moved tests to tests/reductions/rest_reductions.py

pandas/tests/reductions/test_reductions.py

@@ -856,6 +856,16 @@ def test_idxmax(self):
         result = s.idxmin()
         assert result == 1.1
 
+        # GH#36566
+        s = Series("a", dtype="string").value_counts()
+        assert s.idxmax() == "a"
+
+        # GH#32749
+        from pandas.tests.extension.decimal import DecimalArray, make_data
+
+        s = Series(DecimalArray(make_data()[:1]))
+        assert s.idxmax() == 0
+
     def test_all_any(self):
         ts = tm.makeTimeSeries()
         bool_series = ts > 0
@@ -1007,6 +1017,27 @@ def test_idxminmax_with_inf(self):
             assert s.idxmax() == 0
             np.isnan(s.idxmax(skipna=False))
 
+    @pytest.mark.parametrize(
+        "op_name, skipna, expected",
+        [
+            ("idxmax", True, "b"),
+            ("idxmin", True, "a"),
+            ("argmax", True, 1),
+            ("argmin", True, 0),
+            ("idxmax", False, np.nan),
+            ("idxmin", False, np.nan),
+            ("argmax", False, -1),
+            ("argmin", False, -1),
+        ],
+    )
+    def test_argminmax_idxminmax(self, any_numeric_dtype, op_name, skipna, expected):
+        s = Series([1, 2, None], index=["a", "b", "c"], dtype=any_numeric_dtype)
+        result = getattr(s, op_name)(skipna=skipna)
+        if pd.isna(expected):
+            assert np.isnan(result)
+        else:
+            assert result == expected
+
 
 class TestDatetime64SeriesReductions:
     # Note: the name TestDatetime64SeriesReductions indicates these tests
@@ -1072,6 +1103,29 @@ def test_min_max_series(self):
         assert isinstance(result, Timestamp)
         assert result == exp
 
+    @pytest.mark.parametrize(
+        "op_name, skipna, expected",
+        [
+            ("idxmax", True, "b"),
+            ("idxmin", True, "a"),
+            ("argmax", True, 1),
+            ("argmin", True, 0),
+            ("idxmax", False, np.nan),
+            ("idxmin", False, np.nan),
+            ("argmax", False, -1),
+            ("argmin", False, -1),
+        ],
+    )
+    def test_argminmax_idxminmax(self, op_name, skipna, expected):
+        s = Series(
+            [datetime(2020, 1, 1), datetime(2020, 1, 2), None], index=["a", "b", "c"]
+        )
+        result = getattr(s, op_name)(skipna=skipna)
+        if pd.isna(expected):
+            assert np.isnan(result)
+        else:
+            assert result == expected
+
 
 class TestCategoricalSeriesReductions:
     # Note: the name TestCategoricalSeriesReductions indicates these tests

pandas/tests/series/test_reductions.py

@@ -1,5 +1,3 @@
-from datetime import datetime
-
 import numpy as np
 import pytest
 
@@ -116,61 +114,3 @@ def test_validate_stat_keepdims():
     )
     with pytest.raises(ValueError, match=msg):
         np.sum(ser, keepdims=True)
-
-
-@pytest.mark.parametrize(
-    "op_name, skipna, expected",
-    [
-        ("idxmax", True, "b"),
-        ("idxmin", True, "a"),
-        ("argmax", True, 1),
-        ("argmin", True, 0),
-        ("idxmax", False, np.nan),
-        ("idxmin", False, np.nan),
-        ("argmax", False, -1),
-        ("argmin", False, -1),
-    ],
-)
-def test_argminmax_idxminmax(any_numeric_dtype, op_name, skipna, expected):
-    ser = Series([1, 2, None], index=["a", "b", "c"], dtype=any_numeric_dtype)
-    result = getattr(ser, op_name)(skipna=skipna)
-    if pd.isna(expected):
-        assert np.isnan(result)
-    else:
-        assert result == expected
-
-
-@pytest.mark.parametrize(
-    "op_name, skipna, expected",
-    [
-        ("idxmax", True, "b"),
-        ("idxmin", True, "a"),
-        ("argmax", True, 1),
-        ("argmin", True, 0),
-        ("idxmax", False, np.nan),
-        ("idxmin", False, np.nan),
-        ("argmax", False, -1),
-        ("argmin", False, -1),
-    ],
-)
-def test_argminmax_idxminmax_with_datetime64_dtype(op_name, skipna, expected):
-    ser = Series(
-        [datetime(2020, 1, 1), datetime(2020, 1, 2), None], index=["a", "b", "c"]
-    )
-    result = getattr(ser, op_name)(skipna=skipna)
-    if pd.isna(expected):
-        assert np.isnan(result)
-    else:
-        assert result == expected
-
-
-def test_github_issues():
-    # GH#36566
-    ser = Series("a", dtype="string").value_counts()
-    assert ser.idxmax() == "a"
-
-    # GH#32749
-    from pandas.tests.extension.decimal import DecimalArray, make_data
-
-    ser = Series(DecimalArray(make_data()[:1]))
-    assert ser.idxmax() == 0