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 module
import { average, rate, score } from "@ndaidong/average-rating";
// CommonJS
const {
score,
rate,
average,
} = require("@ndaidong/average-rating");
score(80, 20); // => 0.71
rate([134055, 57472, 143135, 365957, 1448459]); // => 0.84
average([134055, 57472, 143135, 365957, 1448459]); // => 4.4
You can use JSR packages without an install step using jsr:
specifiers:
import { average } from "jsr:@ndaidong/average-rating";
average([134055, 57472, 143135, 365957, 1448459]); // => 4.4
You can also use npm:
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
# pnpm
pnpm i @ndaidong/average-rating
# yarn
yarn add @ndaidong/average-rating
# bun
bun 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
<script type="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 systems with 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
rate
method accepts custom range of ratings. 5 or more values are OK.
const input = [3, 4, 2, 6, 12, 46, 134, 213, 116, 91, 45, 15, 58, 96, 1654]; // 15 values
rate(input); // => 0.85
rate([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 to Deno platform, and use DNT to build Node.js packages.
git clone https://github.com/ndaidong/average-rating.git
cd average-rating
# test
deno test
# build npm packages
deno task build
cd npm
node test_runner.js
The MIT License (MIT)