bpo-36546: Clean-up comments (GH-14857) (#14859)
(cherry picked from commit eed5e9a9562d4dcd137e9f0fc7157bc3373c98cc)
Co-authored-by: Raymond Hettinger <rhettinger@users.noreply.github.com>
diff --git a/Lib/statistics.py b/Lib/statistics.py
index 79b65a2..f09f7be 100644
--- a/Lib/statistics.py
+++ b/Lib/statistics.py
@@ -596,12 +596,9 @@
# 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 @@
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'):