Update tests to return single index

Author: Kei

pandas/tests/groupby/methods/test_value_counts.py

@@ -329,13 +329,10 @@ def test_against_frame_and_seriesgroupby(
         else:
             name = "proportion" if normalize else "count"
             expected = expected.reset_index().rename({0: name}, axis=1)
-            if groupby == "column":
-                expected = expected.rename({"level_0": "country"}, axis=1)
-                expected["country"] = np.where(expected["country"], "US", "FR")
-            elif groupby == "function":
-                expected["level_0"] = expected["level_0"] == 1
+            if "level_0" in result:
+                expected.insert(loc=0, column="level_0", value=result["level_0"])
             else:
-                expected["level_0"] = np.where(expected["level_0"], "US", "FR")
+                expected.insert(loc=0, column="country", value=result["country"])
             tm.assert_frame_equal(result, expected)
     else:
         # compare against SeriesGroupBy value_counts

pandas/tests/groupby/test_groupby.py

@@ -113,8 +113,9 @@ def f(x, q=None, axis=0):
         expected_seq = df_grouped.quantile([0.4, 0.8])
         if not as_index:
             # apply treats the op as a transform; .quantile knows it's a reduction
-            apply_result = apply_result.reset_index()
-            apply_result["level_0"] = [1, 1, 2, 2]
+            apply_result.index = range(4)
+            apply_result.insert(loc=0, column="level_0", value=[1, 1, 2, 2])
+            apply_result.insert(loc=1, column="level_1", value=[0.4, 0.8, 0.4, 0.8])
         tm.assert_frame_equal(apply_result, expected_seq, check_names=False)
 
         agg_result = df_grouped.agg(f, q=80)
@@ -519,9 +520,7 @@ def test_as_index_select_column():
     result = df.groupby("A", as_index=False, group_keys=True)["B"].apply(
         lambda x: x.cumsum()
     )
-    expected = Series(
-        [2, 6, 6], name="B", index=MultiIndex.from_tuples([(0, 0), (0, 1), (1, 2)])
-    )
+    expected = Series([2, 6, 6], name="B", index=range(3))
     tm.assert_series_equal(result, expected)