BUG: stacking with MultiIndex column with some unused level uniques fails pandas-dev#3170

Author: Chang She

pandas/core/reshape.py

@@ -159,7 +159,7 @@ def get_new_values(self):
             dtype, fill_value = _maybe_promote(values.dtype)
             new_values = np.empty(result_shape, dtype=dtype)
             new_values.fill(fill_value)
- 
+
         new_mask = np.zeros(result_shape, dtype=bool)
 
         # is there a simpler / faster way of doing this?
@@ -508,9 +508,12 @@ def _stack_multi_columns(frame, level=-1, dropna=True):
     levsize = len(level_vals)
     for key in unique_groups:
         loc = this.columns.get_loc(key)
-
+        slice_len = loc.stop - loc.start
         # can make more efficient?
-        if loc.stop - loc.start != levsize:
+
+        if slice_len == 0:
+            continue
+        elif slice_len != levsize:
             chunk = this.ix[:, this.columns[loc]]
             chunk.columns = level_vals.take(chunk.columns.labels[-1])
             value_slice = chunk.reindex(columns=level_vals).values

pandas/tests/test_multilevel.py

@@ -930,6 +930,21 @@ def test_stack_unstack_multiple(self):
         expected = self.ymd.unstack(2).unstack(1).dropna(axis=1, how='all')
         assert_frame_equal(unstacked, expected.ix[:, unstacked.columns])
 
+    def test_stack_multiple_bug(self):
+        """ bug when some uniques are not present in the data #3170"""
+        id_col = ([1] * 3) + ([2] * 3)
+        name = (['a'] * 3) + (['b'] * 3)
+        date = pd.to_datetime(['2013-01-03', '2013-01-04', '2013-01-05'] * 2)
+        var1 = np.random.randint(0, 100, 6)
+        df = DataFrame(dict(ID=id_col, NAME=name, DATE=date, VAR1=var1))
+
+        multi = df.set_index(['DATE', 'ID'])
+        unst = multi.unstack('ID')
+        down = unst.resample('W-THU')
+
+        rs = down.stack('ID') # It works!
+
+
     def test_unstack_multiple_hierarchical(self):
         df = DataFrame(index=[[0, 0, 0, 0, 1, 1, 1, 1],
                               [0, 0, 1, 1, 0, 0, 1, 1],