119 def _sum(data, start=0):  argument
159     for typ, values in groupby(data, type):
294 def _counts(data):  argument
296     table = collections.Counter(iter(data)).most_common()
310 def mean(data):  argument
326     if iter(data) is data:
327         data = list(data)
328     n = len(data)
331     T, total, count = _sum(data)
337 def median(data):  argument
350     data = sorted(data)
351     n = len(data)
355         return data[n//2]
358         return (data[i - 1] + data[i])/2
361 def median_low(data):  argument
373     data = sorted(data)
374     n = len(data)
378         return data[n//2]
380         return data[n//2 - 1]
383 def median_high(data):  argument
395     data = sorted(data)
396     n = len(data)
399     return data[n//2]
402 def median_grouped(data, interval=1):  argument
428     data = sorted(data)
429     n = len(data)
433         return data[0]
436     x = data[n//2]
445     cf = data.index(x)  # Number of values below the median interval.
447     f = data.count(x)  # Number of data points in the median interval.
451 def mode(data):  argument
469     table = _counts(data)
493 def _ss(data, c=None):  argument
502         c = mean(data)
503     T, total, count = _sum((x-c)**2 for x in data)
506     U, total2, count2 = _sum((x-c) for x in data)
508     total -=  total2**2/len(data)
513 def variance(data, xbar=None):  argument
551     if iter(data) is data:
552         data = list(data)
553     n = len(data)
556     T, ss = _ss(data, xbar)
560 def pvariance(data, mu=None):  argument
599     if iter(data) is data:
600         data = list(data)
601     n = len(data)
604     ss = _ss(data, mu)
605     T, ss = _ss(data, mu)
609 def stdev(data, xbar=None):  argument
618     var = variance(data, xbar)
625 def pstdev(data, mu=None):  argument
634     var = pvariance(data, mu)