"""
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
# 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