From eed5e9a9562d4dcd137e9f0fc7157bc3373c98cc Mon Sep 17 00:00:00 2001 From: Raymond Hettinger Date: Fri, 19 Jul 2019 01:57:22 -0700 Subject: [PATCH] bpo-36546: Clean-up comments (GH-14857) --- Lib/statistics.py | 12 +++--------- 1 file changed, 3 insertions(+), 9 deletions(-) diff --git a/Lib/statistics.py b/Lib/statistics.py index 79b65a29183..f09f7be354c 100644 --- a/Lib/statistics.py +++ b/Lib/statistics.py @@ -596,12 +596,9 @@ def multimode(data): # intervals, and exactly 100p% of the intervals lie to the left of # Q7(p) and 100(1 - p)% of the intervals lie to the right of Q7(p)." -# If the need arises, we could add method="median" for a median -# unbiased, distribution-free alternative. Also if needed, the -# distribution-free approaches could be augmented by adding -# method='normal'. However, for now, the position is that fewer -# options make for easier choices and that external packages can be -# used for anything more advanced. +# If needed, other methods could be added. However, for now, the +# position is that fewer options make for easier choices and that +# external packages can be used for anything more advanced. def quantiles(dist, /, *, n=4, method='exclusive'): '''Divide *dist* into *n* continuous intervals with equal probability. @@ -620,9 +617,6 @@ def quantiles(dist, /, *, n=4, method='exclusive'): data. The minimum value is treated as the 0th percentile and the maximum value is treated as the 100th percentile. ''' - # Possible future API extensions: - # quantiles(data, already_sorted=True) - # quantiles(data, cut_points=[0.02, 0.25, 0.50, 0.75, 0.98]) if n < 1: raise StatisticsError('n must be at least 1') if hasattr(dist, 'inv_cdf'):