descriptive_statistics.py

from __future__ import division


def calculate_mean(numbers):
    total = sum(numbers)
    count = len(numbers)
    return total / count


def calculate_median(numbers):
    sorted_numbers = sorted(numbers)
    # if our list has a length that is an odd number
    if len(sorted_numbers) % 2 > 0:
        # find the center by dividing by 2 and rounding up (e.g. 7 / 2 = 3.5 rounds up to nearest integer 4)
        middle_number = len(sorted_numbers) / 2
        rounded_integer = int(round(middle_number))
        return sorted_numbers[rounded_integer]
    elif len(sorted_numbers) % 2 == 0:  # check to see if there are an even number of items in the list
        # find the center by dividing by 2 to find one of the two middle numbers
        # (eg. 8 / 2 = 4 then average the 4th and the 5th together)
        middle_left_number = len(sorted_numbers) / 2  # 4th position
        middle_right_number = middle_left_number + 1  # 5th position
        return (middle_left_number + middle_right_number) / 2
    else:
        print('You need to provide a list of numeric types, with a length > 0')


def calculate_variance(numbers):
    # create an empty variance
    variance = 0
    mean = calculate_mean(numbers)
    # go through each number in the list
    for number in numbers:
        # take the difference between the number and the mean
        # square the difference and add it to variance
        variance += (number - mean) ** 2
    return variance


def calculate_standard_deviation(numbers):
    # a square root is the same as using the 1/2 power
    return calculate_variance(numbers) ** 0.5


def descriptive_statistics(numbers):
    # max() and min() are both functions that are implemented in the python language so we don't have to write them.
    print('Min: {}'.format(min(numbers)))
    print('Max: {}'.format(max(numbers)))
    print('Mean: {}'.format(calculate_mean(numbers)))
    print('Median: {}'.format(calculate_median(numbers)))
    print('Variance: {}'.format(calculate_variance(numbers)))
    print('Std Dev: {}'.format(calculate_standard_deviation(numbers)))

# a list of numbers
numbers = [100, 85, 29, 12, 19.5]

print(descriptive_statistics(numbers))