BUG: infer_freq with Series[pyarrow[timestamp]]

doc/source/whatsnew/v3.0.0.rst

@@ -975,6 +975,7 @@ Datetimelike
 - Bug in :class:`Timestamp` constructor failing to raise when given a ``np.datetime64`` object with non-standard unit (:issue:`25611`)
 - Bug in :func:`date_range` where the last valid timestamp would sometimes not be produced (:issue:`56134`)
 - Bug in :func:`date_range` where using a negative frequency value would not include all points between the start and end values (:issue:`56147`)
+- Bug in :func:`infer_freq` with a :class:`Series` with :class:`ArrowDtype` timestamp dtype incorrectly raising ``TypeError`` (:issue:`58403`)
 - Bug in :func:`to_datetime` where passing an ``lxml.etree._ElementUnicodeResult`` together with ``format`` raised  ``TypeError``. Now subclasses of ``str`` are handled. (:issue:`60933`)
 - Bug in :func:`tseries.api.guess_datetime_format` would fail to infer time format when "%Y" == "%H%M" (:issue:`57452`)
 - Bug in :func:`tseries.frequencies.to_offset` would fail to parse frequency strings starting with "LWOM" (:issue:`59218`)

pandas/tests/tseries/frequencies/test_inference.py

@@ -13,6 +13,7 @@
 from pandas._libs.tslibs.offsets import _get_offset
 from pandas._libs.tslibs.period import INVALID_FREQ_ERR_MSG
 from pandas.compat import is_platform_windows
+import pandas.util._test_decorators as td
 
 from pandas import (
     DatetimeIndex,
@@ -542,3 +543,16 @@ def test_infer_freq_non_nano_tzaware(tz_aware_fixture):
 
     res = frequencies.infer_freq(dta)
     assert res == "B"
+
+
+@td.skip_if_no("pyarrow")
+def test_infer_freq_pyarrow():
+    # GH#58403
+    data = ["2022-01-01T10:00:00", "2022-01-01T10:00:30", "2022-01-01T10:01:00"]
+    pd_series = Series(data).astype("timestamp[s][pyarrow]")
+    pd_index = Index(data).astype("timestamp[s][pyarrow]")
+
+    assert frequencies.infer_freq(pd_index.values) == "30s"
+    assert frequencies.infer_freq(pd_series.values) == "30s"
+    assert frequencies.infer_freq(pd_index) == "30s"
+    assert frequencies.infer_freq(pd_series) == "30s"

pandas/tseries/frequencies.py

@@ -37,6 +37,7 @@
 
 from pandas.core.dtypes.common import is_numeric_dtype
 from pandas.core.dtypes.dtypes import (
+    ArrowDtype,
     DatetimeTZDtype,
     PeriodDtype,
 )
@@ -132,6 +133,14 @@ def infer_freq(
 
     if isinstance(index, ABCSeries):
         values = index._values
+
+        if isinstance(index.dtype, ArrowDtype):
+            import pyarrow as pa
+
+            if pa.types.is_timestamp(values.dtype.pyarrow_dtype):
+                # GH#58403
+                values = values._to_datetimearray()
+
         if not (
             lib.is_np_dtype(values.dtype, "mM")
             or isinstance(values.dtype, DatetimeTZDtype)