BUG: Series.argsort validate axis

doc/source/whatsnew/v2.1.0.rst

@@ -642,6 +642,7 @@ Other
 - Bug in :meth:`DataFrame.shift` with ``axis=1`` on a :class:`DataFrame` with a single :class:`ExtensionDtype` column giving incorrect results (:issue:`53832`)
 - Bug in :meth:`Index.sort_values` when a ``key`` is passed (:issue:`52764`)
 - Bug in :meth:`Series.align`, :meth:`DataFrame.align`, :meth:`Series.reindex`, :meth:`DataFrame.reindex`, :meth:`Series.interpolate`, :meth:`DataFrame.interpolate`, incorrectly failing to raise with method="asfreq" (:issue:`53620`)
+- Bug in :meth:`Series.argsort` failing to raise when an invalid ``axis`` is passed (:issue:`54257`)
 - Bug in :meth:`Series.map` when giving a callable to an empty series, the returned series had ``object`` dtype. It now keeps the original dtype (:issue:`52384`)
 - Bug in :meth:`Series.memory_usage` when ``deep=True`` throw an error with Series of objects and the returned value is incorrect, as it does not take into account GC corrections (:issue:`51858`)
 - Bug in :meth:`period_range` the default behavior when freq was not passed as an argument was incorrect(:issue:`53687`)

pandas/core/series.py

@@ -3958,6 +3958,10 @@ def argsort(
         2    0
         dtype: int64
         """
+        if axis != -1:
+            # GH#54257 We allow -1 here so that np.argsort(series) works
+            self._get_axis_number(axis)
+
         values = self._values
         mask = isna(values)
 

pandas/tests/series/methods/test_argsort.py

@@ -10,12 +10,20 @@
 
 
 class TestSeriesArgsort:
+    def test_argsort_axis(self):
+        # GH#54257
+        ser = Series(range(3))
+
+        msg = "No axis named 2 for object type Series"
+        with pytest.raises(ValueError, match=msg):
+            ser.argsort(axis=2)
+
     def test_argsort_numpy(self, datetime_series):
         ser = datetime_series
-        func = np.argsort
-        tm.assert_numpy_array_equal(
-            func(ser).values, func(np.array(ser)), check_dtype=False
-        )
+
+        res = np.argsort(ser).values
+        expected = np.argsort(np.array(ser))
+        tm.assert_numpy_array_equal(res, expected)
 
         # with missing values
         ts = ser.copy()
@@ -25,10 +33,10 @@ def test_argsort_numpy(self, datetime_series):
         with tm.assert_produces_warning(
             FutureWarning, match=msg, check_stacklevel=False
         ):
-            result = func(ts)[1::2]
-        expected = func(np.array(ts.dropna()))
+            result = np.argsort(ts)[1::2]
+        expected = np.argsort(np.array(ts.dropna()))
 
-        tm.assert_numpy_array_equal(result.values, expected, check_dtype=False)
+        tm.assert_numpy_array_equal(result.values, expected)
 
     def test_argsort(self, datetime_series):
         argsorted = datetime_series.argsort()