BUG: Pyarrow timestamp support for map() function

doc/source/whatsnew/v3.0.0.rst

@@ -844,6 +844,7 @@ Other
 - Bug in :meth:`Series.diff` allowing non-integer values for the ``periods`` argument. (:issue:`56607`)
 - Bug in :meth:`Series.dt` methods in :class:`ArrowDtype` that were returning incorrect values. (:issue:`57355`)
 - Bug in :meth:`Series.isin` raising ``TypeError`` when series is large (>10**6) and ``values`` contains NA (:issue:`60678`)
+- Bug in :meth:`Series.map` where mapping with a ``dict`` failed to match keys when the Series used ``timestamp[ns][pyarrow]`` dtype. (:issue:`61231`)
 - Bug in :meth:`Series.mode` where an exception was raised when taking the mode with nullable types with no null values in the series. (:issue:`58926`)
 - Bug in :meth:`Series.rank` that doesn't preserve missing values for nullable integers when ``na_option='keep'``. (:issue:`56976`)
 - Bug in :meth:`Series.replace` and :meth:`DataFrame.replace` inconsistently replacing matching instances when ``regex=True`` and missing values are present. (:issue:`56599`)

pandas/core/algorithms.py

@@ -24,6 +24,7 @@
     lib,
 )
 from pandas._libs.missing import NA
+from pandas._libs.tslibs.timestamps import Timestamp
 from pandas._typing import (
     AnyArrayLike,
     ArrayLike,
@@ -59,6 +60,7 @@
 )
 from pandas.core.dtypes.concat import concat_compat
 from pandas.core.dtypes.dtypes import (
+    ArrowDtype,
     BaseMaskedDtype,
     CategoricalDtype,
     ExtensionDtype,
@@ -1691,6 +1693,14 @@ def map_array(
         if na_action == "ignore":
             mapper = mapper[mapper.index.notna()]
 
+        if isinstance(arr.dtype, ArrowDtype) and arr.dtype.name.startswith("timestamp"):
+            try:
+                # Convert elements to pandas.Timestamp (or datetime64[ns])
+                arr = arr.astype("datetime64[ns]")
+            except Exception:
+                # fallback: safe, slow path
+                arr = np.array([Timestamp(x.as_py()) for x in arr])
+
         # Since values were input this means we came from either
         # a dict or a series and mapper should be an index
         indexer = mapper.index.get_indexer(arr)

pandas/tests/series/methods/test_map.py

@@ -604,3 +604,14 @@ def test_map_kwargs():
     result = Series([2, 4, 5]).map(lambda x, y: x + y, y=2)
     expected = Series([4, 6, 7])
     tm.assert_series_equal(result, expected)
+
+
+def test_map_arrow_timestamp_dict():
+    # GH 61231
+    pytest.importorskip("pyarrow", minversion="10.0.1")
+
+    ser = Series(date_range("2023-01-01", periods=3)).astype("timestamp[ns][pyarrow]")
+    mapper = {ts: i for i, ts in enumerate(ser)}
+    result = ser.map(mapper)
+    expected = Series([0, 1, 2], dtype="int64")
+    tm.assert_series_equal(result, expected)