Applying request changes removing unnecessary test and renameing

Author: jaehoonhwang

pandas/tests/tools/test_concat.py

@@ -1902,63 +1902,14 @@ def test_concat_multiindex_dfs_with_deepcopy(self):
         result_no_copy = pd.concat(example_dict, names=['testname'])
         tm.assert_frame_equal(result_no_copy, expected)
 
-    def test_concat_no_unnecessary_upcast(self):
-        # GH 13247
-        for pdt in [pd.Series, pd.DataFrame, pd.Panel]:
-            dims = pdt().ndim
-            for dt in np.sctypes['float']:
-                dfs = [pdt(np.array([1], dtype=dt, ndmin=dims)),
-                       pdt(np.array([np.nan], dtype=dt, ndmin=dims)),
-                       pdt(np.array([5], dtype=dt, ndmin=dims))]
-                x = pd.concat(dfs)
-                self.assertTrue(x.values.dtype == dt)
-
-            for dt in (np.sctypes['int'] + np.sctypes['uint']):
-                dfs = [pdt(np.array([1], dtype=dt, ndmin=dims)),
-                       pdt(np.array([5], dtype=dt, ndmin=dims))]
-                x = pd.concat(dfs)
-                self.assertTrue(x.values.dtype == dt)
-
-            objs = []
-            objs.append(pdt(np.array([1], dtype=np.float32, ndmin=dims)))
-            objs.append(pdt(np.array([1], dtype=np.float16, ndmin=dims)))
-            self.assertTrue(pd.concat(objs).values.dtype == np.float32)
-
-            objs = []
-            objs.append(pdt(np.array([1], dtype=np.int32, ndmin=dims)))
-            objs.append(pdt(np.array([1], dtype=np.int64, ndmin=dims)))
-            self.assertTrue(pd.concat(objs).values.dtype == np.int64)
-
-            # not sure what is the best answer here
-            objs = []
-            objs.append(pdt(np.array([1], dtype=np.int32, ndmin=dims)))
-            objs.append(pdt(np.array([1], dtype=np.float16, ndmin=dims)))
-            self.assertTrue(pd.concat(objs).values.dtype == np.float64)
-
 
 @pytest.mark.parametrize('pdt', [pd.Series, pd.DataFrame, pd.Panel])
 @pytest.mark.parametrize('dt', np.sctypes['float'])
-def test_concat_no_unnecessary_upcast_pytest(dt, pdt):
+def test_concat_no_unnecessary_upcast(dt, pdt):
     # GH 13247
     dims = pdt().ndim
     dfs = [pdt(np.array([1], dtype=dt, ndmin=dims)),
            pdt(np.array([np.nan], dtype=dt, ndmin=dims)),
            pdt(np.array([5], dtype=dt, ndmin=dims))]
     x = pd.concat(dfs)
     assert x.values.dtype == dt
-
-    objs = []
-    objs.append(pdt(np.array([1], dtype=np.float32, ndmin=dims)))
-    objs.append(pdt(np.array([1], dtype=np.float16, ndmin=dims)))
-    assert pd.concat(objs).values.dtype == np.float32
-
-    objs = []
-    objs.append(pdt(np.array([1], dtype=np.int32, ndmin=dims)))
-    objs.append(pdt(np.array([1], dtype=np.int64, ndmin=dims)))
-    assert pd.concat(objs).values.dtype == np.int64
-
-    # not sure what is the best answer here
-    objs = []
-    objs.append(pdt(np.array([1], dtype=np.int32, ndmin=dims)))
-    objs.append(pdt(np.array([1], dtype=np.float16, ndmin=dims)))
-    assert pd.concat(objs).values.dtype == np.float64