MultiIndex.labels -> MulitIndex.codes

Author: topper-123

pandas/core/frame.py

@@ -1807,7 +1807,7 @@ def to_panel(self):
             selfsorted = self
 
         major_axis, minor_axis = selfsorted.index.levels
-        major_labels, minor_labels = selfsorted.index.labels
+        major_codes, minor_codes = selfsorted.index.codes
         shape = len(major_axis), len(minor_axis)
 
         # preserve names, if any
@@ -1822,8 +1822,8 @@ def to_panel(self):
 
         # create new manager
         new_mgr = selfsorted._data.reshape_nd(axes=new_axes,
-                                              labels=[major_labels,
-                                                      minor_labels],
+                                              labels=[major_codes,
+                                                      minor_codes],
                                               shape=shape,
                                               ref_items=selfsorted.columns)
 
@@ -4259,7 +4259,7 @@ def _maybe_casted_values(index, labels=None):
             if isinstance(self.index, MultiIndex):
                 names = [n if n is not None else ('level_%d' % i)
                          for (i, n) in enumerate(self.index.names)]
-                to_insert = lzip(self.index.levels, self.index.labels)
+                to_insert = lzip(self.index.levels, self.index.codes)
             else:
                 default = 'index' if 'index' not in self else 'level_0'
                 names = ([default] if self.index.name is None
@@ -7167,8 +7167,9 @@ def _count_level(self, level, axis=0, numeric_only=False):
             level = count_axis._get_level_number(level)
 
         level_index = count_axis.levels[level]
-        labels = ensure_int64(count_axis.labels[level])
-        counts = lib.count_level_2d(mask, labels, len(level_index), axis=0)
+        level_codes = ensure_int64(count_axis.codes[level])
+        counts = lib.count_level_2d(mask, level_codes, len(level_index),
+                                    axis=0)
 
         result = DataFrame(counts, index=level_index, columns=agg_axis)
 

pandas/core/groupby/generic.py

@@ -1111,7 +1111,7 @@ def value_counts(self, normalize=False, sort=True, ascending=False,
             lab = cut(Series(val), bins, include_lowest=True)
             lev = lab.cat.categories
             lab = lev.take(lab.cat.codes)
-            llab = lambda lab, inc: lab[inc]._multiindex.labels[-1]
+            llab = lambda lab, inc: lab[inc]._multiindex.codes[-1]
 
         if is_interval_dtype(lab):
             # TODO: should we do this inside II?

pandas/core/indexes/base.py

@@ -3258,27 +3258,27 @@ def droplevel(self, level=0):
         # The two checks above guarantee that here self is a MultiIndex
 
         new_levels = list(self.levels)
-        new_labels = list(self.labels)
+        new_codes = list(self.codes)
         new_names = list(self.names)
 
         for i in levnums:
             new_levels.pop(i)
-            new_labels.pop(i)
+            new_codes.pop(i)
             new_names.pop(i)
 
         if len(new_levels) == 1:
 
             # set nan if needed
-            mask = new_labels[0] == -1
-            result = new_levels[0].take(new_labels[0])
+            mask = new_codes[0] == -1
+            result = new_levels[0].take(new_codes[0])
             if mask.any():
                 result = result.putmask(mask, np.nan)
 
             result.name = new_names[0]
             return result
         else:
             from .multi import MultiIndex
-            return MultiIndex(levels=new_levels, labels=new_labels,
+            return MultiIndex(levels=new_levels, labels=new_codes,
                               names=new_names, verify_integrity=False)
 
     _index_shared_docs['get_indexer'] = """
@@ -4054,19 +4054,19 @@ def _get_leaf_sorter(labels):
                 left_indexer = None
                 join_index = left
             else:  # sort the leaves
-                left_indexer = _get_leaf_sorter(left.labels[:level + 1])
+                left_indexer = _get_leaf_sorter(left.codes[:level + 1])
                 join_index = left[left_indexer]
 
         else:
             left_lev_indexer = ensure_int64(left_lev_indexer)
             rev_indexer = lib.get_reverse_indexer(left_lev_indexer,
                                                   len(old_level))
 
-            new_lev_labels = algos.take_nd(rev_indexer, left.labels[level],
+            new_lev_labels = algos.take_nd(rev_indexer, left.codes[level],
                                            allow_fill=False)
 
-            new_labels = list(left.labels)
-            new_labels[level] = new_lev_labels
+            new_codes = list(left.codes)
+            new_codes[level] = new_lev_labels
 
             new_levels = list(left.levels)
             new_levels[level] = new_level
@@ -4075,7 +4075,7 @@ def _get_leaf_sorter(labels):
                 left_indexer = np.arange(len(left), dtype=np.intp)
                 mask = new_lev_labels != -1
                 if not mask.all():
-                    new_labels = [lab[mask] for lab in new_labels]
+                    new_codes = [lab[mask] for lab in new_codes]
                     left_indexer = left_indexer[mask]
 
             else:  # tie out the order with other
@@ -4086,31 +4086,31 @@ def _get_leaf_sorter(labels):
 
                     # missing values are placed first; drop them!
                     left_indexer = left_indexer[counts[0]:]
-                    new_labels = [lab[left_indexer] for lab in new_labels]
+                    new_codes = [lab[left_indexer] for lab in new_codes]
 
                 else:  # sort the leaves
                     mask = new_lev_labels != -1
                     mask_all = mask.all()
                     if not mask_all:
-                        new_labels = [lab[mask] for lab in new_labels]
+                        new_codes = [lab[mask] for lab in new_codes]
 
-                    left_indexer = _get_leaf_sorter(new_labels[:level + 1])
-                    new_labels = [lab[left_indexer] for lab in new_labels]
+                    left_indexer = _get_leaf_sorter(new_codes[:level + 1])
+                    new_codes = [lab[left_indexer] for lab in new_codes]
 
                     # left_indexers are w.r.t masked frame.
                     # reverse to original frame!
                     if not mask_all:
                         left_indexer = mask.nonzero()[0][left_indexer]
 
-            join_index = MultiIndex(levels=new_levels, labels=new_labels,
+            join_index = MultiIndex(levels=new_levels, labels=new_codes,
                                     names=left.names, verify_integrity=False)
 
         if right_lev_indexer is not None:
             right_indexer = algos.take_nd(right_lev_indexer,
-                                          join_index.labels[level],
+                                          join_index.codes[level],
                                           allow_fill=False)
         else:
-            right_indexer = join_index.labels[level]
+            right_indexer = join_index.codes[level]
 
         if flip_order:
             left_indexer, right_indexer = right_indexer, left_indexer