rather insidious issue with taking from a uint64 array with missing values :>

were being promoted to floats

Author: jreback

.gitignore

@@ -19,6 +19,7 @@
 .noseids
 .ipynb_checkpoints
 .tags
+.cache/
 
 # Compiled source #
 ###################

pandas/tests/frame/test_reshape.py

@@ -629,7 +629,6 @@ def verify(df):
                           names=[None, 'B'])
 
         right = DataFrame(vals, columns=cols, index=idx)
-        import pdb; pdb.set_trace()
         assert_frame_equal(left, right)
 
         # GH4862

pandas/tools/hashing.py

@@ -137,7 +137,7 @@ def hash_tuples(vals, encoding='utf8', hash_key=None):
         is_tuple = True
     elif not is_list_like(vals):
         raise TypeError("must be convertible to a list-of-tuples")
-    import pdb; pdb.set_trace()
+
     if not isinstance(vals, MultiIndex):
         vals = MultiIndex.from_tuples(vals)
 

pandas/tools/tests/test_hashing.py

@@ -152,6 +152,17 @@ def test_categorical_consistency(self):
                 tm.assert_series_equal(h1, h2)
                 tm.assert_series_equal(h1, h3)
 
+    def test_categorical_with_nan_consistency(self):
+        c = pd.Categorical.from_codes(
+            [-1, 0, 1, 2, 3, 4],
+            categories=pd.date_range('2012-01-01', periods=5, name='B'))
+        expected = hash_array(c, categorize=False)
+        c = pd.Categorical.from_codes(
+            [0],
+            categories=[pd.Timestamp('2012-01-01')])
+        result = hash_array(c, categorize=False)
+        assert result.item() in expected
+
     def test_pandas_errors(self):
 
         for obj in [pd.Timestamp('20130101'), tm.makePanel()]:

pandas/types/cast.py

@@ -12,7 +12,8 @@
                      is_datetime64tz_dtype, is_datetime64_dtype,
                      is_timedelta64_dtype, is_dtype_equal,
                      is_float_dtype, is_complex_dtype,
-                     is_integer_dtype, is_datetime_or_timedelta_dtype,
+                     is_integer_dtype, is_unsigned_integer_dtype,
+                     is_datetime_or_timedelta_dtype,
                      is_bool_dtype, is_scalar,
                      _string_dtypes,
                      _coerce_to_dtype,
@@ -265,6 +266,9 @@ def _maybe_promote(dtype, fill_value=np.nan):
     elif is_datetimetz(dtype):
         if isnull(fill_value):
             fill_value = iNaT
+    elif is_unsigned_integer_dtype(dtype):
+        if isnull(fill_value):
+            fill_value = np.iinfo(np.uint64).max
     elif is_float(fill_value):
         if issubclass(dtype.type, np.bool_):
             dtype = np.object_