BUG: fix parquet roundtrip for Interval dtype with datetime64[ns] subtype (#46034)

Author: jorisvandenbossche

doc/source/whatsnew/v1.5.0.rst

@@ -364,6 +364,7 @@ I/O
 - Bug in :func:`read_csv` not respecting a specified converter to index columns in all cases (:issue:`40589`)
 - Bug in :func:`read_parquet` when ``engine="pyarrow"`` which caused partial write to disk when column of unsupported datatype was passed (:issue:`44914`)
 - Bug in :func:`DataFrame.to_excel` and :class:`ExcelWriter` would raise when writing an empty DataFrame to a ``.ods`` file (:issue:`45793`)
+- Bug in Parquet roundtrip for Interval dtype with ``datetime64[ns]`` subtype (:issue:`45881`)
 
 Period
 ^^^^^^

pandas/core/dtypes/dtypes.py

@@ -1253,16 +1253,18 @@ def __from_arrow__(
 
         results = []
         for arr in chunks:
-            left = np.asarray(arr.storage.field("left"), dtype=self.subtype)
-            right = np.asarray(arr.storage.field("right"), dtype=self.subtype)
-            iarr = IntervalArray.from_arrays(left, right, closed=array.type.closed)
+            if isinstance(arr, pyarrow.ExtensionArray):
+                arr = arr.storage
+            left = np.asarray(arr.field("left"), dtype=self.subtype)
+            right = np.asarray(arr.field("right"), dtype=self.subtype)
+            iarr = IntervalArray.from_arrays(left, right, closed=self.closed)
             results.append(iarr)
 
         if not results:
             return IntervalArray.from_arrays(
                 np.array([], dtype=self.subtype),
                 np.array([], dtype=self.subtype),
-                closed=array.type.closed,
+                closed=self.closed,
             )
         return IntervalArray._concat_same_type(results)
 

pandas/tests/arrays/interval/test_interval.py

@@ -376,3 +376,23 @@ def test_arrow_table_roundtrip_without_metadata(breaks):
     result = table.to_pandas()
     assert isinstance(result["a"].dtype, pd.IntervalDtype)
     tm.assert_frame_equal(result, df)
+
+
+@pyarrow_skip
+def test_from_arrow_from_raw_struct_array():
+    # in case pyarrow lost the Interval extension type (eg on parquet roundtrip
+    # with datetime64[ns] subtype, see GH-45881), still allow conversion
+    # from arrow to IntervalArray
+    import pyarrow as pa
+
+    arr = pa.array([{"left": 0, "right": 1}, {"left": 1, "right": 2}])
+    dtype = pd.IntervalDtype(np.dtype("int64"), closed="neither")
+
+    result = dtype.__from_arrow__(arr)
+    expected = IntervalArray.from_breaks(
+        np.array([0, 1, 2], dtype="int64"), closed="neither"
+    )
+    tm.assert_extension_array_equal(result, expected)
+
+    result = dtype.__from_arrow__(pa.chunked_array([arr]))
+    tm.assert_extension_array_equal(result, expected)

pandas/tests/io/test_parquet.py

@@ -928,15 +928,18 @@ def test_pyarrow_backed_string_array(self, pa, string_storage):
         with pd.option_context("string_storage", string_storage):
             check_round_trip(df, pa, expected=df.astype(f"string[{string_storage}]"))
 
-    @td.skip_if_no("pyarrow")
+    @td.skip_if_no("pyarrow", min_version="2.0.0")
     def test_additional_extension_types(self, pa):
         # test additional ExtensionArrays that are supported through the
         # __arrow_array__ protocol + by defining a custom ExtensionType
         df = pd.DataFrame(
             {
-                # Arrow does not yet support struct in writing to Parquet (ARROW-1644)
-                # "c": pd.arrays.IntervalArray.from_tuples([(0, 1), (1, 2), (3, 4)]),
+                "c": pd.IntervalIndex.from_tuples([(0, 1), (1, 2), (3, 4)]),
                 "d": pd.period_range("2012-01-01", periods=3, freq="D"),
+                # GH-45881 issue with interval with datetime64[ns] subtype
+                "e": pd.IntervalIndex.from_breaks(
+                    pd.date_range("2012-01-01", periods=4, freq="D")
+                ),
             }
         )
         check_round_trip(df, pa)