BUG: PeriodArray.__add__(array_of_ints)

doc/source/whatsnew/v1.5.0.rst

@@ -829,6 +829,7 @@ Period
 - Bug in inferring an incorrect ``freq`` when passing a string to :class:`Period` microseconds that are a multiple of 1000 (:issue:`46811`)
 - Bug in constructing a :class:`Period` from a :class:`Timestamp` or ``np.datetime64`` object with non-zero nanoseconds and ``freq="ns"`` incorrectly truncating the nanoseconds (:issue:`46811`)
 - Bug in adding ``np.timedelta64("NaT", "ns")`` to a :class:`Period` with a timedelta-like freq incorrectly raising ``IncompatibleFrequency`` instead of returning ``NaT`` (:issue:`47196`)
+- Bug in adding an array of integers to an array with :class:`PeriodDtype` giving incorrect results when ``dtype.freq.n > 1`` (:issue:`47209`)
 -
 
 Plotting

pandas/core/arrays/datetimelike.py

@@ -1317,7 +1317,7 @@ def __add__(self, other):
             if not is_period_dtype(self.dtype):
                 raise integer_op_not_supported(self)
             result = cast("PeriodArray", self)._addsub_int_array_or_scalar(
-                other, operator.add
+                other * self.freq.n, operator.add
             )
         else:
             # Includes Categorical, other ExtensionArrays
@@ -1379,7 +1379,7 @@ def __sub__(self, other):
             if not is_period_dtype(self.dtype):
                 raise integer_op_not_supported(self)
             result = cast("PeriodArray", self)._addsub_int_array_or_scalar(
-                other, operator.sub
+                other * self.freq.n, operator.sub
             )
         else:
             # Includes ExtensionArrays, float_dtype

pandas/tests/arithmetic/test_period.py

@@ -914,6 +914,19 @@ def test_pi_sub_intlike(self, five):
         exp = rng + (-five)
         tm.assert_index_equal(result, exp)
 
+    def test_pi_add_sub_int_array_freqn_gt1(self):
+        # GH#47209 test adding array of ints when freq.n > 1 matches
+        #  scalar behavior
+        pi = period_range("2016-01-01", periods=10, freq="2D")
+        arr = np.arange(10)
+        result = pi + arr
+        expected = pd.Index([x + y for x, y in zip(pi, arr)])
+        tm.assert_index_equal(result, expected)
+
+        result = pi - arr
+        expected = pd.Index([x - y for x, y in zip(pi, arr)])
+        tm.assert_index_equal(result, expected)
+
     def test_pi_sub_isub_offset(self):
         # offset
         # DateOffset