PERF: Return RangeIndex columns in str.extract when possible

doc/source/whatsnew/v3.0.0.rst

@@ -167,7 +167,7 @@ Performance improvements
 - Performance improvement in :meth:`MultiIndex.equals` for equal length indexes (:issue:`56990`)
 - Performance improvement in :meth:`RangeIndex.append` when appending the same index (:issue:`57252`)
 - Performance improvement in indexing operations for string dtypes (:issue:`56997`)
--
+- :meth:`Series.str.extract` returns a :class:`RangeIndex` columns instead of an :class:`Index` column when possible (:issue:`?``)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_300.bug_fixes:

pandas/core/strings/accessor.py

@@ -3557,7 +3557,7 @@ def _get_single_group_name(regex: re.Pattern) -> Hashable:
         return None
 
 
-def _get_group_names(regex: re.Pattern) -> list[Hashable]:
+def _get_group_names(regex: re.Pattern) -> Index:
     """
     Get named groups from compiled regex.
 
@@ -3569,10 +3569,24 @@ def _get_group_names(regex: re.Pattern) -> list[Hashable]:
 
     Returns
     -------
-    list of column labels
+    Index
     """
+    from pandas import Index
+
     names = {v: k for k, v in regex.groupindex.items()}
-    return [names.get(1 + i, i) for i in range(regex.groups)]
+    if not names:
+        return Index(range(1))
+    return_rangeindex = True
+    result = []
+    for i in range(regex.groups):
+        name = names.get(1 + i, i)
+        if return_rangeindex and name != i:
+            return_rangeindex = False
+        result.append(name)
+    if return_rangeindex:
+        return Index(range(regex.groups))
+    else:
+        return Index(result)
 
 
 def str_extractall(arr, pat, flags: int = 0) -> DataFrame:

pandas/tests/strings/test_extract.py

@@ -372,7 +372,7 @@ def test_extract_dataframe_capture_groups_index(index, any_string_dtype):
 
     result = s.str.extract(r"(\d)", expand=True)
     expected = DataFrame(["1", "2", np.nan], index=index, dtype=any_string_dtype)
-    tm.assert_frame_equal(result, expected)
+    tm.assert_frame_equal(result, expected, check_column_type=True)
 
     result = s.str.extract(r"(?P<letter>\D)(?P<number>\d)?", expand=True)
     expected = DataFrame(