fix dtype of index variables created from Index

Author: benbovy

xarray/core/indexes.py

@@ -169,7 +169,7 @@ def from_variables(cls, variables: Mapping[Hashable, "Variable"]):
 
         obj = cls(var.data, dim)
 
-        data = PandasIndexingAdapter(obj.index)
+        data = PandasIndexingAdapter(obj.index, dtype=var.dtype)
         index_var = IndexVariable(
             dim, data, attrs=var.attrs, encoding=var.encoding, fastpath=True
         )
@@ -314,12 +314,15 @@ def from_variables(cls, variables: Mapping[Hashable, "Variable"]):
 
     @classmethod
     def from_pandas_index(cls, index: pd.MultiIndex, dim: Hashable):
-        levels = [
-            name if name is not None else f"{dim}_level_{i}"
-            for i, name in enumerate(index.names)
-        ]
-        index = index.rename(levels)
-        index_vars = _create_variables_from_multiindex(index, dim)
+        level_meta = {}
+        for i, idx in enumerate(index.levels):
+            name = idx.name or f"{dim}_level_{i}"
+            level_meta[name] = {"dtype": idx.dtype}
+
+        index = index.rename(level_meta.keys())
+        index_vars = _create_variables_from_multiindex(
+            index, dim, level_meta=level_meta
+        )
         return cls(index, dim), index_vars
 
     def query(self, labels, method=None, tolerance=None):

xarray/tests/test_indexes.py

@@ -28,12 +28,15 @@ def test_constructor(self):
         assert index.dim == "x"
 
     def test_from_variables(self):
+        # pandas has only Float64Index but variable dtype should be preserved
+        data = np.array([1.1, 2.2, 3.3], dtype=np.float32)
         var = xr.Variable(
-            "x", [1, 2, 3], attrs={"unit": "m"}, encoding={"dtype": np.int32}
+            "x", data, attrs={"unit": "m"}, encoding={"dtype": np.float64}
         )
 
         index, index_vars = PandasIndex.from_variables({"x": var})
         xr.testing.assert_identical(var.to_index_variable(), index_vars["x"])
+        assert index_vars["x"].dtype == var.dtype
         assert index.dim == "x"
         assert index.index.equals(index_vars["x"].to_index())
 
@@ -166,16 +169,20 @@ def test_from_variables(self):
             PandasMultiIndex.from_variables({"level1": v_level1, "level3": v_level3})
 
     def test_from_pandas_index(self):
-        pd_idx = pd.MultiIndex.from_arrays([[1, 2, 3], [4, 5, 6]], names=("foo", "bar"))
+        foo_data = np.array([0, 0, 1], dtype="int")
+        bar_data = np.array([1.1, 1.2, 1.3], dtype="float64")
+        pd_idx = pd.MultiIndex.from_arrays([foo_data, bar_data], names=("foo", "bar"))
 
         index, index_vars = PandasMultiIndex.from_pandas_index(pd_idx, "x")
 
         assert index.dim == "x"
-        assert index.index is pd_idx
+        assert index.index.equals(pd_idx)
         assert index.index.names == ("foo", "bar")
         xr.testing.assert_identical(index_vars["x"], IndexVariable("x", pd_idx))
-        xr.testing.assert_identical(index_vars["foo"], IndexVariable("x", [1, 2, 3]))
-        xr.testing.assert_identical(index_vars["bar"], IndexVariable("x", [4, 5, 6]))
+        xr.testing.assert_identical(index_vars["foo"], IndexVariable("x", foo_data))
+        xr.testing.assert_identical(index_vars["bar"], IndexVariable("x", bar_data))
+        assert index_vars["foo"].dtype == foo_data.dtype
+        assert index_vars["bar"].dtype == bar_data.dtype
 
     def test_query(self):
         index = PandasMultiIndex(