REF: Unify use of factorize() in groupby

Grouping._codes_and_uniques and BaseGrouper._get_compressed_codes
were both semantically doing the same thing as
core.algorithms.factorize(), so rename them so that it's just a bit
easier to follow.

Per a review comment in pandas-dev#46207

Author: NickCrews

pandas/core/groupby/grouper.py

@@ -619,7 +619,7 @@ def codes(self) -> npt.NDArray[np.signedinteger]:
             # _codes is set in __init__ for MultiIndex cases
             return self._codes
 
-        return self._codes_and_uniques[0]
+        return self._factorize[0]
 
     @cache_readonly
     def group_arraylike(self) -> ArrayLike:
@@ -635,7 +635,7 @@ def group_arraylike(self) -> ArrayLike:
             # retain dtype for categories, including unobserved ones
             return self.result_index._values
 
-        return self._codes_and_uniques[1]
+        return self._factorize[1]
 
     @cache_readonly
     def result_index(self) -> Index:
@@ -653,11 +653,12 @@ def group_index(self) -> Index:
             # _group_index is set in __init__ for MultiIndex cases
             return self._group_index
 
-        uniques = self._codes_and_uniques[1]
+        uniques = self._factorize[1]
         return Index._with_infer(uniques, name=self.name)
 
     @cache_readonly
-    def _codes_and_uniques(self) -> tuple[npt.NDArray[np.signedinteger], ArrayLike]:
+    def _factorize(self) -> tuple[npt.NDArray[np.signedinteger], ArrayLike]:
+        """Analogous to core.algorithms.factorize"""
         if self._passed_categorical:
             # we make a CategoricalIndex out of the cat grouper
             # preserving the categories / ordered attributes

pandas/core/groupby/ops.py

@@ -878,7 +878,7 @@ def has_dropped_na(self) -> bool:
 
     @cache_readonly
     def group_info(self) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp], int]:
-        comp_ids, obs_group_ids = self._get_compressed_codes()
+        comp_ids, obs_group_ids = self._factorize()
 
         ngroups = len(obs_group_ids)
         comp_ids = ensure_platform_int(comp_ids)
@@ -899,10 +899,10 @@ def codes_info(self) -> npt.NDArray[np.intp]:
         return ids
 
     @final
-    def _get_compressed_codes(
+    def _factorize(
         self,
     ) -> tuple[npt.NDArray[np.signedinteger], npt.NDArray[np.intp]]:
-        # The first returned ndarray may have any signed integer dtype
+        """Analogous to core.algorithms.factorize"""
         if len(self.groupings) > 1:
             group_index = get_group_index(self.codes, self.shape, sort=True, xnull=True)
             return compress_group_index(group_index, sort=self._sort)