DEPR: argmin (#30113)

doc/source/whatsnew/v1.0.0.rst

@@ -611,6 +611,7 @@ or ``matplotlib.Axes.plot``. See :ref:`plotting.formatters` for more.
 - Changed the default ``fill_value`` in :meth:`Categorical.take` from ``True`` to ``False`` (:issue:`20841`)
 - Changed the default value for the `raw` argument in :func:`Series.rolling().apply() <pandas.core.window.Rolling.apply>`, :func:`DataFrame.rolling().apply() <pandas.core.window.Rolling.apply>`,
 - :func:`Series.expanding().apply() <pandas.core.window.Expanding.apply>`, and :func:`DataFrame.expanding().apply() <pandas.core.window.Expanding.apply>` to ``False`` (:issue:`20584`)
+- Removed deprecated behavior of :meth:`Series.argmin` and :meth:`Series.argmax`, use :meth:`Series.idxmin` and :meth:`Series.idxmax` for the old behavior (:issue:`16955`)
 - Passing a tz-aware ``datetime.datetime`` or :class:`Timestamp` into the :class:`Timestamp` constructor with the ``tz`` argument now raises a ``ValueError`` (:issue:`23621`)
 - Removed the previously deprecated :attr:`Series.base`, :attr:`Index.base`, :attr:`Categorical.base`, :attr:`Series.flags`, :attr:`Index.flags`, :attr:`PeriodArray.flags`, :attr:`Series.strides`, :attr:`Index.strides`, :attr:`Series.itemsize`, :attr:`Index.itemsize`, :attr:`Series.data`, :attr:`Index.data` (:issue:`20721`)
 - Changed :meth:`Timedelta.resolution` to match the behavior of the standard library ``datetime.timedelta.resolution``, for the old behavior, use :meth:`Timedelta.resolution_string` (:issue:`26839`)

pandas/core/series.py

@@ -13,7 +13,7 @@
 
 from pandas._libs import index as libindex, lib, reshape, tslibs
 from pandas.compat.numpy import function as nv
-from pandas.util._decorators import Appender, Substitution, deprecate
+from pandas.util._decorators import Appender, Substitution
 from pandas.util._validators import validate_bool_kwarg, validate_percentile
 
 from pandas.core.dtypes.common import (
@@ -2001,36 +2001,6 @@ def idxmax(self, axis=0, skipna=True, *args, **kwargs):
             return np.nan
         return self.index[i]
 
-    # ndarray compat
-    argmin = deprecate(
-        "argmin",
-        idxmin,
-        "0.21.0",
-        msg=dedent(
-            """
-        The current behaviour of 'Series.argmin' is deprecated, use 'idxmin'
-        instead.
-        The behavior of 'argmin' will be corrected to return the positional
-        minimum in the future. For now, use 'series.values.argmin' or
-        'np.argmin(np.array(values))' to get the position of the minimum
-        row."""
-        ),
-    )
-    argmax = deprecate(
-        "argmax",
-        idxmax,
-        "0.21.0",
-        msg=dedent(
-            """
-        The current behaviour of 'Series.argmax' is deprecated, use 'idxmax'
-        instead.
-        The behavior of 'argmax' will be corrected to return the positional
-        maximum in the future. For now, use 'series.values.argmax' or
-        'np.argmax(np.array(values))' to get the position of the maximum
-        row."""
-        ),
-    )
-
     def round(self, decimals=0, *args, **kwargs):
         """
         Round each value in a Series to the given number of decimals.

pandas/tests/reductions/test_reductions.py

@@ -695,52 +695,40 @@ def test_empty_timeseries_reductions_return_nat(self):
             assert Series([], dtype=dtype).min(skipna=False) is pd.NaT
             assert Series([], dtype=dtype).max(skipna=False) is pd.NaT
 
-    def test_numpy_argmin_deprecated(self):
+    def test_numpy_argmin(self):
         # See GH#16830
         data = np.arange(1, 11)
 
         s = Series(data, index=data)
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            # The deprecation of Series.argmin also causes a deprecation
-            # warning when calling np.argmin. This behavior is temporary
-            # until the implementation of Series.argmin is corrected.
-            result = np.argmin(s)
+        result = np.argmin(s)
 
-        assert result == 1
+        expected = np.argmin(data)
+        assert result == expected
 
-        with tm.assert_produces_warning(FutureWarning):
-            # argmin is aliased to idxmin
-            result = s.argmin()
+        result = s.argmin()
 
-        assert result == 1
+        assert result == expected
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            msg = "the 'out' parameter is not supported"
-            with pytest.raises(ValueError, match=msg):
-                np.argmin(s, out=data)
+        msg = "the 'out' parameter is not supported"
+        with pytest.raises(ValueError, match=msg):
+            np.argmin(s, out=data)
 
-    def test_numpy_argmax_deprecated(self):
+    def test_numpy_argmax(self):
         # See GH#16830
         data = np.arange(1, 11)
 
         s = Series(data, index=data)
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            # The deprecation of Series.argmax also causes a deprecation
-            # warning when calling np.argmax. This behavior is temporary
-            # until the implementation of Series.argmax is corrected.
-            result = np.argmax(s)
-        assert result == 10
-
-        with tm.assert_produces_warning(FutureWarning):
-            # argmax is aliased to idxmax
-            result = s.argmax()
-
-        assert result == 10
-
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            msg = "the 'out' parameter is not supported"
-            with pytest.raises(ValueError, match=msg):
-                np.argmax(s, out=data)
+        result = np.argmax(s)
+        expected = np.argmax(data)
+        assert result == expected
+
+        result = s.argmax()
+
+        assert result == expected
+
+        msg = "the 'out' parameter is not supported"
+        with pytest.raises(ValueError, match=msg):
+            np.argmax(s, out=data)
 
     def test_idxmin(self):
         # test idxmin