIndex(['2011-01-01', '2011-01-02']),
+        DatetimeIndex(['2011-01-01', '2011-01-02']).tz_localize('US/Eastern'),
+        np.datetime64('2011-01-01'),
+        Timestamp('2011-01-01')
+    ], ids=lambda x: type(x).__name__)
+    @pytest.mark.parametrize('tz', [None, 'US/Eastern'])
+    def test_add_datetimelike_and_dti(self, addend, tz):
         # GH#9631
-        dti = DatetimeIndex(['2011-01-01', '2011-01-02'])
-        msg = 'cannot add DatetimeIndex and {0}'.format(
-            type(addend).__name__)
+        dti = DatetimeIndex(['2011-01-01', '2011-01-02']).tz_localize(tz)
+        msg = 'cannot add DatetimeIndex and {0}'.format(type(addend).__name__)
         with tm.assert_raises_regex(TypeError, msg):
             dti + addend
         with tm.assert_raises_regex(TypeError, msg):
             addend + dti
 
-    def test_add_datetimelike_and_dti_tz(self, addend):
-        # GH#9631
-        dti_tz = DatetimeIndex(['2011-01-01',
-                                '2011-01-02']).tz_localize('US/Eastern')
-        msg = 'cannot add DatetimeIndex and {0}'.format(
-            type(addend).__name__)
-        with tm.assert_raises_regex(TypeError, msg):
-            dti_tz + addend
-        with tm.assert_raises_regex(TypeError, msg):
-            addend + dti_tz
-
     # -------------------------------------------------------------
     # __add__/__sub__ with ndarray[datetime64] and ndarray[timedelta64]
 
@@ -1391,21 +1361,14 @@ def test_sub_period(self, freq, box):
         with pytest.raises(TypeError):
             p - idx
 
-    @pytest.mark.parametrize('box', [
-        pd.Index,
-        pd.Series,
-        pytest.param(pd.DataFrame,
-                     marks=pytest.mark.xfail(reason="Tries to broadcast "
-                                                    "incorrectly",
-                                             strict=True,
-                                             raises=ValueError))
-    ], ids=lambda x: x.__name__)
     @pytest.mark.parametrize('op', [operator.add, ops.radd,
                                     operator.sub, ops.rsub])
     @pytest.mark.parametrize('pi_freq', ['D', 'W', 'Q', 'H'])
     @pytest.mark.parametrize('dti_freq', [None, 'D'])
-    def test_dti_sub_pi(self, dti_freq, pi_freq, op, box):
+    def test_dti_sub_pi(self, dti_freq, pi_freq, op, box_df_broadcast_failure):
         # GH#20049 subtracting PeriodIndex should raise TypeError
+        box = box_df_broadcast_failure
+
         dti = pd.DatetimeIndex(['2011-01-01', '2011-01-02'], freq=dti_freq)
         pi = dti.to_period(pi_freq)
 
@@ -1748,31 +1711,30 @@ def test_dti_add_offset_tzaware(self, tz_aware_fixture, box):
         tm.assert_equal(offset, expected)
 
 
-@pytest.mark.parametrize('klass,assert_func', [
-    (Series, tm.assert_series_equal),
-    (DatetimeIndex, tm.assert_index_equal)])
-def test_dt64_with_offset_array(klass, assert_func):
+@pytest.mark.parametrize('klass', [Series, DatetimeIndex])
+def test_dt64_with_offset_array(klass):
     # GH#10699
     # array of offsets
     box = Series if klass is Series else pd.Index
+    dti = DatetimeIndex([Timestamp('2000-1-1'), Timestamp('2000-2-1')])
+
+    s = klass(dti)
+
     with tm.assert_produces_warning(PerformanceWarning):
-        s = klass([Timestamp('2000-1-1'), Timestamp('2000-2-1')])
         result = s + box([pd.offsets.DateOffset(years=1),
                           pd.offsets.MonthEnd()])
         exp = klass([Timestamp('2001-1-1'), Timestamp('2000-2-29')])
-        assert_func(result, exp)
+        tm.assert_equal(result, exp)
 
         # same offset
         result = s + box([pd.offsets.DateOffset(years=1),
                           pd.offsets.DateOffset(years=1)])
         exp = klass([Timestamp('2001-1-1'), Timestamp('2001-2-1')])
-        assert_func(result, exp)
+        tm.assert_equal(result, exp)
 
 
-@pytest.mark.parametrize('klass,assert_func', [
-    (Series, tm.assert_series_equal),
-    (DatetimeIndex, tm.assert_index_equal)])
-def test_dt64_with_DateOffsets_relativedelta(klass, assert_func):
+@pytest.mark.parametrize('klass', [Series, DatetimeIndex])
+def test_dt64_with_DateOffsets_relativedelta(klass):
     # GH#10699
     vec = klass([Timestamp('2000-01-05 00:15:00'),
                  Timestamp('2000-01-31 00:23:00'),
@@ -1789,11 +1751,11 @@ def test_dt64_with_DateOffsets_relativedelta(klass, assert_func):
                        ('microseconds', 5)]
     for i, kwd in enumerate(relative_kwargs):
         op = pd.DateOffset(**dict([kwd]))
-        assert_func(klass([x + op for x in vec]), vec + op)
-        assert_func(klass([x - op for x in vec]), vec - op)
+        tm.assert_equal(klass([x + op for x in vec]), vec + op)
+        tm.assert_equal(klass([x - op for x in vec]), vec - op)
         op = pd.DateOffset(**dict(relative_kwargs[:i + 1]))
-        assert_func(klass([x + op for x in vec]), vec + op)
-        assert_func(klass([x - op for x in vec]), vec - op)
+        tm.assert_equal(klass([x + op for x in vec]), vec + op)
+        tm.assert_equal(klass([x - op for x in vec]), vec - op)
 
 
 @pytest.mark.parametrize('cls_and_kwargs', [
@@ -1816,10 +1778,8 @@ def test_dt64_with_DateOffsets_relativedelta(klass, assert_func):
     'Easter', ('DateOffset', {'day': 4}),
     ('DateOffset', {'month': 5})])
 @pytest.mark.parametrize('normalize', [True, False])
-@pytest.mark.parametrize('klass,assert_func', [
-    (Series, tm.assert_series_equal),
-    (DatetimeIndex, tm.assert_index_equal)])
-def test_dt64_with_DateOffsets(klass, assert_func, normalize, cls_and_kwargs):
+@pytest.mark.parametrize('klass', [Series, DatetimeIndex])
+def test_dt64_with_DateOffsets(klass, normalize, cls_and_kwargs):
     # GH#10699
     # assert these are equal on a piecewise basis
     vec = klass([Timestamp('2000-01-05 00:15:00'),
@@ -1849,26 +1809,24 @@ def test_dt64_with_DateOffsets(klass, assert_func, normalize, cls_and_kwargs):
                 continue
 
             offset = offset_cls(n, normalize=normalize, **kwargs)
-            assert_func(klass([x + offset for x in vec]), vec + offset)
-            assert_func(klass([x - offset for x in vec]), vec - offset)
-            assert_func(klass([offset + x for x in vec]), offset + vec)
+            tm.assert_equal(klass([x + offset for x in vec]), vec + offset)
+            tm.assert_equal(klass([x - offset for x in vec]), vec - offset)
+            tm.assert_equal(klass([offset + x for x in vec]), offset + vec)
 
 
-@pytest.mark.parametrize('klass,assert_func', zip([Series, DatetimeIndex],
-                                                  [tm.assert_series_equal,
-                                                   tm.assert_index_equal]))
-def test_datetime64_with_DateOffset(klass, assert_func):
+@pytest.mark.parametrize('klass', [Series, DatetimeIndex])
+def test_datetime64_with_DateOffset(klass):
     # GH#10699
     s = klass(date_range('2000-01-01', '2000-01-31'), name='a')
     result = s + pd.DateOffset(years=1)
     result2 = pd.DateOffset(years=1) + s
     exp = klass(date_range('2001-01-01', '2001-01-31'), name='a')
-    assert_func(result, exp)
-    assert_func(result2, exp)
+    tm.assert_equal(result, exp)
+    tm.assert_equal(result2, exp)
 
     result = s - pd.DateOffset(years=1)
     exp = klass(date_range('1999-01-01', '1999-01-31'), name='a')
-    assert_func(result, exp)
+    tm.assert_equal(result, exp)
 
     s = klass([Timestamp('2000-01-15 00:15:00', tz='US/Central'),
                pd.Timestamp('2000-02-15', tz='US/Central')], name='a')
@@ -1876,8 +1834,8 @@ def test_datetime64_with_DateOffset(klass, assert_func):
     result2 = pd.offsets.Day() + s
     exp = klass([Timestamp('2000-01-16 00:15:00', tz='US/Central'),
                  Timestamp('2000-02-16', tz='US/Central')], name='a')
-    assert_func(result, exp)
-    assert_func(result2, exp)
+    tm.assert_equal(result, exp)
+    tm.assert_equal(result2, exp)
 
     s = klass([Timestamp('2000-01-15 00:15:00', tz='US/Central'),
                pd.Timestamp('2000-02-15', tz='US/Central')], name='a')
@@ -1885,8 +1843,8 @@ def test_datetime64_with_DateOffset(klass, assert_func):
     result2 = pd.offsets.MonthEnd() + s
     exp = klass([Timestamp('2000-01-31 00:15:00', tz='US/Central'),
                  Timestamp('2000-02-29', tz='US/Central')], name='a')
-    assert_func(result, exp)
-    assert_func(result2, exp)
+    tm.assert_equal(result, exp)
+    tm.assert_equal(result2, exp)
 
 
 @pytest.mark.parametrize('years', [-1, 0, 1])
diff --git a/pandas/tests/arithmetic/test_numeric.py b/pandas/tests/arithmetic/test_numeric.py
index d3957330f11e4..fcfc3994a88c8 100644
--- a/pandas/tests/arithmetic/test_numeric.py
+++ b/pandas/tests/arithmetic/test_numeric.py
@@ -17,15 +17,6 @@
 from pandas import Timedelta, Series, Index, TimedeltaIndex
 
 
-@pytest.fixture(params=[pd.Float64Index(np.arange(5, dtype='float64')),
-                        pd.UInt64Index(np.arange(5, dtype='uint64')),
-                        pd.Int64Index(np.arange(5, dtype='int64')),
-                        pd.RangeIndex(5)],
-                ids=lambda x: type(x).__name__)
-def idx(request):
-    return request.param
-
-
 # ------------------------------------------------------------------
 # Comparisons
 
@@ -135,20 +126,18 @@ def test_ops_series(self):
         tm.assert_series_equal(expected, td * other)
         tm.assert_series_equal(expected, other * td)
 
-    @pytest.mark.parametrize('index', [
-        pd.Int64Index(range(1, 11)),
-        pd.UInt64Index(range(1, 11)),
-        pd.Float64Index(range(1, 11)),
-        pd.RangeIndex(1, 11)],
-        ids=lambda x: type(x).__name__)
+    # TODO: also test non-nanosecond timedelta64 and Tick objects;
+    #  see test_numeric_arr_rdiv_tdscalar for note on these failing
     @pytest.mark.parametrize('scalar_td', [
         Timedelta(days=1),
         Timedelta(days=1).to_timedelta64(),
         Timedelta(days=1).to_pytimedelta()],
         ids=lambda x: type(x).__name__)
-    def test_numeric_arr_mul_tdscalar(self, scalar_td, index, box):
+    def test_numeric_arr_mul_tdscalar(self, scalar_td, numeric_idx, box):
         # GH#19333
-        expected = pd.timedelta_range('1 days', '10 days')
+        index = numeric_idx
+
+        expected = pd.timedelta_range('0 days', '4 days')
 
         index = tm.box_expected(index, box)
         expected = tm.box_expected(expected, box)
@@ -159,28 +148,27 @@ def test_numeric_arr_mul_tdscalar(self, scalar_td, index, box):
         commute = scalar_td * index
         tm.assert_equal(commute, expected)
 
-    @pytest.mark.parametrize('index', [
-        pd.Int64Index(range(1, 3)),
-        pd.UInt64Index(range(1, 3)),
-        pd.Float64Index(range(1, 3)),
-        pd.RangeIndex(1, 3)],
-        ids=lambda x: type(x).__name__)
-    @pytest.mark.parametrize('scalar_td', [
-        Timedelta(days=1),
-        Timedelta(days=1).to_timedelta64(),
-        Timedelta(days=1).to_pytimedelta()],
-        ids=lambda x: type(x).__name__)
-    def test_numeric_arr_rdiv_tdscalar(self, scalar_td, index, box):
-        expected = TimedeltaIndex(['1 Day', '12 Hours'])
+    def test_numeric_arr_rdiv_tdscalar(self, three_days, numeric_idx, box):
+        index = numeric_idx[1:3]
+
+        broken = (isinstance(three_days, np.timedelta64) and
+                  three_days.dtype != 'm8[ns]')
+        broken = broken or isinstance(three_days, pd.offsets.Tick)
+        if box is not pd.Index and broken:
+            # np.timedelta64(3, 'D') / 2 == np.timedelta64(1, 'D')
+            raise pytest.xfail("timedelta64 not converted to nanos; "
+                               "Tick division not imlpemented")
+
+        expected = TimedeltaIndex(['3 Days', '36 Hours'])
 
         index = tm.box_expected(index, box)
         expected = tm.box_expected(expected, box)
 
-        result = scalar_td / index
+        result = three_days / index
         tm.assert_equal(result, expected)
 
         with pytest.raises(TypeError):
-            index / scalar_td
+            index / three_days
 
 
 # ------------------------------------------------------------------
@@ -188,7 +176,9 @@ def test_numeric_arr_rdiv_tdscalar(self, scalar_td, index, box):
 
 class TestDivisionByZero(object):
 
-    def test_div_zero(self, zero, idx):
+    def test_div_zero(self, zero, numeric_idx):
+        idx = numeric_idx
+
         expected = pd.Index([np.nan, np.inf, np.inf, np.inf, np.inf],
                             dtype=np.float64)
         result = idx / zero
@@ -196,7 +186,9 @@ def test_div_zero(self, zero, idx):
         ser_compat = Series(idx).astype('i8') / np.array(zero).astype('i8')
         tm.assert_series_equal(ser_compat, Series(result))
 
-    def test_floordiv_zero(self, zero, idx):
+    def test_floordiv_zero(self, zero, numeric_idx):
+        idx = numeric_idx
+
         expected = pd.Index([np.nan, np.inf, np.inf, np.inf, np.inf],
                             dtype=np.float64)
 
@@ -205,7 +197,9 @@ def test_floordiv_zero(self, zero, idx):
         ser_compat = Series(idx).astype('i8') // np.array(zero).astype('i8')
         tm.assert_series_equal(ser_compat, Series(result))
 
-    def test_mod_zero(self, zero, idx):
+    def test_mod_zero(self, zero, numeric_idx):
+        idx = numeric_idx
+
         expected = pd.Index([np.nan, np.nan, np.nan, np.nan, np.nan],
                             dtype=np.float64)
         result = idx % zero
@@ -213,7 +207,8 @@ def test_mod_zero(self, zero, idx):
         ser_compat = Series(idx).astype('i8') % np.array(zero).astype('i8')
         tm.assert_series_equal(ser_compat, Series(result))
 
-    def test_divmod_zero(self, zero, idx):
+    def test_divmod_zero(self, zero, numeric_idx):
+        idx = numeric_idx
 
         exleft = pd.Index([np.nan, np.inf, np.inf, np.inf, np.inf],
                           dtype=np.float64)
@@ -430,8 +425,9 @@ def test_div_equiv_binop(self):
         result = second / first
         tm.assert_series_equal(result, expected)
 
-    def test_div_int(self, idx):
+    def test_div_int(self, numeric_idx):
         # truediv under PY3
+        idx = numeric_idx
         result = idx / 1
         expected = idx
         if PY3:
@@ -445,13 +441,15 @@ def test_div_int(self, idx):
         tm.assert_index_equal(result, expected)
 
     @pytest.mark.parametrize('op', [operator.mul, ops.rmul, operator.floordiv])
-    def test_mul_int_identity(self, op, idx, box):
+    def test_mul_int_identity(self, op, numeric_idx, box):
+        idx = numeric_idx
         idx = tm.box_expected(idx, box)
 
         result = op(idx, 1)
         tm.assert_equal(result, idx)
 
-    def test_mul_int_array(self, idx):
+    def test_mul_int_array(self, numeric_idx):
+        idx = numeric_idx
         didx = idx * idx
 
         result = idx * np.array(5, dtype='int64')
@@ -461,39 +459,45 @@ def test_mul_int_array(self, idx):
         result = idx * np.arange(5, dtype=arr_dtype)
         tm.assert_index_equal(result, didx)
 
-    def test_mul_int_series(self, idx):
+    def test_mul_int_series(self, numeric_idx):
+        idx = numeric_idx
         didx = idx * idx
 
         arr_dtype = 'uint64' if isinstance(idx, pd.UInt64Index) else 'int64'
         result = idx * Series(np.arange(5, dtype=arr_dtype))
         tm.assert_series_equal(result, Series(didx))
 
-    def test_mul_float_series(self, idx):
+    def test_mul_float_series(self, numeric_idx):
+        idx = numeric_idx
         rng5 = np.arange(5, dtype='float64')
 
         result = idx * Series(rng5 + 0.1)
         expected = Series(rng5 * (rng5 + 0.1))
         tm.assert_series_equal(result, expected)
 
-    def test_mul_index(self, idx):
+    def test_mul_index(self, numeric_idx):
         # in general not true for RangeIndex
+        idx = numeric_idx
         if not isinstance(idx, pd.RangeIndex):
             result = idx * idx
             tm.assert_index_equal(result, idx ** 2)
 
-    def test_mul_datelike_raises(self, idx):
+    def test_mul_datelike_raises(self, numeric_idx):
+        idx = numeric_idx
         with pytest.raises(TypeError):
             idx * pd.date_range('20130101', periods=5)
 
-    def test_mul_size_mismatch_raises(self, idx):
+    def test_mul_size_mismatch_raises(self, numeric_idx):
+        idx = numeric_idx
         with pytest.raises(ValueError):
             idx * idx[0:3]
         with pytest.raises(ValueError):
             idx * np.array([1, 2])
 
     @pytest.mark.parametrize('op', [operator.pow, ops.rpow])
-    def test_pow_float(self, op, idx, box):
+    def test_pow_float(self, op, numeric_idx, box):
         # test power calculations both ways, GH#14973
+        idx = numeric_idx
         expected = pd.Float64Index(op(idx.values, 2.0))
 
         idx = tm.box_expected(idx, box)
@@ -502,8 +506,9 @@ def test_pow_float(self, op, idx, box):
         result = op(idx, 2.0)
         tm.assert_equal(result, expected)
 
-    def test_modulo(self, idx, box):
+    def test_modulo(self, numeric_idx, box):
         # GH#9244
+        idx = numeric_idx
         expected = Index(idx.values % 2)
 
         idx = tm.box_expected(idx, box)
@@ -512,7 +517,8 @@ def test_modulo(self, idx, box):
         result = idx % 2
         tm.assert_equal(result, expected)
 
-    def test_divmod(self, idx):
+    def test_divmod(self, numeric_idx):
+        idx = numeric_idx
         result = divmod(idx, 2)
         with np.errstate(all='ignore'):
             div, mod = divmod(idx.values, 2)
@@ -530,7 +536,8 @@ def test_divmod(self, idx):
 
     @pytest.mark.xfail(reason='GH#19252 Series has no __rdivmod__',
                        strict=True)
-    def test_divmod_series(self, idx):
+    def test_divmod_series(self, numeric_idx):
+        idx = numeric_idx
         other = np.ones(idx.values.shape, dtype=idx.values.dtype) * 2
         result = divmod(idx, Series(other))
         with np.errstate(all='ignore'):
diff --git a/pandas/tests/arithmetic/test_period.py b/pandas/tests/arithmetic/test_period.py
index 92123bf48bb47..3210290b9c5c8 100644
--- a/pandas/tests/arithmetic/test_period.py
+++ b/pandas/tests/arithmetic/test_period.py
@@ -3,7 +3,6 @@
 # behave identically.
 # Specifically for Period dtype
 import operator
-from datetime import timedelta
 
 import numpy as np
 import pytest
@@ -17,80 +16,10 @@
 import pandas.core.indexes.period as period
 from pandas.core import ops
 from pandas import (
-    Period, PeriodIndex, period_range, Timedelta, Series,
+    Period, PeriodIndex, period_range, Series,
     _np_version_under1p10)
 
 
-# ------------------------------------------------------------------
-# Fixtures
-
-_common_mismatch = [pd.offsets.YearBegin(2),
-                    pd.offsets.MonthBegin(1),
-                    pd.offsets.Minute()]
-
-
-@pytest.fixture(params=[timedelta(minutes=30),
-                        np.timedelta64(30, 's'),
-                        Timedelta(seconds=30)] + _common_mismatch)
-def not_hourly(request):
-    """
-    Several timedelta-like and DateOffset instances that are _not_
-    compatible with Hourly frequencies.
-    """
-    return request.param
-
-
-@pytest.fixture(params=[np.timedelta64(4, 'h'),
-                        timedelta(hours=23),
-                        Timedelta('23:00:00')] + _common_mismatch)
-def not_daily(request):
-    """
-    Several timedelta-like and DateOffset instances that are _not_
-    compatible with Daily frequencies.
-    """
-    return request.param
-
-
-@pytest.fixture(params=[np.timedelta64(365, 'D'),
-                        timedelta(365),
-                        Timedelta(days=365)] + _common_mismatch)
-def mismatched(request):
-    """
-    Several timedelta-like and DateOffset instances that are _not_
-    compatible with Monthly or Annual frequencies.
-    """
-    return request.param
-
-
-@pytest.fixture(params=[pd.offsets.Day(3),
-                        timedelta(days=3),
-                        np.timedelta64(3, 'D'),
-                        pd.offsets.Hour(72),
-                        timedelta(minutes=60 * 24 * 3),
-                        np.timedelta64(72, 'h'),
-                        Timedelta('72:00:00')])
-def three_days(request):
-    """
-    Several timedelta-like and DateOffset objects that each represent
-    a 3-day timedelta
-    """
-    return request.param
-
-
-@pytest.fixture(params=[pd.offsets.Hour(2),
-                        timedelta(hours=2),
-                        np.timedelta64(2, 'h'),
-                        pd.offsets.Minute(120),
-                        timedelta(minutes=120),
-                        np.timedelta64(120, 'm')])
-def two_hours(request):
-    """
-    Several timedelta-like and DateOffset objects that each represent
-    a 2-hour timedelta
-    """
-    return request.param
-
-
 # ------------------------------------------------------------------
 # Comparisons
 
@@ -752,8 +681,9 @@ def test_add_iadd_timedeltalike_annual(self):
         rng += pd.offsets.YearEnd(5)
         tm.assert_index_equal(rng, expected)
 
-    def test_pi_add_iadd_timedeltalike_freq_mismatch_annual(self, mismatched):
-        other = mismatched
+    def test_pi_add_iadd_timedeltalike_freq_mismatch_annual(self,
+                                                            mismatched_freq):
+        other = mismatched_freq
         rng = pd.period_range('2014', '2024', freq='A')
         msg = ('Input has different freq(=.+)? '
                'from PeriodIndex\\(freq=A-DEC\\)')
@@ -762,8 +692,9 @@ def test_pi_add_iadd_timedeltalike_freq_mismatch_annual(self, mismatched):
         with tm.assert_raises_regex(period.IncompatibleFrequency, msg):
             rng += other
 
-    def test_pi_sub_isub_timedeltalike_freq_mismatch_annual(self, mismatched):
-        other = mismatched
+    def test_pi_sub_isub_timedeltalike_freq_mismatch_annual(self,
+                                                            mismatched_freq):
+        other = mismatched_freq
         rng = pd.period_range('2014', '2024', freq='A')
         msg = ('Input has different freq(=.+)? '
                'from PeriodIndex\\(freq=A-DEC\\)')
@@ -782,8 +713,9 @@ def test_pi_add_iadd_timedeltalike_M(self):
         rng += pd.offsets.MonthEnd(5)
         tm.assert_index_equal(rng, expected)
 
-    def test_pi_add_iadd_timedeltalike_freq_mismatch_monthly(self, mismatched):
-        other = mismatched
+    def test_pi_add_iadd_timedeltalike_freq_mismatch_monthly(self,
+                                                             mismatched_freq):
+        other = mismatched_freq
         rng = pd.period_range('2014-01', '2016-12', freq='M')
         msg = 'Input has different freq(=.+)? from PeriodIndex\\(freq=M\\)'
         with tm.assert_raises_regex(period.IncompatibleFrequency, msg):
@@ -791,8 +723,9 @@ def test_pi_add_iadd_timedeltalike_freq_mismatch_monthly(self, mismatched):
         with tm.assert_raises_regex(period.IncompatibleFrequency, msg):
             rng += other
 
-    def test_pi_sub_isub_timedeltalike_freq_mismatch_monthly(self, mismatched):
-        other = mismatched
+    def test_pi_sub_isub_timedeltalike_freq_mismatch_monthly(self,
+                                                             mismatched_freq):
+        other = mismatched_freq
         rng = pd.period_range('2014-01', '2016-12', freq='M')
         msg = 'Input has different freq(=.+)? from PeriodIndex\\(freq=M\\)'
         with tm.assert_raises_regex(period.IncompatibleFrequency, msg):
diff --git a/pandas/tests/arithmetic/test_timedelta64.py b/pandas/tests/arithmetic/test_timedelta64.py
index def7a8be95fc8..5050922173564 100644
--- a/pandas/tests/arithmetic/test_timedelta64.py
+++ b/pandas/tests/arithmetic/test_timedelta64.py
@@ -18,60 +18,6 @@
     DataFrame)
 
 
-# ------------------------------------------------------------------
-# Fixtures
-
-@pytest.fixture
-def tdser():
-    """
-    Return a Series with dtype='timedelta64[ns]', including a NaT.
-    """
-    return Series(['59 Days', '59 Days', 'NaT'], dtype='timedelta64[ns]')
-
-
-@pytest.fixture(params=[pd.offsets.Hour(2), timedelta(hours=2),
-                        np.timedelta64(2, 'h'), Timedelta(hours=2)],
-                ids=lambda x: type(x).__name__)
-def delta(request):
-    """
-    Several ways of representing two hours
-    """
-    return request.param
-
-
-@pytest.fixture(params=[timedelta(minutes=5, seconds=4),
-                        Timedelta('5m4s'),
-                        Timedelta('5m4s').to_timedelta64()],
-                ids=lambda x: type(x).__name__)
-def scalar_td(request):
-    """
-    Several variants of Timedelta scalars representing 5 minutes and 4 seconds
-    """
-    return request.param
-
-
-@pytest.fixture(params=[pd.Index, Series, pd.DataFrame],
-                ids=lambda x: x.__name__)
-def box(request):
-    """
-    Several array-like containers that should have effectively identical
-    behavior with respect to arithmetic operations.
-    """
-    return request.param
-
-
-@pytest.fixture(params=[pd.Index,
-                        Series,
-                        pytest.param(pd.DataFrame,
-                                     marks=pytest.mark.xfail(strict=True))],
-                ids=lambda x: x.__name__)
-def box_df_fail(request):
-    """
-    Fixture equivalent to `box` fixture but xfailing the DataFrame case.
-    """
-    return request.param
-
-
 # ------------------------------------------------------------------
 # Timedelta64[ns] dtype Comparisons
 
@@ -522,8 +468,8 @@ def test_td64arr_add_sub_timestamp(self, box):
         with pytest.raises(TypeError):
             tdser - ts
 
-    def test_tdi_sub_dt64_array(self, box_df_fail):
-        box = box_df_fail  # DataFrame tries to broadcast incorrectly
+    def test_tdi_sub_dt64_array(self, box_df_broadcast_failure):
+        box = box_df_broadcast_failure
 
         dti = pd.date_range('2016-01-01', periods=3)
         tdi = dti - dti.shift(1)
@@ -540,8 +486,8 @@ def test_tdi_sub_dt64_array(self, box_df_fail):
         result = dtarr - tdi
         tm.assert_equal(result, expected)
 
-    def test_tdi_add_dt64_array(self, box_df_fail):
-        box = box_df_fail  # DataFrame tries to broadcast incorrectly
+    def test_tdi_add_dt64_array(self, box_df_broadcast_failure):
+        box = box_df_broadcast_failure
 
         dti = pd.date_range('2016-01-01', periods=3)
         tdi = dti - dti.shift(1)
@@ -559,43 +505,33 @@ def test_tdi_add_dt64_array(self, box_df_fail):
     # ------------------------------------------------------------------
     # Operations with int-like others
 
-    @pytest.mark.parametrize('box', [
-        pd.Index,
-        Series,
-        pytest.param(pd.DataFrame,
-                     marks=pytest.mark.xfail(reason="Attempts to broadcast "
-                                                    "incorrectly",
-                                             strict=True, raises=ValueError))
-    ], ids=lambda x: x.__name__)
-    def test_td64arr_add_int_series_invalid(self, box, tdser):
+    def test_td64arr_add_int_series_invalid(self, box_df_broadcast_failure,
+                                            tdser):
+        box = box_df_broadcast_failure
         tdser = tm.box_expected(tdser, box)
         err = TypeError if box is not pd.Index else NullFrequencyError
         with pytest.raises(err):
             tdser + Series([2, 3, 4])
 
-    def test_td64arr_radd_int_series_invalid(self, box_df_fail, tdser):
-        box = box_df_fail  # Tries to broadcast incorrectly
+    def test_td64arr_radd_int_series_invalid(self, box_df_broadcast_failure,
+                                             tdser):
+        box = box_df_broadcast_failure
         tdser = tm.box_expected(tdser, box)
         err = TypeError if box is not pd.Index else NullFrequencyError
         with pytest.raises(err):
             Series([2, 3, 4]) + tdser
 
-    @pytest.mark.parametrize('box', [
-        pd.Index,
-        Series,
-        pytest.param(pd.DataFrame,
-                     marks=pytest.mark.xfail(reason="Attempts to broadcast "
-                                                    "incorrectly",
-                                             strict=True, raises=ValueError))
-    ], ids=lambda x: x.__name__)
-    def test_td64arr_sub_int_series_invalid(self, box, tdser):
+    def test_td64arr_sub_int_series_invalid(self, box_df_broadcast_failure,
+                                            tdser):
+        box = box_df_broadcast_failure
         tdser = tm.box_expected(tdser, box)
         err = TypeError if box is not pd.Index else NullFrequencyError
         with pytest.raises(err):
             tdser - Series([2, 3, 4])
 
-    def test_td64arr_rsub_int_series_invalid(self, box_df_fail, tdser):
-        box = box_df_fail  # Tries to broadcast incorrectly
+    def test_td64arr_rsub_int_series_invalid(self, box_df_broadcast_failure,
+                                             tdser):
+        box = box_df_broadcast_failure
         tdser = tm.box_expected(tdser, box)
         err = TypeError if box is not pd.Index else NullFrequencyError
         with pytest.raises(err):
@@ -669,9 +605,9 @@ def test_td64arr_add_sub_numeric_scalar_invalid(self, box, scalar, tdser):
         Series([1, 2, 3])
         # TODO: Add DataFrame in here?
     ], ids=lambda x: type(x).__name__)
-    def test_td64arr_add_sub_numeric_arr_invalid(self, box_df_fail, vec,
-                                                 dtype, tdser):
-        box = box_df_fail  # tries to broadcast incorrectly
+    def test_td64arr_add_sub_numeric_arr_invalid(
+            self, box_df_broadcast_failure, vec, dtype, tdser):
+        box = box_df_broadcast_failure
         tdser = tm.box_expected(tdser, box)
         err = TypeError
         if box is pd.Index and not dtype.startswith('float'):
@@ -744,8 +680,8 @@ def test_timedelta64_operations_with_timedeltas(self):
         # roundtrip
         tm.assert_series_equal(result + td2, td1)
 
-    def test_td64arr_add_td64_array(self, box_df_fail):
-        box = box_df_fail  # DataFrame tries to broadcast incorrectly
+    def test_td64arr_add_td64_array(self, box_df_broadcast_failure):
+        box = box_df_broadcast_failure
 
         dti = pd.date_range('2016-01-01', periods=3)
         tdi = dti - dti.shift(1)
@@ -760,8 +696,8 @@ def test_td64arr_add_td64_array(self, box_df_fail):
         result = tdarr + tdi
         tm.assert_equal(result, expected)
 
-    def test_td64arr_sub_td64_array(self, box_df_fail):
-        box = box_df_fail  # DataFrame tries to broadcast incorrectly
+    def test_td64arr_sub_td64_array(self, box_df_broadcast_failure):
+        box = box_df_broadcast_failure
 
         dti = pd.date_range('2016-01-01', periods=3)
         tdi = dti - dti.shift(1)
@@ -843,7 +779,7 @@ def test_td64arr_sub_NaT(self, box):
         res = ser - pd.NaT
         tm.assert_equal(res, expected)
 
-    def test_td64arr_add_timedeltalike(self, delta, box):
+    def test_td64arr_add_timedeltalike(self, two_hours, box):
         # only test adding/sub offsets as + is now numeric
         rng = timedelta_range('1 days', '10 days')
         expected = timedelta_range('1 days 02:00:00', '10 days 02:00:00',
@@ -851,10 +787,10 @@ def test_td64arr_add_timedeltalike(self, delta, box):
         rng = tm.box_expected(rng, box)
         expected = tm.box_expected(expected, box)
 
-        result = rng + delta
+        result = rng + two_hours
         tm.assert_equal(result, expected)
 
-    def test_td64arr_sub_timedeltalike(self, delta, box):
+    def test_td64arr_sub_timedeltalike(self, two_hours, box):
         # only test adding/sub offsets as - is now numeric
         rng = timedelta_range('1 days', '10 days')
         expected = timedelta_range('0 days 22:00:00', '9 days 22:00:00')
@@ -862,7 +798,7 @@ def test_td64arr_sub_timedeltalike(self, delta, box):
         rng = tm.box_expected(rng, box)
         expected = tm.box_expected(expected, box)
 
-        result = rng - delta
+        result = rng - two_hours
         tm.assert_equal(result, expected)
 
     # ------------------------------------------------------------------
@@ -934,9 +870,9 @@ def test_td64arr_add_offset_index(self, names, box):
 
     # TODO: combine with test_td64arr_add_offset_index by parametrizing
     # over second box?
-    def test_td64arr_add_offset_array(self, box_df_fail):
+    def test_td64arr_add_offset_array(self, box_df_broadcast_failure):
         # GH#18849
-        box = box_df_fail  # tries to broadcast incorrectly
+        box = box_df_broadcast_failure
         tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
         other = np.array([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)])
 
@@ -957,9 +893,9 @@ def test_td64arr_add_offset_array(self, box_df_fail):
     @pytest.mark.parametrize('names', [(None, None, None),
                                        ('foo', 'bar', None),
                                        ('foo', 'foo', 'foo')])
-    def test_td64arr_sub_offset_index(self, names, box_df_fail):
+    def test_td64arr_sub_offset_index(self, names, box_df_broadcast_failure):
         # GH#18824, GH#19744
-        box = box_df_fail  # tries to broadcast incorrectly
+        box = box_df_broadcast_failure
         tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'],
                              name=names[0])
         other = pd.Index([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)],
@@ -975,9 +911,9 @@ def test_td64arr_sub_offset_index(self, names, box_df_fail):
             res = tdi - other
         tm.assert_equal(res, expected)
 
-    def test_td64arr_sub_offset_array(self, box_df_fail):
+    def test_td64arr_sub_offset_array(self, box_df_broadcast_failure):
         # GH#18824
-        box = box_df_fail  # tries to broadcast incorrectly
+        box = box_df_broadcast_failure
         tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
         other = np.array([pd.offsets.Hour(n=1), pd.offsets.Minute(n=-2)])
 
@@ -994,9 +930,9 @@ def test_td64arr_sub_offset_array(self, box_df_fail):
     @pytest.mark.parametrize('names', [(None, None, None),
                                        ('foo', 'bar', None),
                                        ('foo', 'foo', 'foo')])
-    def test_td64arr_with_offset_series(self, names, box_df_fail):
+    def test_td64arr_with_offset_series(self, names, box_df_broadcast_failure):
         # GH#18849
-        box = box_df_fail  # tries to broadcast incorrectly
+        box = box_df_broadcast_failure
         box2 = Series if box is pd.Index else box
 
         tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'],
@@ -1027,9 +963,10 @@ def test_td64arr_with_offset_series(self, names, box_df_fail):
         tm.assert_equal(res3, expected_sub)
 
     @pytest.mark.parametrize('obox', [np.array, pd.Index, pd.Series])
-    def test_td64arr_addsub_anchored_offset_arraylike(self, obox, box_df_fail):
+    def test_td64arr_addsub_anchored_offset_arraylike(
+            self, obox, box_df_broadcast_failure):
         # GH#18824
-        box = box_df_fail  # DataFrame tries to broadcast incorrectly
+        box = box_df_broadcast_failure
         tdi = TimedeltaIndex(['1 days 00:00:00', '3 days 04:00:00'])
         tdi = tm.box_expected(tdi, box)
 
@@ -1090,11 +1027,11 @@ def test_td64arr_mul_int(self, box):
         result = 1 * idx
         tm.assert_equal(result, idx)
 
-    def test_td64arr_mul_tdlike_scalar_raises(self, delta, box):
+    def test_td64arr_mul_tdlike_scalar_raises(self, two_hours, box):
         rng = timedelta_range('1 days', '10 days', name='foo')
         rng = tm.box_expected(rng, box)
         with pytest.raises(TypeError):
-            rng * delta
+            rng * two_hours
 
     def test_tdi_mul_int_array_zerodim(self, box):
         rng5 = np.arange(5, dtype='int64')
@@ -1107,8 +1044,8 @@ def test_tdi_mul_int_array_zerodim(self, box):
         result = idx * np.array(5, dtype='int64')
         tm.assert_equal(result, expected)
 
-    def test_tdi_mul_int_array(self, box_df_fail):
-        box = box_df_fail  # DataFrame tries to broadcast incorrectly
+    def test_tdi_mul_int_array(self, box_df_broadcast_failure):
+        box = box_df_broadcast_failure
         rng5 = np.arange(5, dtype='int64')
         idx = TimedeltaIndex(rng5)
         expected = TimedeltaIndex(rng5 ** 2)
@@ -1120,7 +1057,7 @@ def test_tdi_mul_int_array(self, box_df_fail):
         tm.assert_equal(result, expected)
 
     def test_tdi_mul_int_series(self, box_df_fail):
-        box = box_df_fail  # DataFrame tries to broadcast incorrectly
+        box = box_df_fail
         idx = TimedeltaIndex(np.arange(5, dtype='int64'))
         expected = TimedeltaIndex(np.arange(5, dtype='int64') ** 2)
 
@@ -1133,7 +1070,7 @@ def test_tdi_mul_int_series(self, box_df_fail):
         tm.assert_equal(result, expected)
 
     def test_tdi_mul_float_series(self, box_df_fail):
-        box = box_df_fail  # DataFrame tries to broadcast incorrectly
+        box = box_df_fail
         idx = TimedeltaIndex(np.arange(5, dtype='int64'))
         idx = tm.box_expected(idx, box)
 
@@ -1186,7 +1123,7 @@ def test_td64arr_div_int(self, box):
         result = idx / 1
         tm.assert_equal(result, idx)
 
-    def test_tdi_div_tdlike_scalar(self, delta, box):
+    def test_tdi_div_tdlike_scalar(self, two_hours, box):
         # GH#20088, GH#22163 ensure DataFrame returns correct dtype
         rng = timedelta_range('1 days', '10 days', name='foo')
         expected = pd.Float64Index((np.arange(10) + 1) * 12, name='foo')
@@ -1194,17 +1131,17 @@ def test_tdi_div_tdlike_scalar(self, delta, box):
         rng = tm.box_expected(rng, box)
         expected = tm.box_expected(expected, box)
 
-        result = rng / delta
+        result = rng / two_hours
         tm.assert_equal(result, expected)
 
-    def test_tdi_div_tdlike_scalar_with_nat(self, delta, box):
+    def test_tdi_div_tdlike_scalar_with_nat(self, two_hours, box):
         rng = TimedeltaIndex(['1 days', pd.NaT, '2 days'], name='foo')
         expected = pd.Float64Index([12, np.nan, 24], name='foo')
 
         rng = tm.box_expected(rng, box)
         expected = tm.box_expected(expected, box)
 
-        result = rng / delta
+        result = rng / two_hours
         tm.assert_equal(result, expected)
 
     # ------------------------------------------------------------------
@@ -1260,14 +1197,14 @@ def test_td64arr_floordiv_int(self, box):
         result = idx // 1
         tm.assert_equal(result, idx)
 
-    def test_td64arr_floordiv_tdlike_scalar(self, delta, box):
+    def test_td64arr_floordiv_tdlike_scalar(self, two_hours, box):
         tdi = timedelta_range('1 days', '10 days', name='foo')
         expected = pd.Int64Index((np.arange(10) + 1) * 12, name='foo')
 
         tdi = tm.box_expected(tdi, box)
         expected = tm.box_expected(expected, box)
 
-        result = tdi // delta
+        result = tdi // two_hours
         tm.assert_equal(result, expected)
 
     # TODO: Is this redundant with test_td64arr_floordiv_tdlike_scalar?
@@ -1364,14 +1301,6 @@ def test_td64arr_div_numeric_scalar(self, box, two, tdser):
         result = tdser / two
         tm.assert_equal(result, expected)
 
-    @pytest.mark.parametrize('box', [
-        pd.Index,
-        Series,
-        pytest.param(pd.DataFrame,
-                     marks=pytest.mark.xfail(reason="broadcasts along "
-                                                    "wrong axis",
-                                             strict=True))
-    ], ids=lambda x: x.__name__)
     @pytest.mark.parametrize('dtype', ['int64', 'int32', 'int16',
                                        'uint64', 'uint32', 'uint16', 'uint8',
                                        'float64', 'float32', 'float16'])
@@ -1380,9 +1309,11 @@ def test_td64arr_div_numeric_scalar(self, box, two, tdser):
                                         Series([20, 30, 40])],
                              ids=lambda x: type(x).__name__)
     @pytest.mark.parametrize('op', [operator.mul, ops.rmul])
-    def test_td64arr_rmul_numeric_array(self, op, box, vector, dtype, tdser):
+    def test_td64arr_rmul_numeric_array(self, op, box_df_fail,
+                                        vector, dtype, tdser):
         # GH#4521
         # divide/multiply by integers
+        box = box_df_fail  # broadcasts incorrectly but doesn't raise
         vector = vector.astype(dtype)
 
         expected = Series(['1180 Days', '1770 Days', 'NaT'],
@@ -1428,22 +1359,15 @@ def test_td64arr_div_numeric_array(self, box, vector, dtype, tdser):
         with pytest.raises(TypeError):
             vector / tdser
 
-    # TODO: Should we be parametrizing over types for `ser` too?
-    @pytest.mark.parametrize('box', [
-        pd.Index,
-        Series,
-        pytest.param(pd.DataFrame,
-                     marks=pytest.mark.xfail(reason="broadcasts along "
-                                                    "wrong axis",
-                                             strict=True))
-    ], ids=lambda x: x.__name__)
     @pytest.mark.parametrize('names', [(None, None, None),
                                        ('Egon', 'Venkman', None),
                                        ('NCC1701D', 'NCC1701D', 'NCC1701D')])
-    def test_td64arr_mul_int_series(self, box, names):
+    def test_td64arr_mul_int_series(self, box_df_fail, names):
         # GH#19042 test for correct name attachment
+        box = box_df_fail  # broadcasts along wrong axis, but doesn't raise
         tdi = TimedeltaIndex(['0days', '1day', '2days', '3days', '4days'],
                              name=names[0])
+        # TODO: Should we be parametrizing over types for `ser` too?
         ser = Series([0, 1, 2, 3, 4], dtype=np.int64, name=names[1])
 
         expected = Series(['0days', '1day', '4days', '9days', '16days'],
@@ -1491,10 +1415,6 @@ def test_float_series_rdiv_td64arr(self, box, names):
 
 class TestTimedeltaArraylikeInvalidArithmeticOps(object):
 
-    @pytest.mark.parametrize('scalar_td', [
-        timedelta(minutes=5, seconds=4),
-        Timedelta('5m4s'),
-        Timedelta('5m4s').to_timedelta64()])
     def test_td64arr_pow_invalid(self, scalar_td, box):
         td1 = Series([timedelta(minutes=5, seconds=3)] * 3)
         td1.iloc[2] = np.nan