diff options
Diffstat (limited to 'Lib/statistics.py')
-rw-r--r-- | Lib/statistics.py | 29 |
1 files changed, 28 insertions, 1 deletions
diff --git a/Lib/statistics.py b/Lib/statistics.py index 47c2bb41cb..8ecb906d86 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. |