remove tests per comments

Author: aram-cedarwood

pandas/tests/resample/test_resampler_grouper.py

@@ -778,157 +778,3 @@ def test_groupby_resample_on_column_when_index_is_unusual(df):
     expected = DataFrame({"numbers": [100, 200]}, index=index)
 
     tm.assert_frame_equal(result, expected)
-
-
-def test_groupby_resample_then_groupby_is_reused_when_index_is_out_of_order():
-    # GH 59350
-    df = DataFrame(
-        data={
-            "datetime": [
-                pd.to_datetime("2024-07-30T00:00Z"),
-                pd.to_datetime("2024-07-30T00:01Z"),
-            ],
-            "group": ["A", "A"],
-            "numbers": [100, 200],
-        },
-        index=[1, 0],
-    )
-
-    gb = df.groupby("group")
-
-    # use gb
-    result_1 = gb[["numbers"]].transform("sum")
-
-    index = Index([1, 0])
-    expected = DataFrame({"numbers": [300, 300]}, index=index)
-
-    tm.assert_frame_equal(result_1, expected)
-
-    # resample gb, unrelated to above
-    rs = gb.resample("1min", on="datetime")
-    result_2 = rs.aggregate({"numbers": "sum"})
-
-    index = pd.MultiIndex.from_arrays(
-        [
-            ["A", "A"],
-            [pd.to_datetime("2024-07-30T00:00Z"), pd.to_datetime("2024-07-30T00:01Z")],
-        ],
-        names=[
-            "group",
-            "datetime",
-        ],
-    )
-    expected = DataFrame({"numbers": [100, 200]}, index=index)
-
-    tm.assert_frame_equal(result_2, expected)
-
-    # reuse gb, unrelated to above
-    result_3 = gb[["numbers"]].transform("sum")
-
-    tm.assert_frame_equal(result_1, result_3)
-
-
-def test_groupby_resample_then_groupby_is_reused_when_index_is_set_from_column():
-    # GH 59350
-    df = DataFrame(
-        data={
-            "datetime": [
-                pd.to_datetime("2024-07-30T00:00Z"),
-                pd.to_datetime("2024-07-30T00:01Z"),
-            ],
-            "group": ["A", "A"],
-            "numbers": [100, 200],
-        },
-    ).set_index("group")
-
-    gb = df.groupby("group")
-
-    # use gb
-    result_1 = gb[["numbers"]].transform("sum")
-
-    index = Index(["A", "A"], name="group")
-    expected = DataFrame({"numbers": [300, 300]}, index=index)
-
-    tm.assert_frame_equal(result_1, expected)
-
-    # resample gb, unrelated to above
-    rs = gb.resample("1min", on="datetime")
-    result_2 = rs.aggregate({"numbers": "sum"})
-
-    index = pd.MultiIndex.from_arrays(
-        [
-            ["A", "A"],
-            [pd.to_datetime("2024-07-30T00:00Z"), pd.to_datetime("2024-07-30T00:01Z")],
-        ],
-        names=[
-            "group",
-            "datetime",
-        ],
-    )
-    expected = DataFrame({"numbers": [100, 200]}, index=index)
-
-    tm.assert_frame_equal(result_2, expected)
-
-    # reuse gb, unrelated to above
-    result_3 = gb[["numbers"]].transform("sum")
-
-    tm.assert_frame_equal(result_1, result_3)
-
-
-def test_groupby_resample_then_groupby_is_reused_when_groupby_selection_is_not_none():
-    # GH 59350
-    df = DataFrame(
-        data={
-            "datetime": [
-                pd.to_datetime("2024-07-30T00:00Z"),
-                pd.to_datetime("2024-07-30T00:01Z"),
-            ],
-            "group": ["A", "A"],
-            "numbers": [100, 200],
-        },
-        index=[1, 0],
-    )
-
-    gb = df.groupby("group")
-    gb = gb[["numbers", "datetime"]]  # gb._selection is ["numbers", "datetime"]
-
-    # use gb
-    result_1 = gb.transform("max")
-
-    index = Index([1, 0])
-    expected = DataFrame(
-        {
-            "numbers": [200, 200],
-            "datetime": [
-                pd.to_datetime("2024-07-30T00:01Z"),
-                pd.to_datetime("2024-07-30T00:01Z"),
-            ],
-        },
-        index=index,
-    )
-
-    tm.assert_frame_equal(result_1, expected)
-
-    # resample gb, unrelated to above
-    rs = gb.resample("1min", on="datetime")
-    result_2 = rs.aggregate({"numbers": "sum"})  # Enter the `except IndexError:` block
-
-    index = pd.MultiIndex.from_arrays(
-        [
-            ["A", "A"],
-            [pd.to_datetime("2024-07-30T00:00Z"), pd.to_datetime("2024-07-30T00:01Z")],
-        ],
-        names=[
-            "group",
-            "datetime",
-        ],
-    )
-    columns = pd.MultiIndex.from_arrays([["numbers"], ["numbers"]])
-    expected = DataFrame([[100], [200]], index=index, columns=columns)
-
-    tm.assert_frame_equal(result_2, expected)
-
-    # reuse gb, unrelated to above
-    result_3 = gb.transform("max")
-
-    tm.assert_frame_equal(result_1, result_3)