Backport PR #54881 on branch 2.1.x (REGR: read_csv raising when dtype…

…s is specified with usecols) (#54926)

doc/source/whatsnew/v2.1.1.rst

@@ -13,6 +13,7 @@ including other versions of pandas.
 
 Fixed regressions
 ~~~~~~~~~~~~~~~~~
+- Fixed regression in :func:`read_csv` when ``usecols`` is given and ``dtypes`` is a dict for ``engine="python"`` (:issue:`54868`)
 - Fixed regression in :meth:`DataFrame.__setitem__` raising ``AssertionError`` when setting a :class:`Series` with a partial :class:`MultiIndex` (:issue:`54875`)
 - Fixed regression when comparing a :class:`Series` with ``datetime64`` dtype with ``None`` (:issue:`54870`)
 

pandas/io/parsers/python_parser.py

@@ -1176,17 +1176,17 @@ def _set_no_thousand_columns(self) -> set[int]:
             )
         if self.columns and self.dtype:
             assert self._col_indices is not None
-            for i in self._col_indices:
+            for i, col in zip(self._col_indices, self.columns):
                 if not isinstance(self.dtype, dict) and not is_numeric_dtype(
                     self.dtype
                 ):
                     no_thousands_columns.add(i)
                 if (
                     isinstance(self.dtype, dict)
-                    and self.columns[i] in self.dtype
+                    and col in self.dtype
                     and (
-                        not is_numeric_dtype(self.dtype[self.columns[i]])
-                        or is_bool_dtype(self.dtype[self.columns[i]])
+                        not is_numeric_dtype(self.dtype[col])
+                        or is_bool_dtype(self.dtype[col])
                     )
                 ):
                     no_thousands_columns.add(i)

pandas/tests/io/parser/dtypes/test_dtypes_basic.py

@@ -558,3 +558,20 @@ def test_string_inference(all_parsers):
         columns=pd.Index(["a", "b"], dtype=dtype),
     )
     tm.assert_frame_equal(result, expected)
+
+
+def test_dtypes_with_usecols(all_parsers):
+    # GH#54868
+
+    parser = all_parsers
+    data = """a,b,c
+1,2,3
+4,5,6"""
+
+    result = parser.read_csv(StringIO(data), usecols=["a", "c"], dtype={"a": object})
+    if parser.engine == "pyarrow":
+        values = [1, 4]
+    else:
+        values = ["1", "4"]
+    expected = DataFrame({"a": pd.Series(values, dtype=object), "c": [3, 6]})
+    tm.assert_frame_equal(result, expected)