API: Make Categorical.searchsorted returns a scalar when supplied a scalar

doc/source/whatsnew/v0.24.0.rst

@@ -1007,6 +1007,8 @@ Other API Changes
 - Slicing a single row of a DataFrame with multiple ExtensionArrays of the same type now preserves the dtype, rather than coercing to object (:issue:`22784`)
 - :class:`DateOffset` attribute `_cacheable` and method `_should_cache` have been removed (:issue:`23118`)
 - Comparing :class:`Timedelta` to be less or greater than unknown types now raises a ``TypeError`` instead of returning ``False`` (:issue:`20829`)
+- :meth:`Categorical.searchsorted`, when supplied a scalar value to search for, now returns a scalar instead of an array (:issue:`23466`).
+- :meth:`Categorical.searchsorted` now raises a ``KeyError`` rather that a ``ValueError``, if a searched for key is not found in its categories (:issue:`23466`).
 - :meth:`Index.hasnans` and :meth:`Series.hasnans` now always return a python boolean. Previously, a python or a numpy boolean could be returned, depending on circumstances (:issue:`23294`).
 - The order of the arguments of :func:`DataFrame.to_html` and :func:`DataFrame.to_string` is rearranged to be consistent with each other. (:issue:`23614`)
 

pandas/core/arrays/categorical.py

@@ -1344,15 +1344,13 @@ def searchsorted(self, value, side='left', sorter=None):
                              "ordered one")
 
         from pandas.core.series import Series
+        codes = _get_codes_for_values(Series(value).values, self.categories)
+        if -1 in codes:
+            raise KeyError("Value(s) to be inserted must be in categories.")
 
-        values_as_codes = _get_codes_for_values(Series(value).values,
-                                                self.categories)
+        codes = codes[0] if is_scalar(value) else codes
 
-        if -1 in values_as_codes:
-            raise ValueError("Value(s) to be inserted must be in categories.")
-
-        return self.codes.searchsorted(values_as_codes, side=side,
-                                       sorter=sorter)
+        return self.codes.searchsorted(codes, side=side, sorter=sorter)
 
     def isna(self):
         """

pandas/tests/arrays/categorical/test_analytics.py

@@ -85,10 +85,10 @@ def test_searchsorted(self):
 
         # Searching for single item argument, side='left' (default)
         res_cat = c1.searchsorted('apple')
+        assert res_cat == 2
+
         res_ser = s1.searchsorted('apple')
-        exp = np.array([2], dtype=np.intp)
-        tm.assert_numpy_array_equal(res_cat, exp)
-        tm.assert_numpy_array_equal(res_ser, exp)
+        assert res_ser == 2
 
         # Searching for single item array, side='left' (default)
         res_cat = c1.searchsorted(['bread'])
@@ -105,13 +105,13 @@ def test_searchsorted(self):
         tm.assert_numpy_array_equal(res_ser, exp)
 
         # Searching for a single value that is not from the Categorical
-        pytest.raises(ValueError, lambda: c1.searchsorted('cucumber'))
-        pytest.raises(ValueError, lambda: s1.searchsorted('cucumber'))
+        pytest.raises(KeyError, lambda: c1.searchsorted('cucumber'))
+        pytest.raises(KeyError, lambda: s1.searchsorted('cucumber'))
 
         # Searching for multiple values one of each is not from the Categorical
-        pytest.raises(ValueError,
+        pytest.raises(KeyError,
                       lambda: c1.searchsorted(['bread', 'cucumber']))
-        pytest.raises(ValueError,
+        pytest.raises(KeyError,
                       lambda: s1.searchsorted(['bread', 'cucumber']))
 
         # searchsorted call for unordered Categorical