BUG: .rolling() returns incorrect values when ts index is not nano seconds

doc/source/conf.py

@@ -172,7 +172,9 @@
 import pandas  # isort:skip
 
 # version = '%s r%s' % (pandas.__version__, svn_version())
-version = str(pandas.__version__)
+# version = str(pandas.__version__)
+
+version = str(pandas.__version__).split("+")[0]
 
 # The full version, including alpha/beta/rc tags.
 release = version

pandas/core/window/rolling.py

@@ -1884,6 +1884,9 @@ def _validate(self):
             else:
                 self._win_freq_i8 = freq.nanos
 
+            if self._on.dtype == "M8[us]":
+                self._win_freq_i8 /= 1000
+
             # min_periods must be an integer
             if self.min_periods is None:
                 self.min_periods = 1

pandas/tests/window/test_rolling.py

@@ -1950,3 +1950,24 @@ def test_numeric_only_corr_cov_series(kernel, use_arg, numeric_only, dtype):
         op2 = getattr(rolling2, kernel)
         expected = op2(*arg2, numeric_only=numeric_only)
         tm.assert_series_equal(result, expected)
+
+
+def test_rolling_rolling_sum_window_microseconds_confilict_timestamp():
+    # GH#55106
+    df_time = DataFrame(
+        {"B": [0, 1, 2, 4, 5, 6]},
+        index=[
+            Timestamp("20130101 09:00:00"),
+            Timestamp("20130101 09:00:02"),
+            Timestamp("20130101 09:00:03"),
+            Timestamp("20130101 09:00:06"),
+            Timestamp("20130101 09:00:07"),
+            Timestamp("20130101 09:00:08"),
+        ],
+    )
+    sum_in_nanosecs = df_time.rolling("1s").sum()
+    # micro seconds / milliseconds should not breaks the correct rolling
+    df_time.index = df_time.index.as_unit("us")
+    sum_in_microsecs = df_time.rolling("1s").sum()
+    sum_in_microsecs.index = sum_in_microsecs.index.as_unit("ns")
+    tm.assert_frame_equal(sum_in_nanosecs, sum_in_microsecs)