Improve MultiIndex repr str

Author: tp

doc/source/whatsnew/v0.23.1.txt

@@ -15,6 +15,36 @@ and bug fixes. We recommend that all users upgrade to this version.
 New features
 ~~~~~~~~~~~~
 
+.. _whatsnew_0231.enhancements.new_multi_index_repr_:
+
+MultiIndex now has limits on many levels/labels are shown when printed
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Outputting a :class:`MultiIndex` used to print all level/label of the
+multiindex. This could be a problem for large indices as the output could be
+slow to print and make the console output difficult to navigate.
+
+Outputting of ``MultiIndex`` instances now has limits to the number of levels
+and labels shown ((:issue:`21145`):
+
+.. ipython:: python
+
+ index1=range(1000)
+ pd.MultiIndex.from_arrays([index1, index1])
+
+Previously all 1000 index rows would have been shown.
+
+For smaller number of values, all values will still be shown:
+
+.. ipython:: python
+
+ index1=range(30)
+ pd.MultiIndex.from_arrays([index1, index1])
+ index1=range(2)
+ pd.MultiIndex.from_arrays([index1, index1])
+
+You can change the cutoff point for when all values are shown in the outputs
+by changing :attr:`options.display.max_seq_items` (default is 100).
 
 .. _whatsnew_0231.deprecations:
 

pandas/core/indexes/multi.py

@@ -7,7 +7,7 @@
 import numpy as np
 from pandas._libs import algos as libalgos, index as libindex, lib, Timestamp
 
-from pandas.compat import range, zip, lrange, lzip, map
+from pandas.compat import range, zip, lrange, lzip, map, u
 from pandas.compat.numpy import function as nv
 from pandas import compat
 
@@ -609,11 +609,28 @@ def _format_attrs(self):
  """
  Return a list of tuples of the (attr,formatted_value)
  """
+ def to_string_helper(obj, attr_name):
+ """converts obj.attr_name to a string.
+ """
+ indices = getattr(obj, attr_name)
+ if attr_name == 'labels':
+ # self.labels is a list of FrozenNDArray, Index._format_data
+ # expects a pd.Index
+ indices = [Index(i) for i in indices]
+
+ _name = u("{}({}=").format(obj.__class__.__name__, attr_name)
+ attr_string = [idx._format_data(name=_name)
+ for idx in indices]
+ attr_string = u("").join(attr_string)
+ if attr_string.endswith(u(", ")): # else [1, 2, ], want [1, 2]
+ attr_string = attr_string[:-2]
+
+ return u("[{}]").format(attr_string)
+
  attrs = [
- ('levels', ibase.default_pprint(self._levels,
- max_seq_items=False)),
- ('labels', ibase.default_pprint(self._labels,
- max_seq_items=False))]
+ ('levels', to_string_helper(self, attr_name='levels')),
+ ('labels', to_string_helper(self, attr_name='labels')),
+ ]
  if com._any_not_none(*self.names):
  attrs.append(('names', ibase.default_pprint(self.names)))
  if self.sortorder is not None:

pandas/tests/indexes/test_multi.py

@@ -3279,3 +3279,78 @@ def test_duplicate_multiindex_labels(self):
  with pytest.raises(ValueError):
  ind.set_levels([['A', 'B', 'A', 'A', 'B'], [2, 1, 3, -2, 5]],
  inplace=True)
+
+ def test_repr(self):
+ # GH21145
+
+ # no items
+ idx1, idx2 = range(0), []
+ idx = pd.MultiIndex.from_arrays([idx1, idx2])
+ expected = """\
+MultiIndex(levels=[[], []],
+ labels=[[], []])"""
+ assert repr(idx) == expected
+
+ # two items
+ idx1, idx2 = range(2), ['a', 'b']
+ idx = MultiIndex.from_arrays([idx1, idx2])
+ expected = """\
+MultiIndex(levels=[[0, 1], ['a', 'b']],
+ labels=[[0, 1], [0, 1]])"""
+ assert repr(idx) == expected
+
+ # 100 items
+ idx1, idx2 = range(100), range(100)
+ idx = pd.MultiIndex.from_arrays([idx1, idx2])
+ expected = """\
+MultiIndex(levels=[[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
+ 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
+ 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
+ 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+ 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
+ 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
+ 90, 91, 92, 93, 94, 95, 96, 97, 98, 99],
+ [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
+ 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
+ 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
+ 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+ 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
+ 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
+ 90, 91, 92, 93, 94, 95, 96, 97, 98, 99],
+ ],
+ labels=[[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
+ 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
+ 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
+ 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+ 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
+ 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
+ 90, 91, 92, 93, 94, 95, 96, 97, 98, 99],
+ [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
+ 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
+ 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
+ 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+ 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
+ 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
+ 90, 91, 92, 93, 94, 95, 96, 97, 98, 99],
+ ])"""
+ assert repr(idx) == expected
+
+ # 1000 items
+ idx1, idx2 = range(1000), range(1000)
+ idx = pd.MultiIndex.from_arrays([idx1, idx2])
+ expected = """\
+MultiIndex(levels=[[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
+ ...
+ 990, 991, 992, 993, 994, 995, 996, 997, 998, 999],
+ [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
+ ...
+ 990, 991, 992, 993, 994, 995, 996, 997, 998, 999],
+ ],
+ labels=[[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
+ ...
+ 990, 991, 992, 993, 994, 995, 996, 997, 998, 999],
+ [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
+ ...
+ 990, 991, 992, 993, 994, 995, 996, 997, 998, 999],
+ ])"""
+ assert repr(idx) == expected