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-rw-r--r--Lib/statistics.py25
1 files changed, 18 insertions, 7 deletions
diff --git a/Lib/statistics.py b/Lib/statistics.py
index 5d38f85..bd3813c 100644
--- a/Lib/statistics.py
+++ b/Lib/statistics.py
@@ -136,7 +136,7 @@ from decimal import Decimal
from itertools import groupby, repeat
from bisect import bisect_left, bisect_right
from math import hypot, sqrt, fabs, exp, erf, tau, log, fsum
-from operator import itemgetter
+from operator import itemgetter, mul
from collections import Counter, namedtuple
# === Exceptions ===
@@ -345,7 +345,7 @@ def mean(data):
return _convert(total / n, T)
-def fmean(data):
+def fmean(data, weights=None):
"""Convert data to floats and compute the arithmetic mean.
This runs faster than the mean() function and it always returns a float.
@@ -363,13 +363,24 @@ def fmean(data):
nonlocal n
for n, x in enumerate(iterable, start=1):
yield x
- total = fsum(count(data))
- else:
+ data = count(data)
+ if weights is None:
total = fsum(data)
- try:
+ if not n:
+ raise StatisticsError('fmean requires at least one data point')
return total / n
- except ZeroDivisionError:
- raise StatisticsError('fmean requires at least one data point') from None
+ try:
+ num_weights = len(weights)
+ except TypeError:
+ weights = list(weights)
+ num_weights = len(weights)
+ num = fsum(map(mul, data, weights))
+ if n != num_weights:
+ raise StatisticsError('data and weights must be the same length')
+ den = fsum(weights)
+ if not den:
+ raise StatisticsError('sum of weights must be non-zero')
+ return num / den
def geometric_mean(data):