BUG: add pyarrow autogenerated prefix

doc/source/whatsnew/v2.2.0.rst

@@ -221,8 +221,10 @@ Bug fixes
 ~~~~~~~~~
 - Bug in :class:`AbstractHolidayCalendar` where timezone data was not propagated when computing holiday observances (:issue:`54580`)
 - Bug in :class:`pandas.core.window.Rolling` where duplicate datetimelike indexes are treated as consecutive rather than equal with ``closed='left'`` and ``closed='neither'`` (:issue:`20712`)
+- Bug in :class:`pandas.io.parsers.ArrowParserWrapper` where ``usecols`` wasn't working when using pyarrow to read a csv with no headers (:issue:`54459`)
 - Bug in :meth:`DataFrame.apply` where passing ``raw=True`` ignored ``args`` passed to the applied function (:issue:`55009`)
 
+
 Categorical
 ^^^^^^^^^^^
 - :meth:`Categorical.isin` raising ``InvalidIndexError`` for categorical containing overlapping :class:`Interval` values (:issue:`34974`)

pandas/io/parsers/arrow_parser_wrapper.py

@@ -100,6 +100,12 @@ def _get_pyarrow_options(self) -> None:
             )
         }
         self.convert_options["strings_can_be_null"] = "" in self.kwds["null_values"]
+        # autogenerated column names are prefixed with 'f' in pyarrow.csv
+        if self.header is None and "include_columns" in self.convert_options:
+            self.convert_options["include_columns"] = [
+                f"f{n}" for n in self.convert_options["include_columns"]
+            ]
+
         self.read_options = {
             "autogenerate_column_names": self.header is None,
             "skip_rows": self.header

pandas/tests/io/parser/test_header.py

@@ -684,3 +684,21 @@ def test_header_delim_whitespace(all_parsers):
     result = parser.read_csv(StringIO(data), delim_whitespace=True)
     expected = DataFrame({"a,b": ["1,2", "3,4"]})
     tm.assert_frame_equal(result, expected)
+
+
+def test_usecols_no_header_pyarrow(pyarrow_parser_only):
+    parser = pyarrow_parser_only
+    data = """
+a,i,x
+b,j,y
+"""
+    result = parser.read_csv(
+        StringIO(data),
+        header=None,
+        usecols=[0, 1],
+        dtype="object",
+        dtype_backend="pyarrow",
+        engine="pyarrow",
+    )
+    expected = DataFrame([["a", "i"], ["b", "j"]])
+    tm.assert_frame_equal(result, expected)