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

To do this with a "simple for loop", using your constraints against using the dict methods:

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)

If you're supposed to avoid dict methods, clearly this is an academic exercise.

Without that constraint:

The statistics module in the standard library has a mean method, which would be my first thought (as the standard library does not require third party packages.):

>>> G={'E': 18.0, 'D': 17.0, 'C': 19.0, 'B': 15.0, 'A': 0}
>>> from statistics import mean
>>> mean(G[k] for k in G)
13.8

Third party packages like numpy and pandas have objects with a mean method:

>>> from numpy import array
>>> array([G[k] for k in G]).mean()
13.8

>>> from pandas import Series
>>> Series([G[k] for k in G]).mean()
13.8

If we allow ourselves to use the values() method, this gets a little simpler with iterable unpacking. For some reason the other answers violate that condition, so I figure I should show the more efficient way of doing it:

>>> Series([*G.values()]).mean()
13.8