Get max value from a list with lists?

In perhaps a more functional than pythonic manner:

>>> max(map(lambda x: x[3], resultlist))
9.1931

It begins by mapping each element of result list to the number value and then finds the max.

The intermediate array is:

>>> map(lambda x: x[3], resultlist)
[8.3931000000000004, 6.3231000000000002, 9.1930999999999994]

Loop through your outer list and select the last element of each sublist:

def max_value(inputlist):
    return max([sublist[-1] for sublist in inputlist])

print max_value(resultlist)
# 9.1931

It's also best if you keep all function related variables in-scope (pass the list as an argument and don't confuse the namespace by reusing variable names).

If you want the index too you can use enumerate with operator.itemgetter using map:

from operator import itemgetter
def max_val(l, i):
    return max(enumerate(map(itemgetter(i), l)),key=itemgetter(1)))

Which will return a tuple of the max with the index:

In [7]: resultlist = [["1", "1", "a", 8.3931], ["1", "2", "b", 6.3231], ["2", "1", "c", 9.1931]]

In [8]: max_val(resultlist, -1)
Out[8]: (2, 9.1931)

Or just a regular gen exp:

from operator import itemgetter
def max_val(l, i):
    return max(enumerate(sub[i] for sub in l), key=itemgetter(1))

Numpy helps with numerical nested lists. Try this:

resultlist = [[3, 2, 4, 4], [1, 6, 7, -6], [5, 4, 3, 2]]
max(resultlist)  # yields [5, 4, 3, 2] because 5 is the max in: 3, 1, 5
np.max(resultlist)  # yields 7 because it's the absolute max

max() returns the list which first element is the maximum of all lists' first element, while np.max() returns the highest value from all the nested lists.