Doing adjustments as per @jreback requests

Author: Carlos Souza

pandas/sparse/frame.py

@@ -142,7 +142,7 @@ def _init_dict(self, data, index, columns, dtype=None):
 
         sp_maker = lambda x: SparseArray(x, kind=self._default_kind,
                                          fill_value=self._default_fill_value,
-                                         copy=True)
+                                         copy=True, dtype=dtype)
         sdict = DataFrame()
         for k, v in compat.iteritems(data):
             if isinstance(v, Series):
@@ -159,7 +159,7 @@ def _init_dict(self, data, index, columns, dtype=None):
                     v = [v.get(i, nan) for i in index]
 
                 v = sp_maker(v)
-            sdict[k] = v.astype(np.dtype(dtype)) if dtype is not None else v
+            sdict[k] = v
 
         # TODO: figure out how to handle this case, all nan's?
         # add in any other columns we want to have (completeness)

pandas/tests/sparse/test_frame.py

@@ -236,6 +236,18 @@ def test_constructor_nan_dataframe(self):
                                       dtype=float)
         tm.assert_sp_frame_equal(result, expected)
 
+    def test_type_coercion_at_construction(self):
+        # GH 15682
+        result = pd.SparseDataFrame(
+            {'a': [1, 0, 0], 'b': [0, 1, 0], 'c': [0, 0, 1]}, dtype='uint8',
+            default_fill_value=0)
+        expected = pd.SparseDataFrame(
+            {'a': pd.SparseSeries([1, 0, 0], dtype='uint8'),
+             'b': pd.SparseSeries([0, 1, 0], dtype='uint8'),
+             'c': pd.SparseSeries([0, 0, 1], dtype='uint8')},
+            default_fill_value=0)
+        tm.assert_sp_frame_equal(result, expected)
+
     def test_dtypes(self):
         df = DataFrame(np.random.randn(10000, 4))
         df.loc[:9998] = np.nan
@@ -756,8 +768,8 @@ def test_sparse_frame_fillna_limit(self):
 
     def test_rename(self):
         # just check this works
-        renamed = self.frame.rename(index=str)  # noqa
-        renamed = self.frame.rename(
+        rename = self.frame.rename(index=str)  # noqa
+        rename = self.frame.rename(
             columns=lambda x: '%s%d' % (x, len(x)))  # noqa
 
     def test_corr(self):
@@ -1225,6 +1237,7 @@ def test_from_to_scipy_object(spmatrix, fill_value):
 
 
 class TestSparseDataFrameArithmetic(tm.TestCase):
+
     def test_numeric_op_scalar(self):
         df = pd.DataFrame({'A': [nan, nan, 0, 1, ],
                            'B': [0, 1, 2, nan],
@@ -1297,11 +1310,3 @@ def test_numpy_func_call(self):
         for func in funcs:
             getattr(np, func)(self.frame)
 
-    def test_type_coercion_at_construction(self):
-        # GH 15682
-        df = pd.SparseDataFrame(
-            {'a': [1, 0, 0], 'b': [0, 1, 0], 'c': [0, 0, 1]}, dtype='uint8',
-            default_fill_value=0)
-        result = df.dtypes[0]
-        expected = np.dtype('uint8')
-        assert result == expected