_ _ _ ___| |_ __ _| |_ ___ ___ ___ _ _ _ __ | |_ ___ _ __ / __| __/ _` | __/ __|/ __/ _ \| | | | '_ \| __/ _ \ '__| \__ \ || (_| | |_\__ \ (_| (_) | |_| | | | | || __/ | |___/\__\__,_|\__|___/\___\___/ \__,_|_| |_|\__\___|_|
StatsCounter is a GNU Licensed, statistics powered version
of Python's standard library Counter class. It attaches
several helpful methods that can be used to make your
data-driven uses a breeze.
>>>importstatscounterasstats>>>letter_freq=stats.StatsCounter(a=1, b=2, c=3, d=4, e=4, f=6)
>>>letter_freq.mean() # average frequency3.3333333333333335>>>letter_freq.mode() # most frequent element4>>>letter_freq.median() # the median number (avg if even # of items)3.5>>>letter_freq.variance() # sample variance3.066666666666667>>>letter_freq.stdev() # sample standard deviation1.7511900715418263>>>letter_freq.pvariance() # population variance2.555555555555556>>>letter_freq.pstdev() # population std. dev.1.5986105077709065>>>letter_freq.max() # the maximum value6>>>letter_freq.argmax() # the argument yielding the maximum value"f">>>importstatscounterasstats>>>stats.mean([1, 2, 3, 4, 4, 6]) # average frequency3.3333333333333335>>>stats.mode([1, 2, 3, 4, 4, 6]) # most frequent element4>>>stats.median([1, 2, 3, 4, 4, 6]) # the median number (avg if even # of items)3.5>>>stats.variance([1, 2, 3, 4, 4, 6]) # sample variance3.066666666666667>>>stats.stdev([1, 2, 3, 4, 4, 6]) # sample standard deviation1.7511900715418263>>>stats.pvariance([1, 2, 3, 4, 4, 6]) # population variance2.555555555555556>>>stats.pstdev([1, 2, 3, 4, 4, 6]) # population std. dev.1.5986105077709065