BUG: assign doesnt cast SparseDataFrame to DataFrame

doc/source/whatsnew/v0.23.0.txt

@@ -491,7 +491,7 @@ Groupby/Resample/Rolling
 Sparse
 ^^^^^^
 
--
+- Bug in :class:`SparseArray` where if a scalar and index are passed in it will coerce to float64 regardless of scalar's dtype. (:issue:`19163`)
 -
 -
 
@@ -508,7 +508,6 @@ Reshaping
 - Bug in :func:`DataFrame.merge` in which merging using ``Index`` objects as vectors raised an Exception (:issue:`19038`)
 - Bug in :func:`DataFrame.stack`, :func:`DataFrame.unstack`, :func:`Series.unstack` which were not returning subclasses (:issue:`15563`)
 - Bug in timezone comparisons, manifesting as a conversion of the index to UTC in ``.concat()`` (:issue:`18523`)
--
 
 Numeric
 ^^^^^^^

pandas/core/sparse/array.py

@@ -27,7 +27,7 @@
     is_scalar, is_dtype_equal)
 from pandas.core.dtypes.cast import (
     maybe_convert_platform, maybe_promote,
-    astype_nansafe, find_common_type)
+    astype_nansafe, find_common_type, infer_dtype_from)
 from pandas.core.dtypes.missing import isna, notna, na_value_for_dtype
 
 import pandas._libs.sparse as splib
@@ -195,7 +195,7 @@ def __new__(cls, data, sparse_index=None, index=None, kind='integer',
                 data = np.nan
             if not is_scalar(data):
                 raise Exception("must only pass scalars with an index ")
-            values = np.empty(len(index), dtype='float64')
+            values = np.empty(len(index), dtype=infer_dtype_from(data)[0])
             values.fill(data)
             data = values
 

pandas/tests/sparse/frame/test_frame.py

@@ -1271,3 +1271,14 @@ def test_quantile_multi(self):
 
         tm.assert_frame_equal(result, dense_expected)
         tm.assert_sp_frame_equal(result, sparse_expected)
+
+    def test_assign_with_sparse_frame(self):
+        # GH 19163
+        df = pd.DataFrame({"a": [1, 2, 3]})
+        res = df.to_sparse(fill_value=False).assign(newcol=False)
+        exp = df.assign(newcol=False).to_sparse(fill_value=False)
+
+        tm.assert_sp_frame_equal(res, exp)
+
+        for column in res.columns:
+            assert type(res[column]) is SparseSeries

pandas/tests/sparse/test_array.py

@@ -113,6 +113,21 @@ def test_constructor_spindex_dtype(self):
         assert arr.dtype == np.int64
         assert arr.fill_value == 0
 
+    @pytest.mark.parametrize('scalar,dtype', [
+        (False, bool),
+        (0.0, 'float64'),
+        (1, 'int64'),
+        ('z', 'object')])
+    def test_scalar_with_index_infer_dtype(self, scalar, dtype):
+        # GH 19163
+        arr = SparseArray(scalar, index=[1, 2, 3], fill_value=scalar)
+        exp = SparseArray([scalar, scalar, scalar], fill_value=scalar)
+
+        tm.assert_sp_array_equal(arr, exp)
+
+        assert arr.dtype == dtype
+        assert exp.dtype == dtype
+
     def test_sparseseries_roundtrip(self):
         # GH 13999
         for kind in ['integer', 'block']: