how to get percentage of the i th value from list from the total of i th values of lists

Question

I am facing a little challenge to create a certain logic in python, I am creating a dataset that has three lists, I want to calculate the percentage of every i-th value of the list and create new lists, here is the example of what I am trying to achieve

I have these three lists

 good=[500,400,300]
 opportunity=[300,200,100]
 bad=[100,50,20]

I am able to have the list of total of the i-th values

total=[x + y + z for x, y, z in zip(good, opportunity ,bad)]
##total=[900,650,420]

now I want the list to be converted into percentages as

good=[(500/900)*100,(400/900)*100,(300/900)*100]
opportunity=[(300/650)*100,(200/650)*100,(100/650)*100]
bad=[(100/420)*100,(50/420)*100,(20/420)*100]

Answer 1

good = [(x/total[0])*100 for x in good]
opportunity=[(x/total[1])*100 for x in opportunity]
bad=[(x/total[2])*100 for x in bad]

output:

[55.55555555555556, 44.44444444444444, 33.33333333333333]
[46.15384615384615, 30.76923076923077, 15.384615384615385]
[23.809523809523807, 11.904761904761903, 4.761904761904762]

Answer 2

You can use a list of lists, and numpy to make this problem easier to solve

import numpy as np

#List of lists from good, opportunity and bad
li = [[500,400,300],[300,200,100],[100,50,20]]

#Convert list to numpy arr
arr = np.array(li)

#Calculate total
total=[x + y + z for x, y, z in zip(*li)]

#Use numpy.divide to divide each element of list by total
print([np.divide(li[idx], total[idx]) for idx in range(3)])

The output will then be

[array([0.55555556, 0.44444444, 0.33333333]), 
array([0.46153846, 0.30769231, 0.15384615]), 
array([0.23809524, 0.11904762, 0.04761905])]

You can also assign back your percentages to variables as follows

perc_good, perc_opportunity, perc_bad = [np.divide(li[idx], total[idx]) for idx in range(3)]
print(list(perc_good))
print(list(perc_opportunity))
print(list(perc_bad))

The output will be

[0.5555555555555556, 0.4444444444444444, 0.3333333333333333]
[0.46153846153846156, 0.3076923076923077, 0.15384615384615385]
[0.23809523809523808, 0.11904761904761904, 0.047619047619047616]

Answer 3

In your example, your divisors are computed on columns (ith positions) but are applied across rows instead of columns. I assume that you actually meant to apply them on columns (eg good=[(500/900)*100,(400/650)*100,(300/420)*100] )

Once you have your list of totals you can use zip to transform each list of values into a list of percentages:

totals             = [ sum(v)  for v   in zip(good,opportunity,bad) ]
goodPercent        = [ 100*v/t for v,t in zip(good,totals) ]
opportunityPercent = [ 100*v/t for v,t in zip(opportunity,totals) ]
badPercent         = [ 100*v/t for v,t in zip(bad,totals) ]

# goodPercent:        [55.55555555555556,  61.53846153846154,  71.42857142857143]
# opportunityPercent: [33.333333333333336, 30.76923076923077,  23.80952380952381]
# badPercent:         [11.11111111111111,   7.6923076923076925, 4.761904761904762]

# (columns add up to 100%)

On the other hand, if you want percentages across rows, then you should treat each list individually:

goodPercent        = [ 100*v/t for t in [sum(good)]        for v in good         ]
opportunityPercent = [ 100*v/t for t in [sum(opportunity)] for v in opportunity  ]
badPercent         = [ 100*v/t for t in [sum(bad)]         for v in bad          ]

# goodPercent:        [41.666666666666664, 33.333333333333336, 25.0]
# opportunityPercent: [50.0, 33.333333333333336, 16.666666666666668]
# badPercent:         [58.8235294117647, 29.41176470588235, 11.764705882352942]

# (rows add up to 100%)