statscounter 0.0.010

Python's missing statistical Swiss Army knife

StatsCounter: A statistics-enabled Python container

     _        _                             _
 ___| |_ __ _| |_ ___  ___ ___  _   _ _ __ | |_ ___ _ __
/ __| __/ _` | __/ __|/ __/ _ \| | | | '_ \| __/ _ \ '__|
\__ \ || (_| | |_\__ \ (_| (_) | |_| | | | | ||  __/ |
|___/\__\__,_|\__|___/\___\___/ \__,_|_| |_|\__\___|_|

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.

Usage

As a histogram

>>> import statscounter as stats
>>> letter_freq = stats.StatsCounter(a=1, b=2, c=3, d=4, e=4, f=6)
>>> letter_freq.mean()      # average frequency
3.3333333333333335
>>> letter_freq.mode()      # most frequent element
4
>>> letter_freq.median()    # the median number (avg if even # of items)
3.5
>>> letter_freq.variance()  # sample variance
3.066666666666667
>>> letter_freq.stdev()     # sample standard deviation
1.7511900715418263
>>> letter_freq.pvariance() # population variance
2.555555555555556
>>> letter_freq.pstdev()    # population std. dev.
1.5986105077709065
>>> letter_freq.max()       # the maximum value
6
>>> letter_freq.argmax()    # the argument yielding the maximum value
"f"

As a utility

>>> import statscounter as stats
>>> stats.mean([1, 2, 3, 4, 4, 6])      # average frequency
3.3333333333333335
>>> stats.mode([1, 2, 3, 4, 4, 6])      # most frequent element
4
>>> 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 variance
3.066666666666667
>>> stats.stdev([1, 2, 3, 4, 4, 6])     # sample standard deviation
1.7511900715418263
>>> stats.pvariance([1, 2, 3, 4, 4, 6]) # population variance
2.555555555555556
>>> stats.pstdev([1, 2, 3, 4, 4, 6])    # population std. dev.
1.5986105077709065