jorisvandenbossche commented on code in PR #44720:
URL: https://github.com/apache/arrow/pull/44720#discussion_r1842857876
##########
python/pyarrow/tests/test_pandas.py:
##########
@@ -4411,6 +4412,31 @@ def test_to_pandas_extension_dtypes_mapping():
assert isinstance(result['a'].dtype, pd.PeriodDtype)
+
+def test_to_pandas_extension_dtypes_mapping_complex_type():
+ pa_type = pa.struct(
+ [
+ pa.field("bar", pa.bool_(), nullable=False),
+ pa.field("baz", pa.float32(), nullable=True),
+ ],
+ )
+ pd_type = pd.ArrowDtype(pa_type)
+ schema = pa.schema([pa.field("foo", pa_type)])
+ df0 = pd.DataFrame(
+ [
+ {"foo": {"bar": True, "baz": np.float32(1)}},
+ {"foo": {"bar": True, "baz": None}},
+ ],
+ ).astype({"foo": pd_type})
+
+ # Round trip df0 into df1
+ with io.BytesIO() as stream:
+ df0.to_parquet(stream, schema=schema)
+ stream.seek(0)
+ df1 = pd.read_parquet(stream, dtype_backend="pyarrow")
Review Comment:
The pandas `to_parquet` method essentially just does a `table =
pa.Table.from_pandas(df)` and then writes that to parquet (and `pa.table(df)`
is a shorter less explicit version of that, but you can also use
Table.from_pandas)
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