Reputation: 55
I have this list of tuples
[('Jem', 10), ('Sam', 10), ('Sam', 2), ('Jem', 9), ('Jem', 10)]
How do I find the average of the numbers coupled with each name, i.e. the average of all the numbers stored in a tuple with Jem, and then output them? In this example, the output would be:
Jem 9.66666666667
Sam 6
Upvotes: 4
Views: 2156
Reputation: 2099
You can also use List comprehensions:
l = [('Jem', 10), ('Sam', 10), ('Sam', 2), ('Jem', 9), ('Jem', 10)]
def avg(l):
return sum(l)/len(l)
result = [(n, avg([v[1] for v in l if v[0] is n])) for n in set([n[0] for n in l])]
# result is [('Jem', 9.666666666666666), ('Sam', 6.0)]
Upvotes: 0
Reputation: 54223
There's a couple ways to do this. One is easy, one is pretty.
Use a dictionary! It's easy to build a for
loop that goes through your tuples and appends the second element to a dictionary, keyed on the first element.
d = {}
tuples = [('Jem', 10), ('Sam', 10), ('Sam', 2), ('Jem', 9), ('Jem', 10)]
for tuple in tuples:
key,val = tuple
d.setdefault(key, []).append(val)
Once it's in a dictionary, you can do:
for name, values in d.items():
print("{name} {avg}".format(name=name, avg=sum(values)/len(values)))
Use itertools.groupby
. This only works if your data is sorted by the key you want to group by (in this case, t[0]
for each t
in tuples
) so it's not ideal in this case, but it's a nice way to highlight the function.
from itertools import groupby
tuples = [('Jem', 10), ('Sam', 10), ('Sam', 2), ('Jem', 9), ('Jem', 10)]
tuples.sort(key=lambda tup: tup[0])
# tuples is now [('Jem', 10), ('Jem', 9), ('Jem', 10), ('Sam', 10), ('Sam', 2)]
groups = groupby(tuples, lambda tup: tup[0])
This builds a structure that looks kind of like:
[('Jem', [('Jem', 10), ('Jem', 9), ('Jem', 10)]),
('Sam', [('Sam', 10), ('Sam', 2)])]
We can use that to build our names and averages:
for groupname, grouptuples in groups:
values = [t[1] for t in groupvalues]
print("{name} {avg}".format(name=groupname, avg=sum(values)/len(values)))
Upvotes: 5
Reputation: 117981
Seems like a straight-forward case for collections.defaultdict
from collections import defaultdict
l = [('Jem', 10), ('Sam', 10), ('Sam', 2), ('Jem', 9), ('Jem', 10)]
d = defaultdict(list)
for key, value in l:
d[key].append(value)
Then calculating the mean
from numpy import mean
for key in d:
print(key, mean(d[key]))
Output
Jem 9.66666666667
Sam 6.0
Upvotes: 5