Fix reset_index with the default index is "distributed-sequence".

databricks/koalas/frame.py

@@ -2722,36 +2722,32 @@ def rename(index):
         if drop:
             new_index_map = []
 
-        internal = self._internal.copy(
-            sdf=sdf,
-            index_map=index_map,
-            column_index=None,
-            column_scols=([scol_for(sdf, name_like_string(name)) for _, name in new_index_map]
-                          + self._internal.column_scols))
-
         if self._internal.column_index_level > 1:
             column_depth = len(self._internal.column_index[0])
             if col_level >= column_depth:
                 raise IndexError('Too many levels: Index has only {} levels, not {}'
                                  .format(column_depth, col_level + 1))
             if any(col_level + len(name) > column_depth for _, name in new_index_map):
                 raise ValueError('Item must have length equal to number of levels.')
-            columns = pd.MultiIndex.from_tuples(
-                [tuple(([col_fill] * col_level)
-                       + list(name)
-                       + ([col_fill] * (column_depth - (len(name) + col_level))))
-                 for _, name in new_index_map]
-                + self._internal.column_index)
+            column_index = ([tuple(([col_fill] * col_level)
+                                   + list(name)
+                                   + ([col_fill] * (column_depth - (len(name) + col_level))))
+                             for _, name in new_index_map]
+                            + self._internal.column_index)
         else:
-            columns = [name for _, name in new_index_map] + self._internal.column_index
+            column_index = [name for _, name in new_index_map] + self._internal.column_index
+
+        internal = self._internal.copy(
+            sdf=sdf,
+            index_map=index_map,
+            column_index=column_index,
+            column_scols=([scol_for(sdf, name_like_string(name)) for _, name in new_index_map]
+                          + [scol_for(sdf, col) for col in self._internal.data_columns]))
 
         if inplace:
             self._internal = internal
-            self.columns = columns
         else:
-            kdf = DataFrame(internal)
-            kdf.columns = columns
-            return kdf
+            return DataFrame(internal)
 
     def isnull(self):
         """

databricks/koalas/tests/test_dataframe.py

@@ -158,6 +158,24 @@ def test_iterrows(self):
             self.assert_eq(pdf_k, kdf_k)
             self.assert_eq(pdf_v, kdf_v)
 
+    def test_reset_index_with_default_index_types(self):
+        pdf = pd.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6]},
+                           index=np.random.rand(3))
+        kdf = ks.from_pandas(pdf)
+
+        with ks.option_context('compute.default_index_type', 'sequence'):
+            self.assert_eq(kdf.reset_index(), pdf.reset_index())
+
+        with ks.option_context('compute.default_index_type', 'distributed-sequence'):
+            # the order might be changed.
+            self.assert_eq(kdf.reset_index().sort_index(),
+                           pdf.reset_index())
+
+        with ks.option_context('compute.default_index_type', 'distributed'):
+            # the index is different.
+            self.assert_eq(kdf.reset_index().to_pandas().reset_index(drop=True),
+                           pdf.reset_index())
+
     def test_reset_index_with_multiindex_columns(self):
         index = pd.MultiIndex.from_tuples([('bird', 'falcon'),
                                            ('bird', 'parrot'),

databricks/koalas/tests/test_series.py

@@ -469,6 +469,23 @@ def test_any(self):
 
         self.assert_eq((kser % 2 == 0).any(), (pser % 2 == 0).any())
 
+    def test_reset_index_with_default_index_types(self):
+        pser = pd.Series([1, 2, 3], name='0', index=np.random.rand(3))
+        kser = ks.from_pandas(pser)
+
+        with ks.option_context('compute.default_index_type', 'sequence'):
+            self.assert_eq(kser.reset_index(), pser.reset_index())
+
+        with ks.option_context('compute.default_index_type', 'distributed-sequence'):
+            # the order might be changed.
+            self.assert_eq(kser.reset_index().sort_index(),
+                           pser.reset_index())
+
+        with ks.option_context('compute.default_index_type', 'distributed'):
+            # the index is different.
+            self.assert_eq(kser.reset_index().to_pandas().reset_index(drop=True),
+                           pser.reset_index())
+
     def test_sort_values(self):
         pser = pd.Series([1, 2, 3, 4, 5, None, 7], name='0')
         kser = ks.from_pandas(pser)