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Calculate average score and rating based on Wilson Score Equation
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ndaidong/average-rating
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Calculate average and scoring based on Wilson Score Equation
https://jsr.io/@ndaidong/average-rating
deno add @ndaidong/average-rating# npm (use any of npx, yarn dlx, pnpm dlx, or bunx)npx jsr add @ndaidong/average-rating// es6 moduleimport{average,rate,score}from"@ndaidong/average-rating";// CommonJSconst{ score, rate, average,}=require("@ndaidong/average-rating");score(80,20);// => 0.71rate([134055,57472,143135,365957,1448459]);// => 0.84average([134055,57472,143135,365957,1448459]);// => 4.4
You can use JSR packages without an install step usingjsr: specifiers:
import{average}from"jsr:@ndaidong/average-rating";average([134055,57472,143135,365957,1448459]);// => 4.4
You can also usenpm: specifiers as before:
import{average}from"npm:@ndaidong/average-rating";average([134055,57472,143135,365957,1448459]);// => 4.4
Or import from esm.sh
import{average}from"https://esm.sh/@ndaidong/average-rating";average([134055,57472,143135,365957,1448459]);// => 4.4
https://www.npmjs.com/package/@ndaidong/average-rating
npm i @ndaidong/average-rating# pnpmpnpm i @ndaidong/average-rating# yarnyarn add @ndaidong/average-rating# bunbun add @ndaidong/average-rating
import{average}from"@ndaidong/average-rating";average([134055,57472,143135,365957,1448459]);// => 4.4
You can also use CJS style:
const{ average}=require("@ndaidong/average-rating");average([134055,57472,143135,365957,1448459]);// => 4.4
<scripttype="module">import{average}from"https://esm.sh/@ndaidong/average-rating";// import { average } from 'https://unpkg.com/@ndaidong/average-rating/esm/mod.js';average([134055,57472,143135,365957,1448459])// => 4.4</script>
This method returns a normalized value between 0 and 1, but it's applicable for systemswith only positive and negative ratings (like/dislike, thumbs up/thumbs down).Examples include videos on YouTube or answers on Stack Overflow.In these systems, users can express their opinion by voting for either a positive or negative option.
Let's illustrate how this method works with a blog post that received 80 likes and 20 dislikes:
import{score}from"@ndaidong/average-rating";score(80,20);// => 0.71
This method returns a normalized value between 0 and 1, commonly used in rating systems with 5 levels.Examples include applications on Google Play Store or books on Amazon.In these systems, each item receives a user rating between 1 and 5 stars.
Let's take a product with a large volume of reviews as an example. Here's how we calculate its rating:
- 134,055 customers rated it 1 star
- 57,472 gave it a 2-star rating
- There are 143,135 ratings of 3 stars
- It received a 4-star rating from 365,957 users
- And a whopping 1,448,459 customers rated it 5 stars
import{rate}from"@ndaidong/average-rating";rate([134055,57472,143135,365957,1448459]);// => 0.84
- Since v1.1.5, this
ratemethod accepts custom range of ratings. 5 or morevalues are OK.
constinput=[3,4,2,6,12,46,134,213,116,91,45,15,58,96,1654];// 15 valuesrate(input);// => 0.85rate([3,4,2,6,12,46,134,213,116,91]);// => 0.74
Return a value from 0 to 5.
Calculate normal average value for the systems of 5 rating levels.
import{average}from"@ndaidong/average-rating";average([134055,57472,143135,365957,1448459]);// => 4.4
Since v3.x.x, we switched toDenoplatform, and useDNT to build Node.jspackages.
git clone https://github.com/ndaidong/average-rating.gitcd average-rating# testdenotest# build npm packagesdeno task buildcd npmnode test_runner.js
The MIT License (MIT)
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Calculate average score and rating based on Wilson Score Equation