fixed a bunch of failing tests

pandas/tests/frame/test_apply.py

@@ -133,7 +133,7 @@ def test_nunique_empty(self):
         tm.assert_series_equal(result, expected)
 
         result = df.T.nunique()
-        expected = Series([], index=pd.Index([]))
+        expected = Series(index=pd.Index([]), dtype=np.float64)
         tm.assert_series_equal(result, expected)
 
     def test_apply_standard_nonunique(self):
@@ -1265,16 +1265,16 @@ def test_non_callable_aggregates(self):
             _get_cython_table_params(
                 DataFrame(),
                 [
-                    ("sum", Series()),
-                    ("max", Series()),
-                    ("min", Series()),
+                    ("sum", Series(dtype="float64")),
+                    ("max", Series(dtype="float64")),
+                    ("min", Series(dtype="float64")),
                     ("all", Series(dtype=bool)),
                     ("any", Series(dtype=bool)),
-                    ("mean", Series()),
-                    ("prod", Series()),
-                    ("std", Series()),
-                    ("var", Series()),
-                    ("median", Series()),
+                    ("mean", Series(dtype="float64")),
+                    ("prod", Series(dtype="float64")),
+                    ("std", Series(dtype="float64")),
+                    ("var", Series(dtype="float64")),
+                    ("median", Series(dtype="float64")),
                 ],
             ),
             _get_cython_table_params(

pandas/tests/frame/test_constructors.py

@@ -2442,7 +2442,7 @@ def test_from_records_series_list_dict(self):
     def test_to_frame_with_falsey_names(self):
         # GH 16114
         result = Series(name=0).to_frame().dtypes
-        expected = Series({0: np.float64})
+        expected = Series({0: object})
         tm.assert_series_equal(result, expected)
 
         result = DataFrame(Series(name=0)).dtypes

pandas/tests/frame/test_indexing.py

@@ -2574,7 +2574,9 @@ def test_xs_corner(self):
         # no columns but Index(dtype=object)
         df = DataFrame(index=["a", "b", "c"])
         result = df.xs("a")
-        expected = Series([], name="a", index=pd.Index([], dtype=object))
+        expected = Series(
+            [], name="a", index=pd.Index([], dtype=object), dtype="float64"
+        )
         tm.assert_series_equal(result, expected)
 
     def test_xs_duplicates(self):

pandas/tests/generic/test_generic.py

@@ -734,11 +734,8 @@ def test_squeeze(self):
         # don't fail with 0 length dimensions GH11229 & GH8999
         empty_series = Series([], name="five")
         empty_frame = DataFrame([empty_series])
-
-        [
-            tm.assert_series_equal(empty_series, higher_dim.squeeze())
-            for higher_dim in [empty_series, empty_frame]
-        ]
+        tm.assert_series_equal(empty_series, empty_series.squeeze())
+        tm.assert_series_equal(empty_series, empty_frame.squeeze())
 
         # axis argument
         df = tm.makeTimeDataFrame(nper=1).iloc[:, :1]

pandas/tests/groupby/test_grouping.py

@@ -602,7 +602,7 @@ def test_evaluate_with_empty_groups(self, func, expected):
 
     def test_groupby_empty(self):
         # https://github.com/pandas-dev/pandas/issues/27190
-        s = pd.Series([], name="name")
+        s = pd.Series(name="name", dtype="float64")
         gr = s.groupby([])
 
         result = gr.mean()

pandas/tests/indexing/multiindex/test_loc.py

@@ -50,7 +50,9 @@ def test_loc_getitem_series(self):
 
         empty = Series(data=[], dtype=np.float64)
         expected = Series(
-            [], index=MultiIndex(levels=index.levels, codes=[[], []], dtype=np.float64)
+            [],
+            index=MultiIndex(levels=index.levels, codes=[[], []], dtype=np.float64),
+            dtype=np.float64,
         )
         result = x.loc[empty]
         tm.assert_series_equal(result, expected)
@@ -72,7 +74,9 @@ def test_loc_getitem_array(self):
         # empty array:
         empty = np.array([])
         expected = Series(
-            [], index=MultiIndex(levels=index.levels, codes=[[], []], dtype=np.float64)
+            [],
+            index=MultiIndex(levels=index.levels, codes=[[], []], dtype=np.float64),
+            dtype="float64",
         )
         result = x.loc[empty]
         tm.assert_series_equal(result, expected)

pandas/tests/io/json/test_pandas.py

@@ -670,7 +670,7 @@ def test_series_roundtrip_object(self, orient, numpy, dtype):
     def test_series_roundtrip_empty(self, orient, numpy):
         data = self.empty_series.to_json(orient=orient)
         result = pd.read_json(data, typ="series", orient=orient, numpy=numpy)
-        expected = self.empty_series.copy()
+        expected = self.empty_series.copy().astype("float64")
 
         # TODO: see what causes inconsistency
         if orient in ("values", "records"):

pandas/tests/reductions/test_reductions.py

@@ -900,7 +900,7 @@ def test_timedelta64_analytics(self):
     @pytest.mark.parametrize(
         "test_input,error_type",
         [
-            (pd.Series([]), ValueError),
+            (pd.Series(dtype="float64"), ValueError),
             # For strings, or any Series with dtype 'O'
             (pd.Series(["foo", "bar", "baz"]), TypeError),
             (pd.Series([(1,), (2,)]), TypeError),

pandas/tests/reshape/test_concat.py

@@ -2196,7 +2196,7 @@ def test_concat_period_other_series(self):
     def test_concat_empty_series(self):
         # GH 11082
         s1 = pd.Series([1, 2, 3], name="x")
-        s2 = pd.Series(name="y")
+        s2 = pd.Series(name="y", dtype="float64")
         res = pd.concat([s1, s2], axis=1)
         exp = pd.DataFrame(
             {"x": [1, 2, 3], "y": [np.nan, np.nan, np.nan]},
@@ -2205,15 +2205,15 @@ def test_concat_empty_series(self):
         tm.assert_frame_equal(res, exp)
 
         s1 = pd.Series([1, 2, 3], name="x")
-        s2 = pd.Series(name="y")
+        s2 = pd.Series(name="y", dtype="float64")
         res = pd.concat([s1, s2], axis=0)
         # name will be reset
         exp = pd.Series([1, 2, 3])
         tm.assert_series_equal(res, exp)
 
         # empty Series with no name
         s1 = pd.Series([1, 2, 3], name="x")
-        s2 = pd.Series(name=None)
+        s2 = pd.Series(name=None, dtype="float64")
         res = pd.concat([s1, s2], axis=1)
         exp = pd.DataFrame(
             {"x": [1, 2, 3], 0: [np.nan, np.nan, np.nan]},
@@ -2228,7 +2228,7 @@ def test_concat_empty_series_timelike(self, tz, values):
         # GH 18447
 
         first = Series([], dtype="M8[ns]").dt.tz_localize(tz)
-        second = Series(values)
+        second = Series(values, dtype="float64")
         expected = DataFrame(
             {
                 0: pd.Series([pd.NaT] * len(values), dtype="M8[ns]").dt.tz_localize(tz),

pandas/tests/window/test_moments.py

@@ -674,7 +674,7 @@ def f(x):
 
         self._check_moment_func(np.mean, name="apply", func=f, raw=raw)
 
-        expected = Series([])
+        expected = Series(dtype="float64")
         result = expected.rolling(10).apply(lambda x: x.mean(), raw=raw)
         tm.assert_series_equal(result, expected)
 
@@ -1201,7 +1201,7 @@ def _check_ew(self, name=None, preserve_nan=False):
 
             # check series of length 0
             result = getattr(Series().ewm(com=50, min_periods=min_periods), name)()
-            tm.assert_series_equal(result, Series())
+            tm.assert_series_equal(result, Series(dtype="float64"))
 
             # check series of length 1
             result = getattr(Series([1.0]).ewm(50, min_periods=min_periods), name)()
@@ -1996,8 +1996,8 @@ def func(A, B, com, **kwargs):
             assert not np.isnan(result.values[11:]).any()
 
             # check series of length 0
-            result = func(Series([]), Series([]), 50, min_periods=min_periods)
-            tm.assert_series_equal(result, Series([]))
+            result = func(Series(), Series(), 50, min_periods=min_periods)
+            tm.assert_series_equal(result, Series(dtype="float64"))
 
             # check series of length 1
             result = func(Series([1.0]), Series([1.0]), 50, min_periods=min_periods)
@@ -2197,7 +2197,7 @@ def test_rolling_functions_window_non_shrinkage_binary(self):
 
     def test_moment_functions_zero_length(self):
         # GH 8056
-        s = Series()
+        s = Series(dtype="float64")
         s_expected = s
         df1 = DataFrame()
         df1_expected = df1
@@ -2416,7 +2416,7 @@ def expanding_mean(x, min_periods=1):
         # here to make this pass
         self._check_expanding(expanding_mean, np.mean, preserve_nan=False)
 
-        ser = Series([])
+        ser = Series([], dtype="float64")
         tm.assert_series_equal(ser, ser.expanding().apply(lambda x: x.mean(), raw=raw))
 
         # GH 8080