round-trip categorical pyarrow

Author: MarcoGorelli

pandas/core/interchange/from_dataframe.py

@@ -7,7 +7,6 @@
 import numpy as np
 
 import pandas as pd
-from pandas.core.interchange.column import PandasColumn
 from pandas.core.interchange.dataframe_protocol import (
     Buffer,
     Column,
@@ -182,7 +181,7 @@ def categorical_column_to_series(col: Column) -> tuple[pd.Series, Any]:
 
     cat_column = categorical["categories"]
     # for mypy/pyright
-    assert isinstance(cat_column, PandasColumn), "categories must be a PandasColumn"
+    assert hasattr(cat_column, "_col"), "categories must have a `.col` attribute"
     categories = np.array(cat_column._col)
     buffers = col.get_buffers()
 

pandas/tests/interchange/test_impl.py

@@ -2,6 +2,7 @@
 import random
 
 import numpy as np
+import pyarrow as pa
 import pytest
 
 from pandas._libs.tslibs import iNaT
@@ -74,6 +75,19 @@ def test_categorical_dtype(data):
     tm.assert_frame_equal(df, from_dataframe(df.__dataframe__()))
 
 
+def test_categorical_pyarrow():
+    # GH 49889
+    arr = ["Mon", "Tue", "Mon", "Wed", "Mon", "Thu", "Fri", "Sat", "Sun"]
+    table = pa.table({"weekday": pa.array(arr).dictionary_encode()})
+    exchange_df = table.__dataframe__()
+    result = from_dataframe(exchange_df)
+    weekday = pd.Categorical(
+        arr, categories=["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"]
+    )
+    expected = pd.DataFrame({"weekday": weekday})
+    tm.assert_frame_equal(result, expected)
+
+
 @pytest.mark.parametrize(
     "data", [int_data, uint_data, float_data, bool_data, datetime_data]
 )