Question

How can I iterate over a group of objects to find their mean in the most efficent way? This uses just one loop (except perhaps loops in Numpy) but I was wondering whether there was a better way. At the moment, I am doing this:

scores = []
ratings= []
negative_scores = []
positive_scores = []

for t in text_collection:
 scores.append(t.score)
 ratings.append(t.rating)
 if t.score < 0:
    negative_scores.append(t.score)
 elif t.score > 0:
    positive_scores.append(t.score)

print "average score:", numpy.mean(scores)
print "average rating:", numpy.mean(ratings)
print "average negative score:", numpy.mean(negative_scores)
print "average positive score:", numpy.mean(positive_scores)

Is there a better way of doing this?

Answer 1

import numpy as np
scores, ratings = np.array([(t.score, t.rating) for t in text_collection]).T

print 'average score: ', np.mean(scores)
print 'average rating: ', np.mean(ratings)
print 'average positive score: ', np.mean(scores[scores > 0])
print 'average negative score: ', np.mean(scores[scores < 0])

EDIT:

To check if there actually are any negative scores, you could so something like this:

if np.count_nonzero(scores < 0):
    print 'average negative score: ', np.mean(scores[scores < 0])