Utility functions to calculate percentiles and percent ranks in a JavaScript array.

percentile.js

// Returns the value at a given percentile in a sorted numeric array.
// "Linear interpolation between closest ranks" method
function percentile(arr, p) {
    if (arr.length === 0) return 0;
    if (typeof p !== 'number') throw new TypeError('p must be a number');
    if (p <= 0) return arr[0];
    if (p >= 1) return arr[arr.length - 1];

    var index = (arr.length - 1) * p,
        lower = Math.floor(index),
        upper = lower + 1,
        weight = index % 1;

    if (upper >= arr.length) return arr[lower];
    return arr[lower] * (1 - weight) + arr[upper] * weight;
}

// Returns the percentile of the given value in a sorted numeric array.
function percentRank(arr, v) {
    if (typeof v !== 'number') throw new TypeError('v must be a number');
    for (var i = 0, l = arr.length; i < l; i++) {
        if (v <= arr[i]) {
            while (i < l && v === arr[i]) i++;
            if (i === 0) return 0;
            if (v !== arr[i-1]) {
                i += (v - arr[i-1]) / (arr[i] - arr[i-1]);
            }
            return i / l;
        }
    }
    return 1;
}

Hi,
Thanks for your valuable contribution to writing such a nice code. I had found an issue when we calculate Percentile of decimal values. It's not calculated accurately because resulted value is not matched with Excel resulted value. We need to sort the array before going to perform operations on it. I had added sorting functionality in the following code. Now resulted value is matched with Excel value.

function percentile(arr, p) {
if (arr.length === 0) return 0;
if (typeof p !== 'number') throw new TypeError('p must be a number');
if (p <= 0) return arr[0];
if (p >= 1) return arr[arr.length - 1];

arr.sort(function (a, b) { return a - b; });
var index = (arr.length - 1) * p
    lower = Math.floor(index),
    upper = lower + 1,
    weight = index % 1;

if (upper >= arr.length) return arr[lower];
return arr[lower] * (1 - weight) + arr[upper] * weight;
}

I've ported the function rank method from numpy's percentileofscore.

• Docs of percentileofscore
• Original implementation

You need to have ramda as dependency, but chances are if you need this function, you already use ramda to facilitate functional programming:

const R = require('ramda')
const percentileOfScore = (array, value) => {
  let originalLength = array.length
  let a = [...array]
  let alen
  const equalsValue = v => v === value

  if (!R.any(equalsValue, array)) {
    a.push(value)
    alen = range(a.length)
  } else {
    alen = range(a.length + 1)
  }
  const sortedArray = R.sort((a, b) => a - b, array)
  const idx = R.map(equalsValue, sortedArray)
  const alenTrue = R.filter((v, i) => {
    return idx[alen.indexOf(v)] === true
  }, alen)
  const mean = R.mean(alenTrue)
  const percent = mean / originalLength
  return percent
}

@superzadeh Thanks for the function! Here's modified version that uses Lodash (to get the mean) and it expects array to be already sorted (to avoid n * sorting):

const percentileOfScore = (array, value) => {
    const originalLength = array.length;
    const a = [...array];
    let alen;
    const equalsValue = v => v === value;

    if (!array.some(equalsValue)) {
        a.push(value);
        alen = range(a.length)
    } else {
        alen = range(a.length + 1)
    }
    const idx = array.map(equalsValue);
    const alenTrue = alen.filter((v) => idx[alen.indexOf(v)]);
    const meanVal = mean(alenTrue);
    const percent = meanVal / originalLength;
    return Math.round( percent * 100) / 100;
};

I don't know why I didn't see all these comments for years, but thanks for the contributions. I updated line 9.

---

// sort + filter by open interest
  {
    filteredBacktestResults.sort((a, b) => a.open_interest - b.open_interest)
    const values = filteredBacktestResults.map(backtestResult => backtestResult.open_interest)
    for (let i = 0; i < filteredBacktestResults.length; ++i) {
      filteredBacktestResults[i].open_interest_rank_percentile = percentRank(values, filteredBacktestResults[i].open_interest)
    }
    filteredBacktestResults = filteredBacktestResults.filter(backtestResult => {
      const openInterestTooLow = backtestResult.open_interest_rank_percentile <= 0.25 // bottom 25%
      if (openInterestTooLow === true) {
        return false
      }
      return true
    })
  }

hopefully this example helps somebody else on Google of how to use this, thank you @IceCreamYou + others who helped make it better