calculate_mean.py

import csv
import random
import math

def loadCsv(filename):
	lines = csv.reader(open(filename, "rb"))
	dataset = list(lines)
	for i in range(len(dataset)):
		dataset[i] = [float(x) for x in dataset[i]]
	return dataset

def splitDataset(dataset, splitRatio):
	trainSize = int(len(dataset) * splitRatio)
	trainSet = []
	copy = list(dataset)
	while len(trainSet) < trainSize:
		index = random.randrange(len(copy))
		trainSet.append(copy.pop(index))
	return [trainSet, copy]

def separateByClass(dataset):
	separated = {}
	for i in range(len(dataset)):
		vector = dataset[i]
		if (vector[-1] not in separated):
			separated[vector[-1]] = []
		separated[vector[-1]].append(vector)
	return separated

def mean(numbers):
        return sum(numbers)/float(len(numbers))

def stdev(numbers):
        avg = mean(numbers)
        variance = sum([pow(x-avg,2) for x in numbers])/float(len(numbers)-1)
        return math.sqrt(variance)
def main():
	filename = 'pima_diabetes.csv'
	dataset = loadCsv(filename)
	dataset = [[1], [2], [3], [4], [5]]
        splitRatio = 0.67
        train, test = splitDataset(dataset, splitRatio)
	dataset = [[1,20,1], [2,21,0], [3,22,1]]
	separated = separateByClass(dataset)
	numbers = [1,2,3,4,5]
	print('Summary of {0}: mean={1}, stdev={2}').format(numbers, mean(numbers), stdev(numbers))
	print"==================================================================="
main()