diff --git a/python/ray/dataframe/dataframe.py b/python/ray/dataframe/dataframe.py
index 2eadeda8054f..470e6a72072b 100644
--- a/python/ray/dataframe/dataframe.py
+++ b/python/ray/dataframe/dataframe.py
@@ -2944,29 +2944,54 @@ def __setstate__(self, state):
             "github.com/ray-project/ray.")
 
     def __delitem__(self, key):
-        """Delete an item by key. `del a[key]` for example.
+        """Delete a column by key. `del a[key]` for example.
            Operation happens in place.
 
+           Notes: This operation happen on row and column partition
+                  simultaneously. No rebuild.
         Args:
             key: key to delete
         """
+        # Create helper method for deleting column(s) in row partition.
         to_delete = self.columns.get_loc(key)
 
         def del_helper(df):
-            df.__delitem__(to_delete)
-            df.reset_index(drop=True, inplace=True)
+            cols = df.columns[to_delete]  # either int or an array of ints
+
+            if isinstance(cols, int):
+                cols = [cols]
+
+            for col in cols:
+                df.__delitem__(col)
+
+            df.columns = pd.RangeIndex(0, len(df.columns))
             return df
 
-        self._row_partitions = _map_partitions(del_helper, self._row_partitions)
+        self._row_partitions = _map_partitions(
+            del_helper, self._row_partitions)
 
-        # TODO: See if this is faster than just:
-        # self._col_partitions = _map_partitions(del_helper, self._col_partitions)
-        # Cast cols as pd.Series as duplicate columns mean result may be np.int64 or pd.Series
-        col_parts_to_del = pd.Series(self._col_index.loc[key, 'partition']).unique()
+        # Cast cols as pd.Series as duplicate columns mean result may be
+        # np.int64 or pd.Series
+        col_parts_to_del = pd.Series(
+            self._col_index.loc[key, 'partition']).unique()
+        self._col_index = self._col_index.drop(key)
         for i in col_parts_to_del:
-            self._col_partitions[i] = _deploy_func.remote(del_helper, self._col_partitions[i])
+            self._col_partitions[i] = _deploy_func.remote(
+                del_helper, self._col_partitions[i])
 
-        self._col_index = self._col_index.drop(key)
+            partition_mask = (self._col_index['partition'] == i)
+
+            try:
+                self._col_index.loc[partition_mask,
+                                    'index_within_partition'] = [
+                    p for p in range(sum(partition_mask))]
+            except ValueError:
+                # Copy the arrrow sealed dataframe so we can mutate it.
+                # We only do this the first time we try to mutate the sealed.
+                self._col_index = self._col_index.copy()
+                self._col_index.loc[partition_mask,
+                                    'index_within_partition'] = [
+                    p for p in range(sum(partition_mask))]
 
     def __finalize__(self, other, method=None, **kwargs):
         raise NotImplementedError(
@@ -3107,6 +3132,7 @@ def __neg__(self):
                                    self._col_partitions)
 
         return DataFrame(columns=self.columns,
+                         index=self.index,
                          row_partitions=new_rows,
                          col_partitions=new_cols)