descriptive-stats.py

import numpy as np
import matplotlib.pyplot as plt
import scipy.stats

def descriptive_stats(distribution):

	'''
	Compute and present simple descriptive stats for a distribution
	
	Parameters
	----------
	distribution: list
		Distribution as a Python list	
	'''

	# Convert distribution as numpy ndarray
	dist = np.array(distribution)

	print 'Descriptive statistics for distribution:\n', dist
	print 'Number of scores:', len(dist)
	print 'Number of unique scores:', len(np.unique(dist))
	print 'Sum:', sum(dist)
	print 'Min:', min(dist)
	print 'Max:', max(dist)
	print 'Range:', max(dist)-min(dist)
	print 'Mean:', np.mean(dist, axis=0)
	print 'Median:', np.median(dist, axis=0)
	print 'Mode:', scipy.stats.mode(dist)[0][0]
	print 'Variance:', np.var(dist, axis=0)
	print 'Standard deviation:', np.std(dist, axis=0)
	print '1st quartile:', np.percentile(dist, 25)
	print '3rd quartile:', np.percentile(dist, 75)
	print 'Distribution skew:', scipy.stats.skew(dist)

	plt.hist(dist, bins=len(dist))
	plt.yticks(np.arange(0, 6, 1.0))
	plt.title('Histogram of distribution scores')
	plt.show()

descriptive_stats([ 1, 4, 5, 6, 8, 8, 9, 10, 10, 11, 11, 13, 13, 13, 14, 14, 15, 15, 15, 15 ])