diff --git a/Lib/statistics.py b/Lib/statistics.py
index d81596e..0d747b3 100644
--- a/Lib/statistics.py
+++ b/Lib/statistics.py
@@ -555,8 +555,9 @@
 
     """
     data = iter(data)
+    pairs = Counter(data).most_common(1)
     try:
-        return Counter(data).most_common(1)[0][0]
+        return pairs[0][0]
     except IndexError:
         raise StatisticsError('no mode for empty data') from None
 
@@ -602,6 +603,7 @@
 # mean=0.300.  Only the latter (which corresponds with R6) gives the
 # desired cut point with 30% of the population falling below that
 # value, making it comparable to a result from an inv_cdf() function.
+# The R6 exclusive method is also idempotent.
 
 # For describing population data where the end points are known to
 # be included in the data, the R7 inclusive method is a reasonable