Expand Up @@ -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. Expand All @@ -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'): Expand Down