BUG: fix initialization of Series with dict containing NaN key

closes pandas-dev#18480

Author: toobaz

doc/source/whatsnew/v0.22.0.txt

@@ -205,4 +205,5 @@ Other
 
 - Improved error message when attempting to use a Python keyword as an identifier in a numexpr query (:issue:`18221`)
 - Fixed a bug where creating a Series from an array that contains both tz-naive and tz-aware values will result in a Series whose dtype is tz-aware instead of object (:issue:`16406`)
+- Fixed initialization of Series from dict containing NaN as key (:issue:`18480`)
 -

pandas/core/series.py

@@ -198,18 +198,42 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
                     data = data.reindex(index, copy=copy)
                 data = data._data
             elif isinstance(data, dict):
-                if index is None:
-                    if isinstance(data, OrderedDict):
-                        index = Index(data)
+                if data:
+                    keys, values = zip(*compat.iteritems(data))
+                    keys = Index(list(keys), tupleize_cols=True)
+                    a_values = np.empty(len(values), dtype='object')
+                    # Avoid interpreting list-like elements as 2nd dimension:
+                    for idx, v in enumerate(values):
+                        a_values[idx] = v
+                    try:
+                        values = lib.maybe_convert_objects(a_values)
+                    except:
+                        values = a_values
+                    if index is None:
+                        if isinstance(data, OrderedDict):
+                            order = np.arange(len(keys))
+                        else:
+                            try:
+                                order = keys.argsort()
+                            except TypeError:
+                                order = np.arange(len(keys))
+                        index = keys[order]
                     else:
-                        index = Index(_try_sort(data))
-
-                try:
-                    data = index._get_values_from_dict(data)
-                except TypeError:
-                    data = ([data.get(i, np.nan) for i in index]
-                            if data else np.nan)
-
+                        locs = index.get_indexer(keys)
+                        order = - np.ones(len(index), dtype=int)
+                        order[locs] = np.arange(len(keys))
+                    data = values[order]
+                    nan_idxs = np.where(order == -1)[0]
+                    if len(nan_idxs):
+                        if is_integer_dtype(data):
+                            data = data.astype(float)
+                        data[nan_idxs] = np.nan
+                    if any([is_list_like(item) for item in data]):
+                        data = list(data)
+                else:
+                    if index is None:
+                        index = Index([])
+                    data = np.array([np.nan] * len(index))
             elif isinstance(data, SingleBlockManager):
                 if index is None:
                     index = data.index

pandas/tests/series/test_constructors.py

@@ -625,6 +625,18 @@ def test_constructor_dict(self):
         expected.iloc[1] = 1
         assert_series_equal(result, expected)
 
+        # GH 18480 - NaN key
+        d = {1: 'a', 2: 'b', np.nan: 'c'}
+        result = Series(d).sort_index()
+        expected = Series(['a', 'b', 'c'], index=[1, 2, np.nan])
+        assert_series_equal(result, expected)
+
+        # Different NaNs:
+        d = {1: 'a', 2: 'b', float('nan'): 'c', float('nan'): 'd'}
+        result = Series(d).sort_values()
+        expected = Series(['a', 'b', 'c', 'd'], index=[1, 2, np.nan, np.nan])
+        assert_series_equal(result, expected)
+
     def test_constructor_dict_datetime64_index(self):
         # GH 9456