Freedman-Diaconis thumb rule for number of bins of a histogram

bucket_sizes.py

import math

def numBins(metric, defaultBins):
	h = binWidth(metric)
	ulim = max(metric)
	llim = min(metric)
	if (h <= (ulim - llim) / len(metric)):
		return defaultBins or 10
	return int(math.ceil((ulim - llim) / h))

def binWidth(metric):
	return 2 * iqr(metric) * (len(metric) ** (-0.333))

def comparator(a, b):
	return a - b

def iqr(metric):
	metric[0:].sort(cmp=comparator)
	q1 = metric[int(math.floor(len(metric) / 4))]
	q3 = metric[int(math.floor(len(metric) * 3 / 4))]
	return q3 - q1


metric = []

for x in range(0,1866):
	metric.append(x)

print numBins(metric, 10)