TST: fix tests failing with exact=True (pandas-dev#64481)

Author: natmokval

pandas/tests/arrays/sparse/test_array.py

@@ -481,7 +481,9 @@ def test_dropna(fill_value):
     tm.assert_sp_array_equal(arr.dropna(), exp)
 
     df = pd.DataFrame({"a": [0, 1], "b": arr})
-    expected_df = pd.DataFrame({"a": [1], "b": exp}, index=pd.Index([1]))
+    expected_df = pd.DataFrame(
+        {"a": [1], "b": exp}, index=pd.RangeIndex(start=1, stop=2, step=1)
+    )
     tm.assert_equal(df.dropna(), expected_df)
 
 

pandas/tests/frame/methods/test_asof.py

@@ -5,6 +5,7 @@
 
 from pandas import (
     DataFrame,
+    Index,
     Period,
     Series,
     Timestamp,
@@ -105,7 +106,7 @@ def test_asof_all_nans(self, frame_or_series):
         # GH 15713
         # DataFrame/Series is all nans
         result = frame_or_series([np.nan]).asof([0])
-        expected = frame_or_series([np.nan])
+        expected = frame_or_series([np.nan], index=Index([0]))
         tm.assert_equal(result, expected)
 
     def test_all_nans(self, date_range_frame):

pandas/tests/groupby/test_all_methods.py

@@ -91,7 +91,7 @@ def test_not_c_contiguous_mask(groupby_func):
     if groupby_func == "corrwith":
         # corrwith is deprecated
         return
-    df = DataFrame({"a": [1, 1, 2], "b": [3, 4, 5]}, dtype="Int64")
+    df = DataFrame({"a": [1, 1, 2], "b": [3, 4, 5]}, dtype="Int64", index=[0, 1, 2])
     reversed = DataFrame(
         {"a": [2, 1, 1], "b": [5, 4, 3]}, dtype="Int64", index=[2, 1, 0]
     )[::-1]

pandas/tests/groupby/test_groupby.py

@@ -1834,6 +1834,7 @@ def get_categorical_invalid_expected():
     if override_dtype is not None:
         expected = expected.astype(override_dtype)
     if len(keys) == 1:
+        expected.index = Index([], dtype=df[keys[0]].dtype, name=keys[0])
         expected.index.name = keys[0]
     tm.assert_equal(result, expected)
 

pandas/tests/groupby/test_grouping.py

@@ -465,7 +465,7 @@ def test_groupby_series_named_with_tuple(self, frame_or_series, index):
         obj = frame_or_series([1, 2, 3, 4], index=index)
         groups = Series([1, 0, 1, 0], index=index, name=("a", "a"))
         result = obj.groupby(groups).last()
-        expected = frame_or_series([4, 3])
+        expected = frame_or_series([4, 3], index=Index([0, 1]))
         expected.index.name = ("a", "a")
         tm.assert_equal(result, expected)
 

pandas/tests/io/pytables/test_timezones.py

@@ -13,6 +13,7 @@
 from pandas import (
     DataFrame,
     DatetimeIndex,
+    Index,
     Series,
     Timestamp,
     date_range,
@@ -241,7 +242,7 @@ def test_timezones_fixed_format_empty(temp_hdfstore, tz_aware_fixture, frame_or_
 
     dtype = pd.DatetimeTZDtype(tz=tz_aware_fixture)
 
-    obj = Series(dtype=dtype, name="A")
+    obj = Series(dtype=dtype, name="A", index=Index([]))
     if frame_or_series is DataFrame:
         obj = obj.to_frame()
 

pandas/tests/reshape/concat/test_categorical.py

@@ -183,7 +183,12 @@ def test_concat_categorical_datetime(self):
 
         result = pd.concat([df1, df2])
         expected = DataFrame(
-            {"x": Series([datetime(2021, 1, 1), datetime(2021, 1, 2)])}
+            {
+                "x": Series(
+                    [datetime(2021, 1, 1), datetime(2021, 1, 2)],
+                    index=[0, 1],
+                )
+            }
         )
 
         tm.assert_equal(result, expected)