Make infer_freq accept Series of timezone-aware Timestamps (#52528)

* Make `infer_freq` accept `Series` of timezone-aware timestamps

* Update pandas/tests/tseries/frequencies/test_inference.py

---------

Co-authored-by: Matthew Roeschke <[email protected]>

Author: cai-lw

doc/source/whatsnew/v2.1.0.rst

@@ -283,7 +283,7 @@ Timedelta
 
 Timezones
 ^^^^^^^^^
--
+- Bug in :func:`infer_freq` that raises ``TypeError`` for ``Series`` of timezone-aware timestamps (:issue:`52456`)
 -
 
 Numeric

pandas/tests/tseries/frequencies/test_inference.py

@@ -236,6 +236,15 @@ def test_infer_freq_tz(tz_naive_fixture, expected, dates):
     assert idx.inferred_freq == expected
 
 
+def test_infer_freq_tz_series(tz_naive_fixture):
+    # infer_freq should work with both tz-naive and tz-aware series. See gh-52456
+    tz = tz_naive_fixture
+    idx = date_range("2021-01-01", "2021-01-04", tz=tz)
+    series = idx.to_series().reset_index(drop=True)
+    inferred_freq = frequencies.infer_freq(series)
+    assert inferred_freq == "D"
+
+
 @pytest.mark.parametrize(
     "date_pair",
     [

pandas/tseries/frequencies.py

@@ -32,6 +32,7 @@
 
 from pandas.core.dtypes.common import (
     is_datetime64_dtype,
+    is_datetime64tz_dtype,
     is_numeric_dtype,
     is_timedelta64_dtype,
 )
@@ -120,7 +121,7 @@ def infer_freq(
 
     Parameters
     ----------
-    index : DatetimeIndex or TimedeltaIndex
+    index : DatetimeIndex, TimedeltaIndex, Series or array-like
       If passed a Series will use the values of the series (NOT THE INDEX).
 
     Returns
@@ -150,6 +151,7 @@ def infer_freq(
         values = index._values
         if not (
             is_datetime64_dtype(values)
+            or is_datetime64tz_dtype(values)
             or is_timedelta64_dtype(values)
             or values.dtype == object
         ):