deprecate passing args as positional in sort_values

Author: MarcoGorelli

doc/source/whatsnew/v1.3.0.rst

@@ -647,6 +647,7 @@ Deprecations
 - Deprecated setting :attr:`Categorical._codes`, create a new :class:`Categorical` with the desired codes instead (:issue:`40606`)
 - Deprecated behavior of :meth:`DatetimeIndex.union` with mixed timezones; in a future version both will be cast to UTC instead of object dtype (:issue:`39328`)
 - Deprecated using ``usecols`` with out of bounds indices for ``read_csv`` with ``engine="c"`` (:issue:`25623`)
+- Deprecated passing arguments as positional (except for ``by``) in :meth:`DataFrame.sort_values` and :meth:`Series.sort_values` (:issue:`41485`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/frame.py

@@ -6188,6 +6188,7 @@ def f(vals) -> tuple[np.ndarray, int]:
     # ----------------------------------------------------------------------
     # Sorting
     # TODO: Just move the sort_values doc here.
+    @deprecate_nonkeyword_arguments(version="2.0", allowed_args=["self", "by"])
     @Substitution(**_shared_doc_kwargs)
     @Appender(NDFrame.sort_values.__doc__)
     # error: Signature of "sort_values" incompatible with supertype "NDFrame"

pandas/core/series.py

@@ -3224,6 +3224,7 @@ def update(self, other) -> None:
     # ----------------------------------------------------------------------
     # Reindexing, sorting
 
+    @deprecate_nonkeyword_arguments(version="2.0", allowed_args=["self"])
     def sort_values(
         self,
         axis=0,

pandas/tests/frame/methods/test_sort_values.py

@@ -856,3 +856,13 @@ def test_sort_column_level_and_index_label(
                 tm.assert_frame_equal(result, expected)
         else:
             tm.assert_frame_equal(result, expected)
+
+    def test_sort_values_pos_args_deprecation(self):
+        # https://github.com/pandas-dev/pandas/issues/41485
+        df = DataFrame({"a": [1, 2, 3]})
+        msg = (
+            r"Starting with Pandas version 2\.0 all arguments of sort_values except "
+            r"for the arguments 'self' and 'by' will be keyword-only"
+        )
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            df.sort_values("a", 0)

pandas/tests/series/methods/test_sort_values.py

@@ -187,30 +187,40 @@ def test_sort_values_ignore_index(
         tm.assert_series_equal(result_ser, expected)
         tm.assert_series_equal(ser, Series(original_list))
 
+    def test_sort_values_pos_args_deprecation(self):
+        # https://github.com/pandas-dev/pandas/issues/41485
+        ser = Series([1, 2, 3])
+        msg = (
+            r"Starting with Pandas version 2\.0 all arguments of sort_values except "
+            r"for the argument 'self' will be keyword-only"
+        )
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            ser.sort_values(0)
+
 
 class TestSeriesSortingKey:
     def test_sort_values_key(self):
         series = Series(np.array(["Hello", "goodbye"]))
 
-        result = series.sort_values(0)
+        result = series.sort_values(axis=0)
         expected = series
         tm.assert_series_equal(result, expected)
 
-        result = series.sort_values(0, key=lambda x: x.str.lower())
+        result = series.sort_values(axis=0, key=lambda x: x.str.lower())
         expected = series[::-1]
         tm.assert_series_equal(result, expected)
 
     def test_sort_values_key_nan(self):
         series = Series(np.array([0, 5, np.nan, 3, 2, np.nan]))
 
-        result = series.sort_values(0)
+        result = series.sort_values(axis=0)
         expected = series.iloc[[0, 4, 3, 1, 2, 5]]
         tm.assert_series_equal(result, expected)
 
-        result = series.sort_values(0, key=lambda x: x + 5)
+        result = series.sort_values(axis=0, key=lambda x: x + 5)
         expected = series.iloc[[0, 4, 3, 1, 2, 5]]
         tm.assert_series_equal(result, expected)
 
-        result = series.sort_values(0, key=lambda x: -x, ascending=False)
+        result = series.sort_values(axis=0, key=lambda x: -x, ascending=False)
         expected = series.iloc[[0, 4, 3, 1, 2, 5]]
         tm.assert_series_equal(result, expected)