BUG: .sparse.to_coo() with numeric col index without a 0 (pandas-dev#38567)

Author: mzeitlin11

doc/source/whatsnew/v1.3.0.rst

@@ -273,6 +273,7 @@ Reshaping
 Sparse
 ^^^^^^
 
+- Bug in :meth:`DataFrame.sparse.to_coo` raising ``KeyError`` with columns that are a numeric :class:`Index` without a 0 (:issue:`18414`)
 -
 -
 

pandas/core/arrays/sparse/accessor.py

@@ -329,7 +329,7 @@ def to_coo(self):
         import_optional_dependency("scipy")
         from scipy.sparse import coo_matrix
 
-        dtype = find_common_type(self._parent.dtypes)
+        dtype = find_common_type(self._parent.dtypes.to_list())
         if isinstance(dtype, SparseDtype):
             dtype = dtype.subtype
 

pandas/tests/arrays/sparse/test_accessor.py

@@ -68,11 +68,14 @@ def test_from_spmatrix_columns(self, columns):
         expected = pd.DataFrame(mat.toarray(), columns=columns).astype(dtype)
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize("colnames", [("A", "B"), (1, 2), (1, pd.NA), (0.1, 0.2)])
     @td.skip_if_no_scipy
-    def test_to_coo(self):
+    def test_to_coo(self, colnames):
         import scipy.sparse
 
-        df = pd.DataFrame({"A": [0, 1, 0], "B": [1, 0, 0]}, dtype="Sparse[int64, 0]")
+        df = pd.DataFrame(
+            {colnames[0]: [0, 1, 0], colnames[1]: [1, 0, 0]}, dtype="Sparse[int64, 0]"
+        )
         result = df.sparse.to_coo()
         expected = scipy.sparse.coo_matrix(np.asarray(df))
         assert (result != expected).nnz == 0