Backport PR #55562 on branch 2.1.x (Floordiv fix for pyarrow dtypes) (#…

…55578)

Backport PR #55562: Floordiv fix for pyarrow dtypes

Co-authored-by: rohanjain101 <38412262+rohanjain101@users.noreply.github.com>

doc/source/whatsnew/v2.1.2.rst

@@ -27,9 +27,9 @@ Bug fixes
 - Fixed bug in :meth:`DataFrame.interpolate` raising incorrect error message (:issue:`55347`)
 - Fixed bug in :meth:`Index.insert` raising when inserting ``None`` into :class:`Index` with ``dtype="string[pyarrow_numpy]"`` (:issue:`55365`)
 - Fixed bug in :meth:`Series.all`  and :meth:`Series.any` not treating missing values correctly for ``dtype="string[pyarrow_numpy]"`` (:issue:`55367`)
+- Fixed bug in :meth:`Series.floordiv` for :class:`ArrowDtype` (:issue:`55561`)
 - Fixed bug in :meth:`Series.rank` for ``string[pyarrow_numpy]`` dtype (:issue:`55362`)
 - Silence ``Period[B]`` warnings introduced by :issue:`53446` during normal plotting activity (:issue:`55138`)
--
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_212.other:

pandas/core/arrays/arrow/array.py

@@ -116,7 +116,8 @@ def floordiv_compat(
     ) -> pa.ChunkedArray:
         # Ensure int // int -> int mirroring Python/Numpy behavior
         # as pc.floor(pc.divide_checked(int, int)) -> float
-        result = pc.floor(pc.divide(left, right))
+        converted_left = cast_for_truediv(left, right)
+        result = pc.floor(pc.divide(converted_left, right))
         if pa.types.is_integer(left.type) and pa.types.is_integer(right.type):
             result = result.cast(left.type)
         return result

pandas/tests/extension/test_arrow.py

@@ -3091,3 +3091,12 @@ def test_factorize_chunked_dictionary():
     exp_uniques = pd.Index(ArrowExtensionArray(pa_array.combine_chunks()))
     tm.assert_numpy_array_equal(res_indices, exp_indicies)
     tm.assert_index_equal(res_uniques, exp_uniques)
+
+
+def test_arrow_floordiv():
+    # GH 55561
+    a = pd.Series([-7], dtype="int64[pyarrow]")
+    b = pd.Series([4], dtype="int64[pyarrow]")
+    expected = pd.Series([-2], dtype="int64[pyarrow]")
+    result = a // b
+    tm.assert_series_equal(result, expected)