Preserve sparse dtype when reindexing

 - This is currently broken due to many tests
   relying on possibly broken behaviour.
 - BUG #26123.

Author: Alex Hutton

pandas/core/generic.py

@@ -4502,7 +4502,7 @@ def reindex_axis(self, labels, axis=0, method=None, level=None, copy=True,
                                            fill_value=fill_value, copy=copy)
 
     def _reindex_with_indexers(self, reindexers, fill_value=None, copy=False,
-                               allow_dups=False):
+                               allow_dups=False, preserve_dtype=False):
         """allow_dups indicates an internal call here """
 
         # reindex doing multiple operations on different axes if indicated
@@ -4527,7 +4527,8 @@ def _reindex_with_indexers(self, reindexers, fill_value=None, copy=False,
         if copy and new_data is self._data:
             new_data = new_data.copy()
 
-        return self._constructor(new_data).__finalize__(self)
+        kwargs = {'dtype': self._data.dtype} if preserve_dtype else {}
+        return self._constructor(new_data, **kwargs).__finalize__(self)
 
     def filter(self, items=None, like=None, regex=None, axis=None):
         """

pandas/core/sparse/series.py

@@ -464,10 +464,20 @@ def copy(self, deep=True):
     def reindex(self, index=None, method=None, copy=True, limit=None,
                 **kwargs):
         # TODO: remove?
+        fill_value = kwargs.pop('fill_value', None)
+        if fill_value is None:
+            fill_value = self.fill_value
         return super(SparseSeries, self).reindex(index=index, method=method,
+                                                 fill_value=fill_value,
                                                  copy=copy, limit=limit,
                                                  **kwargs)
 
+    def _reindex_with_indexers(self, *args, **kwargs):
+        return super(SparseSeries, self)._reindex_with_indexers(
+            *args,
+            preserve_dtype=True,
+            **kwargs)
+
     def sparse_reindex(self, new_index):
         """
         Conform sparse values to new SparseIndex

pandas/tests/sparse/series/test_series.py

@@ -12,7 +12,7 @@
 
 import pandas as pd
 from pandas import (
-    DataFrame, Series, SparseDtype, SparseSeries, bdate_range, isna)
+    DataFrame, Series, SparseDtype, SparseSeries, bdate_range)
 from pandas.core.reshape.util import cartesian_product
 import pandas.core.sparse.frame as spf
 from pandas.tests.series.test_api import SharedWithSparse
@@ -309,7 +309,7 @@ def test_constructor_scalar(self):
         sp = SparseSeries(data, np.arange(100))
         sp = sp.reindex(np.arange(200))
         assert (sp.loc[:99] == data).all()
-        assert isna(sp.loc[100:]).all()
+        assert sp.loc[100:].isin((0,)).all()
 
         data = np.nan
         sp = SparseSeries(data, np.arange(100))
@@ -1031,6 +1031,11 @@ def test_memory_usage_deep(self, deep, fill_value):
 
         assert sparse_usage < dense_usage
 
+    @pytest.mark.parametrize('dtype', (np.float32, np.int32, np.bool))
+    def test_resize_preserves_dtype(self, dtype):
+        s = pd.SparseSeries([1, 0], dtype=dtype)
+        assert s.dtype == s.reindex([0, 1, 2]).dtype
+
 
 class TestSparseHandlingMultiIndexes: