Update 2015-08-10

The example given now uses strings as the keys instead of numbers to ward off any confusion between the keys and their counts.

Getting the greatest element from a sequence in Python is dead simple: just use the built-in max function.

Storing the frequency of items is also dead easy with collections.Counter:

>>> from collections import Counter
>>> c = Counter('abracadabra')
>>> print(c)
Counter({'a': 5, 'b': 2, 'r': 2, 'c': 1, 'd': 1})

The greatest item in a counter is obviously the most common, so surely we’ll just …

>>> max(c)
'r'

What? Here’s the gotcha: Python counters are a dictionary subclass. Call max with a dictionary and it’ll get the greatest key, because keys are what you get when you iterate over a dictionary. Same deal.

To get the most common element you have to use — surprise! — Counter.most_common(). Without arguments this produces a list of tuples (item, count), sorted by count:

>>> c.most_common()
[('a', 5), ('b', 2), ('r', 2), ('c', 1), ('d', 1)]

So to get the actual most common element, you do:

>>> c.most_common(1)[0][0]
'a'

Where the argument 1 limits it to the first tuple.

But what if the counter’s empty? You’ll get an IndexError trying to index into the list returned by most_common():

>>> d = Counter()
>>> d.most_common()
[]
>>> d.most_common()[0][0]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
IndexError: list index out of range

In Python 3.4 max got the default argument, which you can use to get a default value when a sequence is empty. Here’s how to get similar behaviour with Counter:

d.most_common(1)[0][0] if d else None

This takes advantage of the "falsey" nature of an empty dictionary to give you None without having to handle an IndexError.