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authorRaymond Hettinger <rhettinger@users.noreply.github.com>2019-09-21 04:46:52 (GMT)
committerGitHub <noreply@github.com>2019-09-21 04:46:52 (GMT)
commit7ce4bfa8cfcc78d03e164f2de64a2caad1d919af (patch)
tree6415e46d93a245d7758d876ff57617471895fc95 /Lib/statistics.py
parent87d6cd3604e5c83c06339276228139f5e040b0e7 (diff)
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Minor code and comment cleanup (GH-16315)
Diffstat (limited to 'Lib/statistics.py')
-rw-r--r--Lib/statistics.py4
1 files changed, 3 insertions, 1 deletions
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 @@ def mode(data):
"""
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 @@ def multimode(data):
# 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