BUG: pd.api.interchange.from_pandas raises with all-null categorical (#53078)

Co-authored-by: MarcoGorelli <>

Author: MarcoGorelli

doc/source/whatsnew/v2.0.2.rst

@@ -21,6 +21,7 @@ Fixed regressions
 
 Bug fixes
 ~~~~~~~~~
+- Bug in :func:`api.interchange.from_dataframe` was raising ``IndexError`` on empty categorical data (:issue:`53077`)
 - Bug in :func:`api.interchange.from_dataframe` was returning :class:`DataFrame`'s of incorrect sizes when called on slices (:issue:`52824`)
 - Bug in :func:`api.interchange.from_dataframe` was unnecessarily raising on bitmasks (:issue:`49888`)
 - Bug in :func:`to_timedelta` was raising ``ValueError`` with ``pandas.NA`` (:issue:`52909`)

pandas/core/interchange/from_dataframe.py

@@ -202,7 +202,10 @@ def categorical_column_to_series(col: Column) -> tuple[pd.Series, Any]:
 
     # Doing module in order to not get ``IndexError`` for
     # out-of-bounds sentinel values in `codes`
-    values = categories[codes % len(categories)]
+    if len(categories) > 0:
+        values = categories[codes % len(categories)]
+    else:
+        values = codes
 
     cat = pd.Categorical(
         values, categories=categories, ordered=categorical["is_ordered"]

pandas/tests/interchange/test_impl.py

@@ -89,6 +89,18 @@ def test_categorical_pyarrow():
     tm.assert_frame_equal(result, expected)
 
 
+def test_empty_categorical_pyarrow():
+    # https://github.com/pandas-dev/pandas/issues/53077
+    pa = pytest.importorskip("pyarrow", "11.0.0")
+
+    arr = [None]
+    table = pa.table({"arr": pa.array(arr, "float64").dictionary_encode()})
+    exchange_df = table.__dataframe__()
+    result = pd.api.interchange.from_dataframe(exchange_df)
+    expected = pd.DataFrame({"arr": pd.Categorical([np.nan])})
+    tm.assert_frame_equal(result, expected)
+
+
 def test_large_string_pyarrow():
     # GH 52795
     pa = pytest.importorskip("pyarrow", "11.0.0")