Normalizing a list of numbers in Python

Question

I need to normalize a list of values to fit in a probability distribution, i.e. between 0.0 and 1.0.

I understand how to normalize, but was curious if Python had a function to automate this.

I'd like to go from:

raw = [0.07, 0.14, 0.07]  

to

normed = [0.25, 0.50, 0.25]

Answer 1

Try this :

from __future__ import division

raw = [0.07, 0.14, 0.07]  

def norm(input_list):
    norm_list = list()

    if isinstance(input_list, list):
        sum_list = sum(input_list)

        for value in input_list:
            tmp = value  /sum_list
            norm_list.append(tmp) 

    return norm_list

print norm(raw)

This will do what you asked. But I will suggest to try Min-Max normalization.

min-max normalization :

def min_max_norm(dataset):
    if isinstance(dataset, list):
        norm_list = list()
        min_value = min(dataset)
        max_value = max(dataset)

        for value in dataset:
            tmp = (value - min_value) / (max_value - min_value)
            norm_list.append(tmp)

    return norm_list