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authorRaymond Hettinger <rhettinger@users.noreply.github.com>2019-02-21 23:06:29 (GMT)
committerGitHub <noreply@github.com>2019-02-21 23:06:29 (GMT)
commit47d9987247bcc45983a6d51fd1ae46d5d356d0f8 (patch)
tree16b7e88590f9a28ff47e8a0e041510c4a2d86756 /Lib/statistics.py
parentf36f89257b30e0bf88e8aaff6da14a9a96f57b9e (diff)
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bpo-35904: Add statistics.fmean() (GH-11892)
Diffstat (limited to 'Lib/statistics.py')
-rw-r--r--Lib/statistics.py29
1 files changed, 28 insertions, 1 deletions
diff --git a/Lib/statistics.py b/Lib/statistics.py
index 47c2bb4..8ecb906 100644
--- a/Lib/statistics.py
+++ b/Lib/statistics.py
@@ -79,7 +79,7 @@ A single exception is defined: StatisticsError is a subclass of ValueError.
__all__ = [ 'StatisticsError',
'pstdev', 'pvariance', 'stdev', 'variance',
'median', 'median_low', 'median_high', 'median_grouped',
- 'mean', 'mode', 'harmonic_mean',
+ 'mean', 'mode', 'harmonic_mean', 'fmean',
]
import collections
@@ -312,6 +312,33 @@ def mean(data):
assert count == n
return _convert(total/n, T)
+def fmean(data):
+ """ Convert data to floats and compute the arithmetic mean.
+
+ This runs faster than the mean() function and it always returns a float.
+ The result is highly accurate but not as perfect as mean().
+ If the input dataset is empty, it raises a StatisticsError.
+
+ >>> fmean([3.5, 4.0, 5.25])
+ 4.25
+
+ """
+ try:
+ n = len(data)
+ except TypeError:
+ # Handle iterators that do not define __len__().
+ n = 0
+ def count(x):
+ nonlocal n
+ n += 1
+ return x
+ total = math.fsum(map(count, data))
+ else:
+ total = math.fsum(data)
+ try:
+ return total / n
+ except ZeroDivisionError:
+ raise StatisticsError('fmean requires at least one data point') from None
def harmonic_mean(data):
"""Return the harmonic mean of data.