given a histogram and the parameters used to construct it, return the percentile rank of of a given value

calc_per_rank.py

import math

def calc_per_rank(val, hist, min_, max_, n_bins):
  
  # determine how large each bin is
  bin_interval = ( max_ - min_ ) / float( n_bins)

  # identify which bin the value falls in
  bin_index = int( math.floor( ( float( val ) - min_ ) / bin_interval ) )

  # divide the number of observations up to and including the value's bin
  # by the number of all observations
  ratio = float( sum( hist[:bin_index] ) ) / float( sum( hist ) ) 

  # return the percentile rank of the value
  # multiply by 100 for interpretability
  return ratio * 100.