Backport PR #31528 on branch 1.0.x (REGR: Categorical with np.str_ categories)

doc/source/whatsnew/v1.0.1.rst

@@ -22,6 +22,7 @@ Fixed regressions
 - Fixed regression in :meth:`GroupBy.apply` if called with a function which returned a non-pandas non-scalar object (e.g. a list or numpy array) (:issue:`31441`)
 - Fixed regression in :meth:`to_datetime` when parsing non-nanosecond resolution datetimes (:issue:`31491`)
 - Fixed regression in :meth:`~DataFrame.to_csv` where specifying an ``na_rep`` might truncate the values written (:issue:`31447`)
+- Fixed regression in :class:`Categorical` construction with ``numpy.str_`` categories (:issue:`31499`)
 - Fixed regression where setting :attr:`pd.options.display.max_colwidth` was not accepting negative integer. In addition, this behavior has been deprecated in favor of using ``None`` (:issue:`31532`)
 - Fixed regression in objTOJSON.c fix return-type warning (:issue:`31463`)
 - Fixed regression in :meth:`qcut` when passed a nullable integer. (:issue:`31389`)

pandas/_libs/hashtable_class_helper.pxi.in

@@ -670,7 +670,9 @@ cdef class StringHashTable(HashTable):
             val = values[i]
 
             if isinstance(val, str):
-                v = get_c_string(val)
+                # GH#31499 if we have a np.str_ get_c_string wont recognize
+                #  it as a str, even though isinstance does.
+                v = get_c_string(<str>val)
             else:
                 v = get_c_string(self.na_string_sentinel)
             vecs[i] = v
@@ -703,7 +705,9 @@ cdef class StringHashTable(HashTable):
             val = values[i]
 
             if isinstance(val, str):
-                v = get_c_string(val)
+                # GH#31499 if we have a np.str_ get_c_string wont recognize
+                #  it as a str, even though isinstance does.
+                v = get_c_string(<str>val)
             else:
                 v = get_c_string(self.na_string_sentinel)
             vecs[i] = v

pandas/tests/arrays/categorical/test_constructors.py

@@ -408,6 +408,11 @@ def test_constructor_str_unknown(self):
         with pytest.raises(ValueError, match="Unknown dtype"):
             Categorical([1, 2], dtype="foo")
 
+    def test_constructor_np_strs(self):
+        # GH#31499 Hastable.map_locations needs to work on np.str_ objects
+        cat = pd.Categorical(["1", "0", "1"], [np.str_("0"), np.str_("1")])
+        assert all(isinstance(x, np.str_) for x in cat.categories)
+
     def test_constructor_from_categorical_with_dtype(self):
         dtype = CategoricalDtype(["a", "b", "c"], ordered=True)
         values = Categorical(["a", "b", "d"])