ARROW-6556: [Python] Handle future removal of pandas SparseDataFrame

python/pyarrow/feather.py

@@ -82,7 +82,8 @@ def __init__(self, dest):
         self.writer.open(dest)
 
     def write(self, df):
-        if isinstance(df, _pandas_api.pd.SparseDataFrame):
+        if (_pandas_api.has_sparse
+                and isinstance(df, _pandas_api.pd.SparseDataFrame)):
             df = df.to_dense()
 
         if not df.columns.is_unique:

python/pyarrow/pandas-shim.pxi

@@ -32,6 +32,7 @@ cdef class _PandasAPIShim(object):
         object _data_frame, _index, _series, _categorical_type
         object _datetimetz_type, _extension_array
         object _array_like_types
+        bint has_sparse
 
     def __init__(self):
         self._tried_importing_pandas = False
@@ -81,6 +82,12 @@ cdef class _PandasAPIShim(object):
         self._datetimetz_type = DatetimeTZDtype
         self._have_pandas = True
 
+        try:
+            from pandas import SparseDataFrame
+            self.has_sparse = True
+        except ImportError:
+            self.has_sparse = False
+
     cdef inline _check_import(self, bint raise_=True):
         if self._tried_importing_pandas:
             if not self._have_pandas and raise_:

python/pyarrow/serialization.py

@@ -163,7 +163,8 @@ def _register_custom_pandas_handlers(context):
     )
 
     def _serialize_pandas_dataframe(obj):
-        if isinstance(obj, pd.SparseDataFrame):
+        if (pdcompat._pandas_api.has_sparse
+                and isinstance(obj, pd.SparseDataFrame)):
             raise NotImplementedError(
                 sparse_type_error_msg.format('SparseDataFrame')
             )
@@ -174,7 +175,8 @@ def _deserialize_pandas_dataframe(data):
         return pdcompat.serialized_dict_to_dataframe(data)
 
     def _serialize_pandas_series(obj):
-        if isinstance(obj, pd.SparseSeries):
+        if (pdcompat._pandas_api.has_sparse
+                and isinstance(obj, pd.SparseSeries)):
             raise NotImplementedError(
                 sparse_type_error_msg.format('SparseSeries')
             )

python/pyarrow/tests/test_feather.py

@@ -515,7 +515,11 @@ def test_filelike_objects(self):
         result = read_feather(buf)
         assert_frame_equal(result, df)
 
+    @pytest.mark.filterwarnings("ignore:Sparse:FutureWarning")
+    @pytest.mark.filterwarnings("ignore:DataFrame.to_sparse:FutureWarning")
     def test_sparse_dataframe(self):
+        if not hasattr(pd, 'SparseDataFrame'):
+            pytest.skip("version of pandas does not support SparseDataFrame")
         # GH #221
         data = {'A': [0, 1, 2],
                 'B': [1, 0, 1]}