Map each list value to its corresponding percentile

Question

I\'d like to create a function that takes a (sorted) list as its argument and outputs a list containing each element\'s corresponding percentile.

For example,

Answer 1

If I understand you correctly, all you want to do, is to define the percentile this element represents in the array, how much of the array is before that element. as in [1, 2, 3, 4, 5] should be [0.0, 0.25, 0.5, 0.75, 1.0]

I believe such code will be enough:

def percentileListEdited(List):
    uniqueList = list(set(List))
    increase = 1.0/(len(uniqueList)-1)
    newList = {}
    for index, value in enumerate(uniqueList):
        newList[index] = 0.0 + increase * index
    return [newList[val] for val in List]

Answer 2

Pure numpy version of Kevin's solution

As Kevin said, optimal solution works in O(n log(n)) time. Here is fast version of his code in numpy, which works almost the same time as stats.rankdata:

percentiles = numpy.argsort(numpy.argsort(array)) * 100. / (len(array) - 1)

PS. This is one if my favourite tricks in numpy.

Answer 3

this might look oversimplyfied but what about this:

def percentile(x):
    pc = float(1)/(len(x)-1)
    return ["%.2f"%(n*pc) for n, i in enumerate(x)]

EDIT:

def percentile(x):
    unique = set(x)
    mapping = {}
    pc = float(1)/(len(unique)-1)
    for n, i in enumerate(unique):
        mapping[i] = "%.2f"%(n*pc)
    return [mapping.get(el) for el in x]