Some reformatting (suggested by Black) and minor factoring. (GH-20865)

Lib/statistics.py

@@ -554,8 +554,7 @@ def mode(data):
     If *data* is empty, ``mode``, raises StatisticsError.
 
     """
-    data = iter(data)
-    pairs = Counter(data).most_common(1)
+    pairs = Counter(iter(data)).most_common(1)
     try:
         return pairs[0][0]
     except IndexError:
@@ -597,7 +596,7 @@ def multimode(data):
 # For sample data where there is a positive probability for values
 # beyond the range of the data, the R6 exclusive method is a
 # reasonable choice.  Consider a random sample of nine values from a
-# population with a uniform distribution from 0.0 to 100.0.  The
+# population with a uniform distribution from 0.0 to 1.0.  The
 # distribution of the third ranked sample point is described by
 # betavariate(alpha=3, beta=7) which has mode=0.250, median=0.286, and
 # mean=0.300.  Only the latter (which corresponds with R6) gives the
@@ -643,8 +642,7 @@ def quantiles(data, *, n=4, method='exclusive'):
         m = ld - 1
         result = []
         for i in range(1, n):
-            j = i * m // n
-            delta = i*m - j*n
+            j, delta = divmod(i * m, n)
             interpolated = (data[j] * (n - delta) + data[j + 1] * delta) / n
             result.append(interpolated)
         return result