Change MultiIndex repr (labels -> codes) (#24731)

Author: topper-123

pandas/core/indexes/base.py

@@ -1302,15 +1302,15 @@ def set_names(self, names, level=None, inplace=False):
  ... [2018, 2019]])
  >>> idx
  MultiIndex(levels=[['cobra', 'python'], [2018, 2019]],
- labels=[[1, 1, 0, 0], [0, 1, 0, 1]])
+ codes=[[1, 1, 0, 0], [0, 1, 0, 1]])
  >>> idx.set_names(['kind', 'year'], inplace=True)
  >>> idx
  MultiIndex(levels=[['cobra', 'python'], [2018, 2019]],
- labels=[[1, 1, 0, 0], [0, 1, 0, 1]],
+ codes=[[1, 1, 0, 0], [0, 1, 0, 1]],
  names=['kind', 'year'])
  >>> idx.set_names('species', level=0)
  MultiIndex(levels=[['cobra', 'python'], [2018, 2019]],
- labels=[[1, 1, 0, 0], [0, 1, 0, 1]],
+ codes=[[1, 1, 0, 0], [0, 1, 0, 1]],
  names=['species', 'year'])
  """
 
@@ -1373,11 +1373,11 @@ def rename(self, name, inplace=False):
  ... names=['kind', 'year'])
  >>> idx
  MultiIndex(levels=[['cobra', 'python'], [2018, 2019]],
- labels=[[1, 1, 0, 0], [0, 1, 0, 1]],
+ codes=[[1, 1, 0, 0], [0, 1, 0, 1]],
  names=['kind', 'year'])
  >>> idx.rename(['species', 'year'])
  MultiIndex(levels=[['cobra', 'python'], [2018, 2019]],
- labels=[[1, 1, 0, 0], [0, 1, 0, 1]],
+ codes=[[1, 1, 0, 0], [0, 1, 0, 1]],
  names=['species', 'year'])
  >>> idx.rename('species')
  Traceback (most recent call last):
@@ -4511,7 +4511,7 @@ def isin(self, values, level=None):
  ... names=('number', 'color'))
  >>> midx
  MultiIndex(levels=[[1, 2, 3], ['blue', 'green', 'red']],
- labels=[[0, 1, 2], [2, 0, 1]],
+ codes=[[0, 1, 2], [2, 0, 1]],
  names=['number', 'color'])
 
  Check whether the strings in the 'color' level of the MultiIndex
@@ -5214,7 +5214,7 @@ def ensure_index_from_sequences(sequences, names=None):
  >>> ensure_index_from_sequences([['a', 'a'], ['a', 'b']],
  names=['L1', 'L2'])
  MultiIndex(levels=[['a'], ['a', 'b']],
- labels=[[0, 0], [0, 1]],
+ codes=[[0, 0], [0, 1]],
  names=['L1', 'L2'])
 
  See Also
@@ -5255,7 +5255,7 @@ def ensure_index(index_like, copy=False):
 
  >>> ensure_index([['a', 'a'], ['b', 'c']])
  MultiIndex(levels=[['a'], ['b', 'c']],
- labels=[[0, 0], [0, 1]])
+ codes=[[0, 0], [0, 1]])
 
  See Also
  --------

pandas/core/indexes/multi.py

@@ -190,8 +190,8 @@ class MultiIndex(Index):
  >>> arrays = [[1, 1, 2, 2], ['red', 'blue', 'red', 'blue']]
  >>> pd.MultiIndex.from_arrays(arrays, names=('number', 'color'))
  MultiIndex(levels=[[1, 2], ['blue', 'red']],
- labels=[[0, 0, 1, 1], [1, 0, 1, 0]],
- names=['number', 'color'])
+  codes=[[0, 0, 1, 1], [1, 0, 1, 0]],
+  names=['number', 'color'])
 
  See further examples for how to construct a MultiIndex in the doc strings
  of the mentioned helper methods.
@@ -321,7 +321,7 @@ def from_arrays(cls, arrays, sortorder=None, names=None):
  >>> arrays = [[1, 1, 2, 2], ['red', 'blue', 'red', 'blue']]
  >>> pd.MultiIndex.from_arrays(arrays, names=('number', 'color'))
  MultiIndex(levels=[[1, 2], ['blue', 'red']],
- labels=[[0, 0, 1, 1], [1, 0, 1, 0]],
+ codes=[[0, 0, 1, 1], [1, 0, 1, 0]],
  names=['number', 'color'])
  """
  if not is_list_like(arrays):
@@ -376,7 +376,7 @@ def from_tuples(cls, tuples, sortorder=None, names=None):
  ... (2, u'red'), (2, u'blue')]
  >>> pd.MultiIndex.from_tuples(tuples, names=('number', 'color'))
  MultiIndex(levels=[[1, 2], ['blue', 'red']],
- labels=[[0, 0, 1, 1], [1, 0, 1, 0]],
+ codes=[[0, 0, 1, 1], [1, 0, 1, 0]],
  names=['number', 'color'])
  """
  if not is_list_like(tuples):
@@ -433,7 +433,7 @@ def from_product(cls, iterables, sortorder=None, names=None):
  >>> pd.MultiIndex.from_product([numbers, colors],
  ... names=['number', 'color'])
  MultiIndex(levels=[[0, 1, 2], ['green', 'purple']],
- labels=[[0, 0, 1, 1, 2, 2], [0, 1, 0, 1, 0, 1]],
+ codes=[[0, 0, 1, 1, 2, 2], [0, 1, 0, 1, 0, 1]],
  names=['number', 'color'])
  """
  from pandas.core.arrays.categorical import _factorize_from_iterables
@@ -493,14 +493,14 @@ def from_frame(cls, df, sortorder=None, names=None):
 
  >>> pd.MultiIndex.from_frame(df)
  MultiIndex(levels=[['HI', 'NJ'], ['Precip', 'Temp']],
- labels=[[0, 0, 1, 1], [1, 0, 1, 0]],
+ codes=[[0, 0, 1, 1], [1, 0, 1, 0]],
  names=['a', 'b'])
 
  Using explicit names, instead of the column names
 
  >>> pd.MultiIndex.from_frame(df, names=['state', 'observation'])
  MultiIndex(levels=[['HI', 'NJ'], ['Precip', 'Temp']],
- labels=[[0, 0, 1, 1], [1, 0, 1, 0]],
+ codes=[[0, 0, 1, 1], [1, 0, 1, 0]],
  names=['state', 'observation'])
  """
  if not isinstance(df, ABCDataFrame):
@@ -619,19 +619,19 @@ def set_levels(self, levels, level=None, inplace=False,
  names=['foo', 'bar'])
  >>> idx.set_levels([['a','b'], [1,2]])
  MultiIndex(levels=[[u'a', u'b'], [1, 2]],
- labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
+ codes=[[0, 0, 1, 1], [0, 1, 0, 1]],
  names=[u'foo', u'bar'])
  >>> idx.set_levels(['a','b'], level=0)
  MultiIndex(levels=[[u'a', u'b'], [u'one', u'two']],
- labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
+ codes=[[0, 0, 1, 1], [0, 1, 0, 1]],
  names=[u'foo', u'bar'])
  >>> idx.set_levels(['a','b'], level='bar')
  MultiIndex(levels=[[1, 2], [u'a', u'b']],
- labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
+ codes=[[0, 0, 1, 1], [0, 1, 0, 1]],
  names=[u'foo', u'bar'])
  >>> idx.set_levels([['a','b'], [1,2]], level=[0,1])
  MultiIndex(levels=[[u'a', u'b'], [1, 2]],
- labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
+ codes=[[0, 0, 1, 1], [0, 1, 0, 1]],
  names=[u'foo', u'bar'])
  """
  if is_list_like(levels) and not isinstance(levels, Index):
@@ -738,19 +738,19 @@ def set_codes(self, codes, level=None, inplace=False,
  names=['foo', 'bar'])
  >>> idx.set_codes([[1,0,1,0], [0,0,1,1]])
  MultiIndex(levels=[[1, 2], [u'one', u'two']],
- labels=[[1, 0, 1, 0], [0, 0, 1, 1]],
+ codes=[[1, 0, 1, 0], [0, 0, 1, 1]],
  names=[u'foo', u'bar'])
  >>> idx.set_codes([1,0,1,0], level=0)
  MultiIndex(levels=[[1, 2], [u'one', u'two']],
- labels=[[1, 0, 1, 0], [0, 1, 0, 1]],
+ codes=[[1, 0, 1, 0], [0, 1, 0, 1]],
  names=[u'foo', u'bar'])
  >>> idx.set_codes([0,0,1,1], level='bar')
  MultiIndex(levels=[[1, 2], [u'one', u'two']],
- labels=[[0, 0, 1, 1], [0, 0, 1, 1]],
+ codes=[[0, 0, 1, 1], [0, 0, 1, 1]],
  names=[u'foo', u'bar'])
  >>> idx.set_codes([[1,0,1,0], [0,0,1,1]], level=[0,1])
  MultiIndex(levels=[[1, 2], [u'one', u'two']],
- labels=[[1, 0, 1, 0], [0, 0, 1, 1]],
+ codes=[[1, 0, 1, 0], [0, 0, 1, 1]],
  names=[u'foo', u'bar'])
  """
  if level is not None and not is_list_like(level):
@@ -909,8 +909,8 @@ def _format_attrs(self):
  attrs = [
  ('levels', ibase.default_pprint(self._levels,
  max_seq_items=False)),
- ('labels', ibase.default_pprint(self._codes,
-  max_seq_items=False))]
+ ('codes', ibase.default_pprint(self._codes,
+ max_seq_items=False))]
  if com._any_not_none(*self.names):
  attrs.append(('names', ibase.default_pprint(self.names)))
  if self.sortorder is not None:
@@ -1509,8 +1509,8 @@ def to_hierarchical(self, n_repeat, n_shuffle=1):
  (2, u'one'), (2, u'two')])
  >>> idx.to_hierarchical(3)
  MultiIndex(levels=[[1, 2], [u'one', u'two']],
- labels=[[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1],
-  [0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1]])
+ codes=[[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1],
+ [0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1]])
  """
  levels = self.levels
  codes = [np.repeat(level_codes, n_repeat) for
@@ -1601,11 +1601,11 @@ def _sort_levels_monotonic(self):
  codes=[[0, 0, 1, 1], [0, 1, 0, 1]])
  >>> i
  MultiIndex(levels=[['a', 'b'], ['bb', 'aa']],
- labels=[[0, 0, 1, 1], [0, 1, 0, 1]])
+ codes=[[0, 0, 1, 1], [0, 1, 0, 1]])
 
  >>> i.sort_monotonic()
  MultiIndex(levels=[['a', 'b'], ['aa', 'bb']],
- labels=[[0, 0, 1, 1], [1, 0, 1, 0]])
+ codes=[[0, 0, 1, 1], [1, 0, 1, 0]])
 
  """
 
@@ -1657,18 +1657,18 @@ def remove_unused_levels(self):
  --------
  >>> i = pd.MultiIndex.from_product([range(2), list('ab')])
  MultiIndex(levels=[[0, 1], ['a', 'b']],
- labels=[[0, 0, 1, 1], [0, 1, 0, 1]])
+ codes=[[0, 0, 1, 1], [0, 1, 0, 1]])
 
  >>> i[2:]
  MultiIndex(levels=[[0, 1], ['a', 'b']],
- labels=[[1, 1], [0, 1]])
+ codes=[[1, 1], [0, 1]])
 
  The 0 from the first level is not represented
  and can be removed
 
  >>> i[2:].remove_unused_levels()
  MultiIndex(levels=[[1], ['a', 'b']],
- labels=[[0, 0], [0, 1]])
+ codes=[[0, 0], [0, 1]])
  """
 
  new_levels = []
@@ -1975,10 +1975,10 @@ def swaplevel(self, i=-2, j=-1):
  ... codes=[[0, 0, 1, 1], [0, 1, 0, 1]])
  >>> mi
  MultiIndex(levels=[['a', 'b'], ['bb', 'aa']],
- labels=[[0, 0, 1, 1], [0, 1, 0, 1]])
+  codes=[[0, 0, 1, 1], [0, 1, 0, 1]])
  >>> mi.swaplevel(0, 1)
  MultiIndex(levels=[['bb', 'aa'], ['a', 'b']],
- labels=[[0, 1, 0, 1], [0, 0, 1, 1]])
+  codes=[[0, 1, 0, 1], [0, 0, 1, 1]])
  """
  new_levels = list(self.levels)
  new_codes = list(self.codes)

pandas/core/strings.py

@@ -2473,7 +2473,7 @@ def rsplit(self, pat=None, n=-1, expand=False):
 
  >>> idx.str.partition()
  MultiIndex(levels=[['X', 'Y'], [' '], ['123', '999']],
- labels=[[0, 1], [0, 0], [0, 1]])
+ codes=[[0, 1], [0, 0], [0, 1]])
 
  Or an index with tuples with ``expand=False``:
 

pandas/tests/util/test_assert_index_equal.py

@@ -13,7 +13,7 @@ def test_index_equal_levels_mismatch():
 Index levels are different
 \\[left\\]: 1, Int64Index\\(\\[1, 2, 3\\], dtype='int64'\\)
 \\[right\\]: 2, MultiIndex\\(levels=\\[\\[u?'A', u?'B'\\], \\[1, 2, 3, 4\\]\\],
- labels=\\[\\[0, 0, 1, 1\\], \\[0, 1, 2, 3\\]\\]\\)"""
+ codes=\\[\\[0, 0, 1, 1\\], \\[0, 1, 2, 3\\]\\]\\)"""
 
  idx1 = Index([1, 2, 3])
  idx2 = MultiIndex.from_tuples([("A", 1), ("A", 2),