ENH: Add ignore_index for df.sort_values and series.sort_values

doc/source/whatsnew/v1.0.0.rst

@@ -474,6 +474,7 @@ Other API changes
   Supplying anything else than ``how`` to ``**kwargs`` raised a ``TypeError`` previously (:issue:`29388`)
 - When testing pandas, the new minimum required version of pytest is 5.0.1 (:issue:`29664`)
 - :meth:`Series.str.__iter__` was deprecated and will be removed in future releases (:issue:`28277`).
+- ``ignore_index`` is added in :meth:`DataFrame.sort_values` and :meth:`Series.sort_values` to be able to reset index after sorting (:issue:`30114`)
 
 
 .. _whatsnew_1000.api.documentation:

pandas/core/frame.py

@@ -4704,6 +4704,7 @@ def sort_values(
         inplace=False,
         kind="quicksort",
         na_position="last",
+        ignore_index=False,
     ):
         inplace = validate_bool_kwarg(inplace, "inplace")
         axis = self._get_axis_number(axis)
@@ -4737,6 +4738,9 @@ def sort_values(
             indexer, axis=self._get_block_manager_axis(axis), verify=False
         )
 
+        if ignore_index:
+            new_data.axes[1] = ibase.default_index(len(indexer))
+
         if inplace:
             return self._update_inplace(new_data)
         else:

pandas/core/generic.py

@@ -4087,6 +4087,7 @@ def sort_values(
         inplace: bool_t = False,
         kind: str = "quicksort",
         na_position: str = "last",
+        ignore_index: bool_t = False,
     ):
         """
         Sort by the values along either axis.
@@ -4109,6 +4110,8 @@ def sort_values(
         na_position : {'first', 'last'}, default 'last'
              Puts NaNs at the beginning if `first`; `last` puts NaNs at the
              end.
+        ignore_index : bool, default False
+             If True, the resulting axis will be labeled 0, 1, …, n - 1.
 
         Returns
         -------

pandas/core/series.py

@@ -2693,6 +2693,7 @@ def sort_values(
         inplace=False,
         kind="quicksort",
         na_position="last",
+        ignore_index=False,
     ):
         """
         Sort by the values.
@@ -2715,6 +2716,8 @@ def sort_values(
         na_position : {'first' or 'last'}, default 'last'
             Argument 'first' puts NaNs at the beginning, 'last' puts NaNs at
             the end.
+        ignore_index : bool, default False
+             If True, the resulting axis will be labeled 0, 1, …, n - 1.
 
         Returns
         -------
@@ -2855,6 +2858,9 @@ def _try_kind_sort(arr):
 
         result = self._constructor(arr[sortedIdx], index=self.index[sortedIdx])
 
+        if ignore_index:
+            result = result.reset_index(drop=True)
+
         if inplace:
             self._update_inplace(result)
         else:

pandas/tests/frame/test_sorting.py

@@ -376,6 +376,36 @@ def test_sort_nat(self):
         sorted_df = df.sort_values(by=["a", "b"])
         tm.assert_frame_equal(sorted_df, expected)
 
+    @pytest.mark.parametrize(
+        "original_dict, sorted_dict, ignore_index, output_index",
+        [
+            ({"A": [1, 2, 3]}, {"A": [3, 2, 1]}, True, [0, 1, 2]),
+            ({"A": [1, 2, 3]}, {"A": [3, 2, 1]}, False, [2, 1, 0]),
+            (
+                {"A": [1, 2, 3], "B": [2, 3, 4]},
+                {"A": [3, 2, 1], "B": [4, 3, 2]},
+                True,
+                [0, 1, 2],
+            ),
+            (
+                {"A": [1, 2, 3], "B": [2, 3, 4]},
+                {"A": [3, 2, 1], "B": [4, 3, 2]},
+                False,
+                [2, 1, 0],
+            ),
+        ],
+    )
+    def test_sort_values_ignore_index(
+        self, original_dict, sorted_dict, ignore_index, output_index
+    ):
+
+        # GH 30114
+        df = pd.DataFrame(original_dict)
+        sorted_df = df.sort_values("A", ascending=False, ignore_index=ignore_index)
+
+        expected = pd.DataFrame(sorted_dict, index=output_index)
+        tm.assert_frame_equal(sorted_df, expected)
+
 
 class TestDataFrameSortIndexKinds:
     def test_sort_index_multicolumn(self):

pandas/tests/series/test_sorting.py

@@ -269,3 +269,21 @@ def test_sort_values_categorical(self):
         result = df.sort_values(by=["grade", "id"])
         expected = df.iloc[[2, 1, 5, 4, 3, 0]]
         tm.assert_frame_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "original_list, sorted_list, ignore_index, output_index",
+        [
+            ([2, 3, 6, 1], [6, 3, 2, 1], True, [0, 1, 2, 3]),
+            ([2, 3, 6, 1], [6, 3, 2, 1], False, [2, 1, 0, 3]),
+        ],
+    )
+    def test_sort_values_ignore_index(
+        self, original_list, sorted_list, ignore_index, output_index
+    ):
+
+        # GH 30114
+        sr = Series(original_list)
+        sorted_sr = sr.sort_values(ascending=False, ignore_index=ignore_index)
+
+        expected = Series(sorted_list, index=output_index)
+        tm.assert_series_equal(sorted_sr, expected)