analysis.py

#!/usr/bin/env python

import matplotlib.pyplot as plt
import math
import random

data = [random.randint(10,100) for i in range(0,100)]


class Analysis(object):
    def __init__(self, data):
        data = ds or []
        if not isinstance(ds, list):
            return 'no list... why no list???'
        if any(not isinstance(d, int) for d in ds):
            return 'At least one element of ds is not an int.'
        self.data = data

    def mean(self):
        return sum(self.data) / len(self.data) 

    def median(self):
        data = sorted(self.data)
        ds_length = len(self.data)
        if ds_length < 1:
            return None
        elif ds_length % 2 == 1:
            return self.data[((ds_length + 1) / 2) - 1]
        else:
            return float(sum(self.data[(ds_length / 2) - 1:(ds_length / 2) + 1])) / 2.0

    def mode(self):
        return max(set(self.data), key=self.data.count)

    def std(self):
        return math.sqrt(sum((val - mean(self.data)) ** 2 for val in self.data) / (len(self.data) - 1))

    def get_max(self):
        return max(self.data)

    def get_min(self):
        return min(self.data)

    def get_range(self):
        return max(self.data) - min(self.data)

    def graph_it(ds, mean=None, median=None, mode=None, maximum=None, minimum=None, range=None, std_dev=None):
        mean = mean or self.mean()
        median = median or self.median()
        mode = mode or self.mode()
        maximum = maximum or self.get_max()
        minimum = minimum or self.get_min()
        data_range = data_range or self.get_range()
        std_dev = std_dev or self.std_dev()

        means = [mean for i in ds]
        medians = [median for i in ds]
        modes = [mode for i in ds]
        maxes = [maximum for i in ds]
        mins = [get_min for i in ds]
        stdsp = [mean + std for i in ds]
        stdsm = [mean - std for i in ds]
        ranges = [get_range for i in ds]
        [plt.plot(i) for i in [ds,means,medians,modes,maxes,mins,ranges,stdsp,stdsm]]
        plt.title(
            'mean = {} median = {} mode = {} std = {} max = {} min = {} range = {}'.format(
                mean, median, mode, std_dev, maximum, minimum, data_range))
        #  plt.savefig('./tmp.png')
        plt.show()


Analysis(data).graph_it()