Finding mean of a values in a dictionary without using .values() etc

Question

I have a dictionary that looks like:

G={\'E\': 18.0, \'D\': 17.0, \'C\': 19.0, \'B\': 15.0, \'A\': 0}

I have to find the mean of the values

Answer 1

Use G.values() to get all the values from a dictionary.

G = {'E': 18.0, 'D': 17.0, 'C': 19.0, 'B': 15.0, 'A': 0}
d = float(sum(G.values())) / len(G)
print (d)

This prints 13.8.

Note that there is a difference between Python 2 and Python 3 here. In Python 2, G.values() is a newly constructed list of values. In Python 3, it is a generator, which can be thought of as a “lazy list”. The same thing is called G.itervalues() in Python 2.

Answer 2

You want:

mean = sum([G[key] for key in G])/float(len(G))

Your original code will also produce a:

TypeError: 'int' object is not iterable

when you try to sum the values.

Answer 3

What I suggest instead of the current answers is adopting a functional programming paradigm that is reusable and flexible. For example, creating a function to calculate any statistic on list values contained within a simple dict:

def summarize_dict(dictionary, function):
        dict_new = {}
    for k,v in dictionary.items():
        dict_new[k] = function(v)
    return dict_new

Testing:

import numpy as np

keys = ["a","b","c","d","e"]
values = [range(2),range(4),range(6),range(8),range(10)]
dictionary = dict(zip(keys, values))

summarize_dict(dictionary, np.mean)

Yields:

{'a': 0.5, 'b': 1.5, 'c': 2.5, 'd': 3.5, 'e': 4.5}

Answer 4

Suppose you have a dictionary with multiple keys, each having a list of values:

your_averaged_dictionary = {key: np.mean(values) for key, values in your_dictionary}