tests for GH5873

Author: behzadnouri

doc/source/whatsnew/v0.16.0.txt

@@ -92,7 +92,7 @@ Bug Fixes
 
 
 
-- Bug in ``MultiIndex.has_duplicates`` when having many levels causes an indexer overflow (:issue:`9075`)
+- Bug in ``MultiIndex.has_duplicates`` when having many levels causes an indexer overflow (:issue:`9075`, :issue:`5873`)
 - Bug in ``pivot`` and `unstack`` where ``nan`` values would break index alignment (:issue:`7466`)
 
 

pandas/tests/test_index.py

@@ -33,6 +33,7 @@
 
 import pandas as pd
 from pandas.lib import Timestamp
+from itertools import product
 
 
 class Base(object):
@@ -3525,6 +3526,25 @@ def check(nlevels, with_nulls):
             right = pd.lib.duplicated(mi.values, take_last=take_last)
             tm.assert_array_equal(left, right)
 
+        # GH5873
+        for a in [101, 102]:
+            mi = MultiIndex.from_arrays([[101, a], [3.5, np.nan]])
+            self.assertFalse(mi.has_duplicates)
+            self.assertEqual(mi.get_duplicates(), [])
+            self.assert_array_equal(mi.duplicated(), np.zeros(2, dtype='bool'))
+
+        for n in range(1, 6):  # 1st level shape
+            for m in range(1, 5):  # 2nd level shape
+                # all possible unique combinations, including nan
+                lab = product(range(-1, n), range(-1, m))
+                mi = MultiIndex(levels=[list('abcde')[:n], list('WXYZ')[:m]],
+                                labels=np.random.permutation(list(lab)).T)
+                self.assertEqual(len(mi), (n + 1) * (m + 1))
+                self.assertFalse(mi.has_duplicates)
+                self.assertEqual(mi.get_duplicates(), [])
+                self.assert_array_equal(mi.duplicated(),
+                                        np.zeros(len(mi), dtype='bool'))
+
     def test_tolist(self):
         result = self.index.tolist()
         exp = list(self.index.values)

pandas/tests/test_series.py

@@ -5884,6 +5884,24 @@ def test_unstack(self):
         unstacked = s.unstack(0)
         assert_frame_equal(unstacked, expected)
 
+        # GH5873
+        idx = pd.MultiIndex.from_arrays([[101, 102], [3.5, np.nan]])
+        ts = pd.Series([1,2], index=idx)
+        left = ts.unstack()
+        left.columns = left.columns.astype('float64')
+        right = DataFrame([[nan, 1], [2, nan]], index=[101, 102],
+                          columns=[nan, 3.5])
+        assert_frame_equal(left, right)
+
+        idx = pd.MultiIndex.from_arrays([['cat', 'cat', 'cat', 'dog', 'dog'],
+                ['a', 'a', 'b', 'a', 'b'], [1, 2, 1, 1, np.nan]])
+        ts = pd.Series([1.0, 1.1, 1.2, 1.3, 1.4], index=idx)
+        right = DataFrame([[1.0, 1.3], [1.1, nan], [nan, 1.4], [1.2, nan]],
+                          columns=['cat', 'dog'])
+        tpls = [('a', 1), ('a', 2), ('b', nan), ('b', 1)]
+        right.index = pd.MultiIndex.from_tuples(tpls)
+        assert_frame_equal(ts.unstack(level=0), right)
+
     def test_sortlevel(self):
         mi = MultiIndex.from_tuples([[1, 1, 3], [1, 1, 1]], names=list('ABC'))
         s = Series([1, 2], mi)