Move test to test_function.py and implement PR changes

Author: rbenes

pandas/tests/groupby/test_function.py

@@ -400,6 +400,28 @@ def test_groupby_non_arithmetic_agg_int_like_precision(i):
         assert res.iloc[0].b == data["expected"]
 
 
+@pytest.mark.parametrize("func, expected", [
+    ("idxmin", {'c_int': [0, 2], 'c_float': [1, 3], 'c_date': [1, 2]}),
+    ("idxmax", {'c_int': [1, 3], 'c_float': [0, 2], 'c_date': [0, 3]})
+])
+def test_idxmin_idxmax_returns_int_types(func, expected):
+    # GH 25444
+    df = pd.DataFrame({'name': ['A', 'A', 'B', 'B'],
+                       'c_int': [1, 2, 3, 4],
+                       'c_float': [4.02, 3.03, 2.04, 1.05],
+                       'c_date': ['2019', '2018', '2016', '2017']})
+    df['c_date'] = pd.to_datetime(df['c_date'])
+
+    result = getattr(df.groupby('name'), func)()
+
+    for col in result:
+        assert result[col].dtype == np.int64
+
+    df_expected = pd.DataFrame(expected, index=Index(['A', 'B'], name="name"))
+
+    tm.assert_frame_equal(result, df_expected)
+
+
 def test_fill_consistency():
 
     # GH9221

pandas/tests/groupby/test_groupby.py

@@ -1714,36 +1714,3 @@ def test_groupby_multiindex_nat():
     result = ser.groupby(level=1).mean()
     expected = pd.Series([3., 2.5], index=["a", "b"])
     assert_series_equal(result, expected)
-
-
-def test_idxmin_idxmax_returns_int_types():
-    # GH 25444
-    df = pd.DataFrame({'name': ['A', 'A', 'B', 'B'],
-                       'c_int': [1, 2, 3, 4],
-                       'c_float': [4.02, 3.03, 2.04, 1.05],
-                       'c_date': ['2019', '2018', '2016', '2017']})
-    df['c_date'] = pd.to_datetime(df['c_date'])
-
-    idxmins_computed = df.groupby('name').idxmin()
-    idxmaxs_computed = df.groupby('name').idxmax()
-
-    for col in idxmaxs_computed:
-        assert idxmins_computed[col].dtype == np.int64
-        assert idxmaxs_computed[col].dtype == np.int64
-
-    idxmins_expected = pd.DataFrame({'c_int': [0, 2],
-                                     'c_float': [1, 3],
-                                     'c_date': [1, 2]},
-                                    index=['A', 'B'])
-
-    idxmins_expected.index.name = "name"
-
-    idxmaxs_expected = pd.DataFrame({'c_int': [1, 3],
-                                     'c_float': [0, 2],
-                                     'c_date': [0, 3]},
-                                    index=['A', 'B'])
-
-    idxmaxs_expected.index.name = "name"
-
-    assert_frame_equal(idxmins_expected, idxmins_computed)
-    assert_frame_equal(idxmaxs_expected, idxmaxs_computed)