MultiIndex.labels -> MulitIndex.codes

Author: topper-123

pandas/core/frame.py

@@ -1839,7 +1839,7 @@ 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
@@ -1854,8 +1854,8 @@ 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)
 
@@ -4226,7 +4226,7 @@ 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
@@ -7147,8 +7147,9 @@ 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

@@ -1112,7 +1112,7 @@ 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?
@@ -1163,7 +1163,7 @@ def value_counts(self, normalize=False, sort=True, ascending=False,
             out, labels[-1] = out[sorter], labels[-1][sorter]
 
         if bins is None:
-            mi = MultiIndex(levels=levels, labels=labels, names=names,
+            mi = MultiIndex(levels=levels, codes=labels, names=names,
                             verify_integrity=False)
 
             if is_integer_dtype(out):
@@ -1194,7 +1194,7 @@ def value_counts(self, normalize=False, sort=True, ascending=False,
         labels = list(map(lambda lab: np.repeat(lab[diff], nbin), labels[:-1]))
         labels.append(left[-1])
 
-        mi = MultiIndex(levels=levels, labels=labels, names=names,
+        mi = MultiIndex(levels=levels, codes=labels, names=names,
                         verify_integrity=False)
 
         if is_integer_dtype(out):

pandas/core/groupby/ops.py

@@ -290,10 +290,10 @@ def result_index(self):
         if not self.compressed and len(self.groupings) == 1:
             return self.groupings[0].result_index.rename(self.names[0])
 
-        labels = self.recons_labels
+        codes = self.recons_labels
         levels = [ping.result_index for ping in self.groupings]
         result = MultiIndex(levels=levels,
-                            labels=labels,
+                            codes=codes,
                             verify_integrity=False,
                             names=self.names)
         return result