Awesome Browser Data Science Libraries

A curated list of awesome libraries for doing data science that can run in your browser. That doesn't just mean Javascript: thanks to WebAssembly, many data science libraries from other languages are now available in the browser.

If you want to contribute to this list (please do), file a pull request.

Also, a listed repository should be deprecated if:

• Repository's owner explicitly say that "this library is not maintained".
• Not committed for long time (2~3 years).

Environments

• HASH: create and run multi-agent simulations in your browser
• Observable: The magic notebook for Exploring Data
• Runkit: A Node Playground in your Browser
• Iodide: lets you do data science entirely in your browser
• Carbide: A Reactive Javascript programming environment
• Kaggle Notebooks: Run Analyses on Google Cloud using Python or R

Data Formats

• Papa Parse: Powerful, in-browser CSV parser
• js-xlsx: Parser and writer for various spreadsheet formats
• Apache Arrow: Enable big data systems to process and transfer data quickly

Data Munging

• sql.js: SQLite compiled to JavaScript through Emscripten
• Lodash: A modern JavaScript utility library delivering modularity, performance & extras
• jq-web: the command-line JSON processor, compiled with emscripten and exposed as JavaScript library
• datalib: a JavaScript data utility library
• zebras: a data manipulation and analysis library written in JavaScript offering the convenience of pandas or R

Math/Statistics

• mathjs: An extensive math library for JavaScript and Node.js
• bluemath: Math kernel in Javascript
• libRmath.js: Javascript Pure Implementation of Statistical R "core" numerical libRmath.so
• stdlib: A standard library for Javascript, with an emphasis on numerical and scientific computing applications.
• Simple Statistics: Statistical methods in readable JavaScript for browsers, servers, and people
• jStat: perform advanced statistical operations

Machine learning

• mljs: Machine learning tools in JavaScript
• machinelearn.js: Machine Learning library for the web and Node

Natural Language Processing

• Natural: general natural language facilities for node
• node-nlp: A Fork of Natural with many additional capabilities
• sentiment: AFINN-based sentiment analysis for Node.js
• compromise: interprets and pre-parses English
• wink: Open Source packages for NLP, ML and Statistics in Node JS to build production grade solutions
• twitter-text-js: A JavaScript utility that provides text processing routines for Tweets
• Knwl.js: Find Dates, Places, Times, and More. A .js library for parsing text for specific information
• Talisman: A straightforward & modular NLP, machine learning & fuzzy matching library for JavaScript
• Franc: Natural language detection
• Underscore.string: Not actually an NLP library, but a useful toolkit for working with strings in Javascript

Deep Learning

• TensorFlow.js: TensorFlow.js is a library for developing and training ML models in JavaScript, and deploying in browser or on Node.js
• ml5: Friendly Machine Learning for the Web
• WebDNN: Fastest DNN Execution Framework on Web Browser
• brain.js: Neural networks in JavaScript

Visualization

• D3: Data-driven documents
• C3.js: D3-based reusable chart library
• Vega: A Visualization Grammar
• Plotly.js: General-purpose data visualization
• Nivo: A rich set of dataviz components, built on top of the awesome d3 and Reactjs libraries
• Chart.js: Simple yet flexible JavaScript charting for designers & developers
• sigmajs: a JavaScript library dedicated to graph drawing
• falcon: Interactive Visual Analysis for Big Data. Crossfilter millions of records without latencies

Other languages

• Pyodide: The scientific Python stack, compiled to WebAssembly.