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Awesome Browser Data Science Libraries.md

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Awesome Browser Data Science Libraries Awesome

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.