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

d=[float(sum(values)) / len(values) for key, values in G]
    return (d)
ValueError: need more than 1 value to unpack

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


count = 0
_sum = 0
for key in G:
    count += 1
    _sum += G[key]

print('this is the mean: ', _sum/count)

d=[float(sum(values)) / len(values) for key, values in G.iteritems()]

import statistics
numbers = [G[key] for key in G]
mean_ = statistics.mean(numbers)

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

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

TypeError: 'int' object is not iterable

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

sum = 0
for k in G:
    sum += float(G[k])

print "Mean: " + str(sum/len(G))

Mean: 13.8
[Finished in 0.3s]

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

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)

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