Simple stats module

stats.py

from statistics import mean, median_low, stdev, mode

def stat(lst):
    if not lst:
        return None

    _min = min(lst)
    _max = max(lst)
    _mean = mean(lst)

    return {
        'mean': _mean,
        'median': median_low(lst),
        'mode': mode(lst),
        'min': _min,
        'max': _max,
        'stdev': stdev(lst, _mean),
        'n': len(lst),
        'range': _max - _min
    }

def fmt_stat(lst):
    values = stat(lst)

    if not values:
        return 'N/A, empty data set'

    return 'n: {n}, mean/stdev: {mean:.3f}/{stdev:.2f}, median/mode: {median}/{mode}, min/max: {min}/{max}, range: {range}'.format(**values)


# Example usage:
# lst = [1, 2, 6, 2, 5, 2, 6, 7, 23, 5, 31, 11, 3]
# print(fmt_stat(lst))  # => n: 13, mean/stdev: 8.000/9.00, median/mode: 5/2, min/max: 1/31, range: 30

By no means this is super efficient nor otherwise elegant. Check out Numpy if you want to do heavy lifting /w Python & stats.

Also choosing median_low instead of other options median_high and median: the latter is bad in a sense that one nice property of median is that if you don't use average for even number of datapoints, you can be certain that result is actually a real datapoint -- and with cardinals that could be pretty important (you don't want to fit 2.7 humans somewhere). The choice between high and low was purely random, though.