BUG: workaround for pandas-dev#18485

Author: toobaz

pandas/core/series.py

@@ -200,7 +200,14 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
             elif isinstance(data, dict):
                 if data:
                     keys, values = zip(*compat.iteritems(data))
-                    keys = Index(list(keys), tupleize_cols=True)
+                    # Workaround for #18485 - part 1/3
+                    maybe_mi_keys = Index(list(keys), tupleize_cols=True)
+                    if isinstance(maybe_mi_keys, MultiIndex):
+                        remap_to_mi = True
+                        keys = Index(list(keys), tupleize_cols=False)
+                    else:
+                        remap_to_mi = False
+                        keys = maybe_mi_keys
                     a_values = np.empty(len(values), dtype='object')
                     # Avoid interpreting list-like elements as 2nd dimension:
                     for idx, v in enumerate(values):
@@ -219,7 +226,14 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
                                 order = np.arange(len(keys))
                         index = keys[order]
                     else:
-                        locs = index.get_indexer(keys)
+                        # Workaround for #18485 - part 2/3
+                        remap_to_mi = False
+
+                        def _flatten(idx):
+                            if isinstance(idx, MultiIndex):
+                                return Index(list(idx), tupleize_cols=False)
+                            return idx
+                        locs = _flatten(index).get_indexer(keys)
                         order = - np.ones(len(index), dtype=int)
                         order[locs] = np.arange(len(keys))
                     data = values[order]
@@ -228,6 +242,9 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
                         if is_integer_dtype(data):
                             data = data.astype(float)
                         data[nan_idxs] = np.nan
+                    # Workaround for #18485 - part 3/3
+                    if remap_to_mi:
+                        index = Index(list(index), tupleize_cols=True)
                     if any([is_list_like(item) for item in data]):
                         data = list(data)
                 else: