ENH: Implement str.extract for ArrowDtype

doc/source/whatsnew/v2.2.0.rst

@@ -226,6 +226,7 @@ Other enhancements
 - Allow passing ``read_only``, ``data_only`` and ``keep_links`` arguments to openpyxl using ``engine_kwargs`` of :func:`read_excel` (:issue:`55027`)
 - DataFrame.apply now allows the usage of numba (via ``engine="numba"``) to JIT compile the passed function, allowing for potential speedups (:issue:`54666`)
 - Implement masked algorithms for :meth:`Series.value_counts` (:issue:`54984`)
+- Implemented :meth:`Series.str.extract` for :class:`ArrowDtype` (:issue:`56268`)
 - Improved error message that appears in :meth:`DatetimeIndex.to_period` with frequencies which are not supported as period frequencies, such as "BMS" (:issue:`56243`)
 - Improved error message when constructing :class:`Period` with invalid offsets such as "QS" (:issue:`55785`)
 

pandas/core/arrays/arrow/array.py

@@ -2296,9 +2296,19 @@ def _str_encode(self, encoding: str, errors: str = "strict"):
         return type(self)(pa.chunked_array(result))
 
     def _str_extract(self, pat: str, flags: int = 0, expand: bool = True):
-        raise NotImplementedError(
-            "str.extract not supported with pd.ArrowDtype(pa.string())."
-        )
+        if flags:
+            raise NotImplementedError("Only flags=0 is implemented.")
+        groups = re.compile(pat).groupindex.keys()
+        if len(groups) == 0:
+            raise ValueError(f"{pat=} must contain a symbolic group name.")
+        result = pc.extract_regex(self._pa_array, pat)
+        if expand:
+            return {
+                col: type(self)(pc.struct_field(result, [i]))
+                for col, i in zip(groups, range(result.type.num_fields))
+            }
+        else:
+            return type(self)(pc.struct_field(result, [0]))
 
     def _str_findall(self, pat: str, flags: int = 0):
         regex = re.compile(pat, flags=flags)

pandas/tests/extension/test_arrow.py

@@ -2150,14 +2150,40 @@ def test_str_rsplit():
     tm.assert_frame_equal(result, expected)
 
 
-def test_str_unsupported_extract():
-    ser = pd.Series(["abc", None], dtype=ArrowDtype(pa.string()))
-    with pytest.raises(
-        NotImplementedError, match="str.extract not supported with pd.ArrowDtype"
-    ):
+def test_str_extract_non_symbolic():
+    ser = pd.Series(["a1", "b2", "c3"], dtype=ArrowDtype(pa.string()))
+    with pytest.raises(ValueError, match="pat=.* must contain a symbolic group name."):
         ser.str.extract(r"[ab](\d)")
 
 
+@pytest.mark.parametrize("expand", [True, False])
+def test_str_extract(expand):
+    ser = pd.Series(["a1", "b2", "c3"], dtype=ArrowDtype(pa.string()))
+    result = ser.str.extract(r"(?P<letter>[ab])(?P<digit>\d)", expand=expand)
+    expected = pd.DataFrame(
+        {
+            "letter": ArrowExtensionArray(pa.array(["a", "b", None])),
+            "digit": ArrowExtensionArray(pa.array(["1", "2", None])),
+        }
+    )
+    tm.assert_frame_equal(result, expected)
+
+
+def test_str_extract_expand():
+    ser = pd.Series(["a1", "b2", "c3"], dtype=ArrowDtype(pa.string()))
+    result = ser.str.extract(r"[ab](?P<digit>\d)", expand=True)
+    expected = pd.DataFrame(
+        {
+            "digit": ArrowExtensionArray(pa.array(["1", "2", None])),
+        }
+    )
+    tm.assert_frame_equal(result, expected)
+
+    result = ser.str.extract(r"[ab](?P<digit>\d)", expand=False)
+    expected = pd.Series(ArrowExtensionArray(pa.array(["1", "2", None])), name="digit")
+    tm.assert_series_equal(result, expected)
+
+
 @pytest.mark.parametrize("unit", ["ns", "us", "ms", "s"])
 def test_duration_from_strings_with_nat(unit):
     # GH51175