ENH: Better string representation for MultiIndex

[jtratner]

Fixes #3347.

All interested parties are invited to submit test cases. cc @y-p @hayd

---

Examples:

In [1]: import pandas as pd

In [2]: pd.MultiIndex.from_arrays([[1, 1, 1, 1], [1, 3, 5, 7], [9, 9, 1, 1]])
Out[2]:
MultiIndex(levels=[[1], [1, 3, 5, 7], [1, 9]]
           labels=[[0, 0, 0, 0], [0, 1, 2, 3], [1, 1, 0, 0]])

In [3]: mi = _

In [4]: mi.names = list('abc')

In [5]: print mi
a  b  c
1  1  9
   3  9
   5  1
   7  1

And with too many rows:

In [10]: pd.set_option('display.max_rows', 15)

In [11]: lst1 = [1] * 3 + [2] * 5 + [3] * 2

In [12]: lst1
Out[12]: [1, 1, 1, 2, 2, 2, 2, 2, 3, 3]

In [13]: lst2 = ['a'] * 6 + ['b'] * 3 + ['c'] * 1

In [14]: lst2
Out[14]: ['a', 'a', 'a', 'a', 'a', 'a', 'b', 'b', 'b', 'c']

In [15]: mi = pd.MultiIndex.from_arrays([lst1 * 10, lst2 * 10, range(100)]); mi
Out[15]:
MultiIndex(levels=[[1, 2, 3], [u'a', u'b', u'c'], [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, 0, 0, 1, 1, 1, 1, 1, 2, 2, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2], [0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2], [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]])

In [16]: mi = _

In [17]: print mi

1  a  0
      1
      2
2  a  3
      4
      5
  ...
2  a  93
      94
      95
   b  96
      97
3  b  98
   c  99

Not sure how to handle too wide -- wrap? format() doesn't try to sparsify after a column with values everywhere.

In [19]: mi = pd.MultiIndex.from_arrays([lst1 * 10, lst2 * 10, range(100)] * 10)
In [20]: print mi

1  a  0   1  a  0   1  a  0   1  a  0   1  a  0   1  a  0   1  a  0   1  a  0   1  a  0   1  a  0
      1   1  a  1   1  a  1   1  a  1   1  a  1   1  a  1   1  a  1   1  a  1   1  a  1   1  a  1
      2   1  a  2   1  a  2   1  a  2   1  a  2   1  a  2   1  a  2   1  a  2   1  a  2   1  a  2
2  a  3   2  a  3   2  a  3   2  a  3   2  a  3   2  a  3   2  a  3   2  a  3   2  a  3   2  a  3
      4   2  a  4   2  a  4   2  a  4   2  a  4   2  a  4   2  a  4   2  a  4   2  a  4   2  a  4
      5   2  a  5   2  a  5   2  a  5   2  a  5   2  a  5   2  a  5   2  a  5   2  a  5   2  a  5
                                               ...
2  a  93  2  a  93  2  a  93  2  a  93  2  a  93  2  a  93  2  a  93  2  a  93  2  a  93  2  a  93
      94  2  a  94  2  a  94  2  a  94  2  a  94  2  a  94  2  a  94  2  a  94  2  a  94  2  a  94
      95  2  a  95  2  a  95  2  a  95  2  a  95  2  a  95  2  a  95  2  a  95  2  a  95  2  a  95
   b  96  2  b  96  2  b  96  2  b  96  2  b  96  2  b  96  2  b  96  2  b  96  2  b  96  2  b  96
      97  2  b  97  2  b  97  2  b  97  2  b  97  2  b  97  2  b  97  2  b  97  2  b  97  2  b  97
3  b  98  3  b  98  3  b  98  3  b  98  3  b  98  3  b  98  3  b  98  3  b  98  3  b  98  3  b  98
   c  99  3  c  99  3  c  99  3  c  99  3  c  99  3  c  99  3  c  99  3  c  99  3  c  99  3  c  99

In [9]: labels = [('foo', '2012-07-26T00:00:00', 'b5c2700'),
   ...: ('foo', '2012-08-06T00:00:00', '900b2ca'),
   ...: ('foo', '2012-08-15T00:00:00', '07f1ce0'),
   ...: ('foo', '2012-09-25T00:00:00', '5c93e83'),
   ...: ('foo', '2012-09-25T00:00:00', '9345bba')]

In [10]: print pd.MultiIndex.from_tuples(labels)

foo  2012-07-26T00:00:00  b5c2700
     2012-08-06T00:00:00  900b2ca
     2012-08-15T00:00:00  07f1ce0
     2012-09-25T00:00:00  5c93e83
                          9345bba

[cpcloud]

+1 ... the current MultiIndex repr always makes me feel a bit strange

[jreback]

looks ok