API: Rename BaseGrouper.recons_codes to BaseGrouper.reconstructed_codes

pandas/core/groupby/generic.py

@@ -655,7 +655,7 @@ def value_counts(
         rep = partial(np.repeat, repeats=np.add.reduceat(inc, idx))
 
         # multi-index components
-        codes = self.grouper.recons_codes
+        codes = self.grouper.reconstructed_codes
         codes = [rep(level_codes) for level_codes in codes] + [llab(lab, inc)]
         levels = [ping.group_index for ping in self.grouper.groupings] + [lev]
         names = self.grouper.names + [self._selection_name]

pandas/core/groupby/ops.py

@@ -7,7 +7,7 @@
 """
 
 import collections
-from typing import List, Optional, Sequence, Type
+from typing import List, Optional, Sequence, Tuple, Type
 
 import numpy as np
 
@@ -216,11 +216,11 @@ def indices(self):
             return get_indexer_dict(codes_list, keys)
 
     @property
-    def codes(self):
+    def codes(self) -> List[np.ndarray]:
         return [ping.codes for ping in self.groupings]
 
     @property
-    def levels(self):
+    def levels(self) -> List[Index]:
         return [ping.group_index for ping in self.groupings]
 
     @property
@@ -264,16 +264,16 @@ def group_info(self):
         return comp_ids, obs_group_ids, ngroups
 
     @cache_readonly
-    def codes_info(self):
+    def codes_info(self) -> np.ndarray:
         # return the codes of items in original grouped axis
         codes, _, _ = self.group_info
         if self.indexer is not None:
             sorter = np.lexsort((codes, self.indexer))
             codes = codes[sorter]
         return codes
 
-    def _get_compressed_codes(self):
-        all_codes = [ping.codes for ping in self.groupings]
+    def _get_compressed_codes(self) -> Tuple[np.ndarray, np.ndarray]:
+        all_codes = self.codes
         if len(all_codes) > 1:
             group_index = get_group_index(all_codes, self.shape, sort=True, xnull=True)
             return compress_group_index(group_index, sort=self.sort)
@@ -286,17 +286,17 @@ def ngroups(self) -> int:
         return len(self.result_index)
 
     @property
-    def recons_codes(self):
+    def reconstructed_codes(self) -> List[np.ndarray]:
+        codes = self.codes
         comp_ids, obs_ids, _ = self.group_info
-        codes = (ping.codes for ping in self.groupings)
         return decons_obs_group_ids(comp_ids, obs_ids, self.shape, codes, xnull=True)
 
     @cache_readonly
     def result_index(self):
         if not self.compressed and len(self.groupings) == 1:
             return self.groupings[0].result_index.rename(self.names[0])
 
-        codes = self.recons_codes
+        codes = self.reconstructed_codes
         levels = [ping.result_index for ping in self.groupings]
         result = MultiIndex(
             levels=levels, codes=codes, verify_integrity=False, names=self.names
@@ -308,7 +308,7 @@ def get_group_levels(self):
             return [self.groupings[0].result_index]
 
         name_list = []
-        for ping, codes in zip(self.groupings, self.recons_codes):
+        for ping, codes in zip(self.groupings, self.reconstructed_codes):
             codes = ensure_platform_int(codes)
             levels = ping.result_index.take(codes)
 
@@ -768,7 +768,7 @@ def group_info(self):
         )
 
     @cache_readonly
-    def recons_codes(self):
+    def reconstructed_codes(self) -> List[np.ndarray]:
         # get unique result indices, and prepend 0 as groupby starts from the first
         return [np.r_[0, np.flatnonzero(self.bins[1:] != self.bins[:-1]) + 1]]