mathjs vs stats.js vs jstat vs simple-statistics vs numeric
JavaScript Statistical Libraries Comparison
1 Year
mathjsstats.jsjstatsimple-statisticsnumericSimilar Packages:
What's JavaScript Statistical Libraries?

JavaScript statistical libraries provide developers with tools to perform statistical analysis, mathematical computations, and data manipulation. These libraries are essential for applications that require data analysis, statistical modeling, or numerical computations. They offer a wide range of functionalities, from basic statistical functions to complex mathematical operations, making them valuable for data scientists, analysts, and developers working with data-driven applications.

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mathjs1,652,56514,6409.49 MB1385 days agoApache-2.0
stats.js372,2028,827-228 years agoMIT
jstat226,3521,779706 kB59--
simple-statistics212,5233,4221.19 MB275 months agoISC
numeric52,0631,432-6912 years ago-
Feature Comparison: mathjs vs stats.js vs jstat vs simple-statistics vs numeric

Statistical Functions

  • mathjs:

    math.js offers an extensive set of mathematical functions, including statistical functions such as mean, median, mode, variance, and standard deviation, along with advanced mathematical capabilities like calculus and algebraic operations.

  • stats.js:

    stats.js does not provide statistical functions but focuses on performance metrics, offering real-time statistics about frame rates and memory usage in web applications.

  • jstat:

    jStat provides a variety of statistical functions, including descriptive statistics, probability distributions, and hypothesis testing. It supports common distributions like normal, binomial, and Poisson, making it suitable for basic statistical analysis.

  • simple-statistics:

    simple-statistics includes essential statistical functions like mean, median, mode, variance, and regression analysis. It is designed for simplicity and ease of use, making it ideal for quick statistical calculations.

  • numeric:

    numeric.js focuses on numerical methods and linear algebra, providing functions for matrix operations, eigenvalues, and numerical integration. It is designed for applications that require high-performance numerical computations.

Complexity and Size

  • mathjs:

    math.js is a more extensive library, which may introduce additional complexity due to its wide range of features. It is suitable for applications that require advanced mathematical capabilities but may be overkill for simple tasks.

  • stats.js:

    stats.js is extremely lightweight and focused solely on performance monitoring, making it easy to include in any project without impacting overall size.

  • jstat:

    jStat is lightweight and easy to integrate into projects without significant overhead. It is designed for users who need basic statistical functions without the complexity of larger libraries.

  • simple-statistics:

    simple-statistics is designed to be minimalistic and easy to use, making it a good choice for developers who want a straightforward library for basic statistical tasks without unnecessary complexity.

  • numeric:

    numeric.js is focused on numerical analysis and is relatively lightweight compared to other comprehensive libraries. It provides a good balance between functionality and performance for numerical computations.

Learning Curve

  • mathjs:

    math.js has a steeper learning curve due to its extensive capabilities and syntax. However, it provides comprehensive documentation that can help users navigate its features effectively.

  • stats.js:

    stats.js is very easy to use, with a simple API focused on performance monitoring. Developers can quickly integrate it into their applications without a steep learning curve.

  • jstat:

    jStat has a gentle learning curve, making it accessible for developers who are new to statistics. Its straightforward API allows users to quickly implement statistical functions without extensive background knowledge.

  • simple-statistics:

    simple-statistics is designed for ease of use, with a simple API that allows developers to perform statistical calculations quickly. It is an excellent choice for beginners or those needing quick results.

  • numeric:

    numeric.js is relatively easy to learn for those familiar with numerical methods and linear algebra. Its API is straightforward, but users may need some background in numerical analysis to fully utilize its capabilities.

Performance

  • mathjs:

    math.js is versatile but may have performance trade-offs due to its extensive feature set. It is optimized for a wide range of mathematical operations, but users should be mindful of potential performance impacts in highly demanding applications.

  • stats.js:

    stats.js is optimized for real-time performance monitoring, providing minimal overhead while delivering accurate statistics about application performance.

  • jstat:

    jStat is optimized for performance in statistical calculations, making it suitable for applications that require efficient processing of statistical data without significant overhead.

  • simple-statistics:

    simple-statistics is efficient for basic statistical calculations, making it suitable for applications that require quick and simple analysis without the need for complex computations.

  • numeric:

    numeric.js is designed for high-performance numerical computations, particularly in linear algebra. It is optimized for speed and efficiency, making it suitable for scientific computing and applications that require intensive numerical analysis.

Use Cases

  • mathjs:

    math.js is suitable for applications that require extensive mathematical computations, such as scientific simulations, engineering calculations, and data analysis. It is versatile enough to handle a wide range of mathematical tasks.

  • stats.js:

    stats.js is specifically designed for performance monitoring in web applications, making it ideal for developers who want to optimize their applications' performance and ensure smooth user experiences.

  • jstat:

    jStat is ideal for projects that require basic statistical analysis, such as data visualization, A/B testing, and simple modeling applications. It is particularly useful for developers who need quick access to statistical functions.

  • simple-statistics:

    simple-statistics is perfect for projects that require quick statistical calculations, such as data reporting, analytics dashboards, and educational tools. It is designed for users who need straightforward statistical functions without complexity.

  • numeric:

    numeric.js is best for applications focused on numerical analysis, such as simulations, optimization problems, and scientific computing. It is particularly useful in fields like physics and engineering.

How to Choose: mathjs vs stats.js vs jstat vs simple-statistics vs numeric
  • mathjs:

    Select math.js for a comprehensive mathematics library that supports a wide array of mathematical operations, including algebra, calculus, and statistics. It is suitable for applications that require extensive mathematical capabilities and offers a flexible syntax for complex calculations.

  • stats.js:

    Choose stats.js if you need a lightweight library for performance monitoring in web applications. It provides real-time statistics about frame rates and memory usage, making it ideal for developers focused on optimizing the performance of their applications.

  • jstat:

    Choose jStat if you need a lightweight library focused on statistical functions, particularly for probability distributions and statistical tests. It is ideal for projects that require basic statistical analysis without the overhead of more complex libraries.

  • simple-statistics:

    Use simple-statistics if you need a straightforward library for basic statistical calculations. It is easy to use and provides essential statistical functions, making it suitable for projects that require quick and simple statistical analysis without unnecessary complexity.

  • numeric:

    Opt for numeric.js if your focus is on numerical analysis and linear algebra. It is particularly useful for applications that require matrix operations, numerical integration, and optimization, making it a good choice for scientific computing.

README for mathjs

math.js

https://mathjs.org

Math.js is an extensive math library for JavaScript and Node.js. It features a flexible expression parser with support for symbolic computation, comes with a large set of built-in functions and constants, and offers an integrated solution to work with different data types like numbers, big numbers, complex numbers, fractions, units, and matrices. Powerful and easy to use.

Version Downloads Build Status Maintenance License FOSSA Status Codecov Github Sponsor

Features

  • Supports numbers, bignumbers, bigints, complex numbers, fractions, units, strings, arrays, and matrices.
  • Is compatible with JavaScript's built-in Math library.
  • Contains a flexible expression parser.
  • Does symbolic computation.
  • Comes with a large set of built-in functions and constants.
  • Can be used as a command line application as well.
  • Runs on any JavaScript engine.
  • Is easily extensible.
  • Open source.

Usage

Math.js can be used in both node.js and in the browser.

Install math.js using npm:

npm install mathjs

Or download mathjs via one of the CDN's listed on the downloads page:

    https://mathjs.org/download.html

Math.js can be used similar to JavaScript's built-in Math library. Besides that, math.js can evaluate expressions and supports chained operations.

import {
  atan2, chain, derivative, e, evaluate, log, pi, pow, round, sqrt
} from 'mathjs'

// functions and constants
round(e, 3)                    // 2.718
atan2(3, -3) / pi              // 0.75
log(10000, 10)                 // 4
sqrt(-4)                       // 2i
pow([[-1, 2], [3, 1]], 2)      // [[7, 0], [0, 7]]
derivative('x^2 + x', 'x')     // 2 * x + 1

// expressions
evaluate('12 / (2.3 + 0.7)')   // 4
evaluate('12.7 cm to inch')    // 5 inch
evaluate('sin(45 deg) ^ 2')    // 0.5
evaluate('9 / 3 + 2i')         // 3 + 2i
evaluate('det([-1, 2; 3, 1])') // -7

// chaining
chain(3)
    .add(4)
    .multiply(2)
    .done()  // 14

See the Getting Started for a more detailed tutorial.

Browser support

Math.js works on any ES2020 compatible JavaScript engine, including node.js, Chrome, Firefox, Safari, and Edge.

Documentation

Build

First clone the project from github:

git clone git@github.com:josdejong/mathjs.git
cd mathjs

Install the project dependencies:

npm install

Then, the project can be build by executing the build script via npm:

npm run build

This will build ESM output, CommonJS output, and the bundle math.js from the source files and put them in the folder lib.

Develop

When developing new features for mathjs, it is good to be aware of the following background information.

Code

The code of mathjs is written in ES modules, and requires all files to have a real, relative path, meaning the files must have a *.js extension. Please configure adding file extensions on auto import in your IDE.

Architecture

What mathjs tries to achieve is to offer an environment where you can do calculations with mixed data types, like multiplying a regular number with a Complex number or a BigNumber, and work with all of those in matrices. Mathjs also allows to add a new data type with little effort.

The solution that mathjs uses has two main ingredients:

  • Typed functions. All functions are created using typed-function. This makes it easier to (dynamically) create and extend a single function with new data types, automatically do type conversions on function inputs, etc. So, if you create function multiply for two numbers, you can extend it with support for multiplying your own data type, say MyDecimal. If you define a conversion from MyDecimal to number, the typed-function will automatically allow you to multiply a MyDecimal with a number.

  • Dependency injection. When we have a function multiply with support for MyDecimal, thanks to the dependency injection, other functions using multiply under the hood, like prod, will automatically support MyDecimal too. This also works the other way around: if you don't need the heavyweight multiply (which supports BigNumbers, matrices, etc), and you just need a plain and simple number support, you can use a lightweight implementation of multiply just for numbers, and inject that in prod and other functions.

At the lowest level, mathjs has immutable factory functions which create immutable functions. The core function math.create(...) creates a new instance having functions created from all passed factory functions. A mathjs instance is a collection of created functions. It contains a function like math.import to allow extending the instance with new functions, which can then be used in the expression parser.

Implementing a new function

A common case is to implement a new function. This involves the following steps:

  • Implement the function in the right category, for example ./src/function/arithmetic/myNewFunction.js, where you can replace arithmetic with the proper category, and myNewFunction with the name of the new function. Add the new function to the index files ./src/factoriesAny.js and possibly ./src/factoriesNumber.js.
  • Write documentation on the function in the source code comment of myNewFunction.js. This documentation is used to auto generate documentation on the website.
  • Write embedded documentation for the new function in ./src/expression/embeddedDocs/function/arithmetic/myNewFunction.js. Add the new documentation to the index file ./src/expression/embeddedDocs/embeddedDocs.js.
  • Write unit tests for the function in ./test/unit-tests/function/arithmetic/myNewFunction.test.js.
  • Write the necessary TypeScript definitions for the new function in ./types/index.d.ts, and write tests for it in ./test/typescript-tests/testTypes.ts. This is described in ./types/EXPLANATION.md.
  • Ensure the code style is ok by running npm run lint (run npm run format to fix the code style automatically).

Build scripts

The build script currently generates two types of output:

  • any, generate entry points to create full versions of all functions
  • number: generating and entry points to create lightweight functions just supporting number

For each function, an object is generated containing the factory functions of all dependencies of the function. This allows to just load a specific set of functions, and not load or bundle any other functionality. So for example, to just create function add you can do math.create(addDependencies).

Test

To execute tests for the library, install the project dependencies once:

npm install

Then, the tests can be executed:

npm test

To test the type definitions:

npm run test:types

Additionally, the tests can be run on FireFox using headless mode:

npm run test:browser

To run the tests remotely on LambdaTest, first set the environment variables LT_USERNAME and LT_ACCESS_KEY with your username and access key and then execute:

npm run test:lambdatest

You can separately run the code linter, though it is also executed with npm test:

npm run lint

To automatically fix linting issue, run:

npm run format

To test code coverage of the tests:

npm run coverage

To see the coverage results, open the generated report in your browser:

./coverage/lcov-report/index.html

Continuous integration testing

Continuous integration tests are run on Github Actions and LambdaTest every time a commit is pushed to github. Github Actions runs the tests for different versions of node.js, and LambdaTest runs the tests on all major browsers.

LambdaTest

Thanks, GitHub Actions and LambdaTest for the generous free hosting of this open source project!

License

mathjs is published under the Apache 2.0 license:

Copyright (C) 2013-2025 Jos de Jong <wjosdejong@gmail.com>

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

   https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

mathjs contains a JavaScript port of the CSparse library, published under the LGPL-2.1+ license:

CSparse: a Concise Sparse matrix package.
Copyright (c) 2006, Timothy A. Davis.
http://www.suitesparse.com

--------------------------------------------------------------------------------

CSparse is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.

CSparse is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public
License along with this Module; if not, write to the Free Software
Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA