Unit test

Author: rbenes

pandas/tests/groupby/test_groupby.py

@@ -1714,3 +1714,35 @@ 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():
+    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)