ENH: Add argmax and argmin to ExtensionArray

doc/source/whatsnew/v0.25.1.rst

@@ -6,6 +6,7 @@ What's new in 0.25.1 (July XX, 2019)
 Enhancements
 ~~~~~~~~~~~~
 
+- Add :meth:`ExtensionArray.argmax`, :meth:`ExtensionArray.max`, :meth:`ExtensionArray.argmin` and :meth:`ExtensionArray.min` (:issue:`24382`)
 
 .. _whatsnew_0251.enhancements.other:
 

pandas/core/arrays/base.py

@@ -461,6 +461,35 @@ def argsort(self, ascending=True, kind="quicksort", *args, **kwargs):
         result = nargsort(self, kind=kind, ascending=ascending, na_position="last")
         return result
 
+    def argmin(self):
+        """
+        Return the minimun argument indexer.
+
+        Returns
+        -------
+        scalar
+            Minimun argument indexer.
+
+        See Also
+        --------
+        Index.max : Return the maximum value of the object.
+        Series.min : Return the minimum value in a Series.
+        DataFrame.min : Return the minimum values in a DataFrame.
+        """
+        return self.argsort()[0]
+
+    def min(self):
+        min_idx = self.argmin()
+        return self[min_idx]
+
+    def argmax(self):
+        no_nan = self.isna().sum()
+        return self.argsort()[-1 - no_nan]
+
+    def max(self):
+        max_idx = self.argmax()
+        return self[max_idx]
+
     def fillna(self, value=None, method=None, limit=None):
         """
         Fill NA/NaN values using the specified method.

pandas/tests/extension/arrow/arrays.py

@@ -155,6 +155,18 @@ def any(self, axis=0, out=None):
     def all(self, axis=0, out=None):
         return self._data.to_pandas().all()
 
+    def argmin(self):
+        raise NotImplementedError
+
+    def min(self):
+        raise NotImplementedError
+
+    def argmax(self):
+        raise NotImplementedError
+
+    def max(self):
+        raise NotImplementedError
+
 
 class ArrowBoolArray(ArrowExtensionArray):
     def __init__(self, values):

pandas/tests/extension/arrow/test_bool.py

@@ -53,6 +53,16 @@ def test_from_sequence_from_cls(self, data):
 
 
 class TestReduce(base.BaseNoReduceTests):
+    @pytest.mark.parametrize("skipna", [True, False])
+    def test_reduce_series_numeric(self, data, all_numeric_reductions, skipna):
+        op_name = all_numeric_reductions
+        if op_name in ("max", "min"):
+            pass
+        else:
+            ser = pd.Series(data)
+            with pytest.raises(TypeError):
+                getattr(ser, op_name)(skipna=skipna)
+
     def test_reduce_series_boolean(self):
         pass
 

pandas/tests/extension/base/methods.py

@@ -59,6 +59,30 @@ def test_argsort_missing(self, data_missing_for_sorting):
         expected = pd.Series(np.array([1, -1, 0], dtype=np.int64))
         self.assert_series_equal(result, expected)
 
+    def test_argmax(self, data_missing_for_sorting):
+        # GH 24382
+        result = data_missing_for_sorting.argmax()
+        expected = 0
+        assert result == expected
+
+    def test_max(self, data_missing_for_sorting):
+        # GH 24382
+        result = data_missing_for_sorting.max()
+        expected = data_missing_for_sorting[0]
+        assert result == expected
+
+    def test_argmin(self, data_missing_for_sorting):
+        # GH 24382
+        result = data_missing_for_sorting.argmin()
+        expected = 2
+        assert result == expected
+
+    def test_min(self, data_missing_for_sorting):
+        # GH 24382
+        result = data_missing_for_sorting.min()
+        expected = data_missing_for_sorting[2]
+        assert result == expected
+
     @pytest.mark.parametrize(
         "na_position, expected",
         [

pandas/tests/extension/test_categorical.py

@@ -195,6 +195,14 @@ def test_searchsorted(self, data_for_sorting):
         if not data_for_sorting.ordered:
             raise pytest.skip(reason="searchsorted requires ordered data.")
 
+    def test_max(self):
+        # GH 24382
+        pass
+
+    def test_min(self):
+        # GH 24382
+        pass
+
 
 class TestCasting(base.BaseCastingTests):
     pass

pandas/tests/extension/test_numpy.py

@@ -246,6 +246,20 @@ def test_repeat(self, data, repeats, as_series, use_numpy):
         # Fails creating expected
         super().test_repeat(data, repeats, as_series, use_numpy)
 
+    def test_max(self):
+        # GH 24382
+        data = PandasArray(np.array([1, np.nan, 0]))
+        result = data.max()
+        expected = data[0]
+        assert result == expected
+
+    def test_min(self):
+        # GH 24382
+        data = PandasArray(np.array([1, np.nan, 0]))
+        result = data.min()
+        expected = data[2]
+        assert result == expected
+
 
 @skip_nested
 class TestArithmetics(BaseNumPyTests, base.BaseArithmeticOpsTests):