Fix conversion of multiindexed pandas objects to sparse xarray objects (#4088)

* Fix conversion of multiindexed pandas objects to sparse xarray objects

* lint

* fix whats-new

* fix test

* minor whats-new

Author: dcherian

doc/whats-new.rst

@@ -102,6 +102,8 @@ Bug fixes
 ~~~~~~~~~
 - Support dark mode in VS code (:issue:`4024`)
   By `Keisuke Fujii <https://github.com/fujiisoup>`_.
+- Fix bug when converting multiindexed Pandas objects to sparse xarray objects. (:issue:`4019`)
+  By `Deepak Cherian <https://github.com/dcherian>`_.
 - ``ValueError`` is raised when ``fill_value`` is not a scalar in :py:meth:`full_like`. (:issue:`3977`)
   By `Huite Bootsma <https://github.com/huite>`_.
 - Fix wrong order in converting a ``pd.Series`` with a MultiIndex to ``DataArray``. (:issue:`3951`)

xarray/core/dataset.py

@@ -4537,7 +4537,7 @@ def _set_sparse_data_from_dataframe(
         idx = dataframe.index
         if isinstance(idx, pd.MultiIndex):
             coords = np.stack([np.asarray(code) for code in idx.codes], axis=0)
-            is_sorted = idx.is_lexsorted
+            is_sorted = idx.is_lexsorted()
             shape = tuple(lev.size for lev in idx.levels)
         else:
             coords = np.arange(idx.size).reshape(1, -1)

xarray/tests/test_dataarray.py

@@ -3532,6 +3532,24 @@ def test_from_series_sparse(self):
         actual_sparse.data = actual_sparse.data.todense()
         assert_identical(actual_sparse, actual_dense)
 
+    @requires_sparse
+    def test_from_multiindex_series_sparse(self):
+        # regression test for GH4019
+        import sparse
+
+        idx = pd.MultiIndex.from_product([np.arange(3), np.arange(5)], names=["a", "b"])
+        series = pd.Series(np.random.RandomState(0).random(len(idx)), index=idx).sample(
+            n=5, random_state=3
+        )
+
+        dense = DataArray.from_series(series, sparse=False)
+        expected_coords = sparse.COO.from_numpy(dense.data, np.nan).coords
+
+        actual_sparse = xr.DataArray.from_series(series, sparse=True)
+        actual_coords = actual_sparse.data.coords
+
+        np.testing.assert_equal(actual_coords, expected_coords)
+
     def test_to_and_from_empty_series(self):
         # GH697
         expected = pd.Series([], dtype=np.float64)