├── LICENSE.md └── README.md /LICENSE.md: -------------------------------------------------------------------------------- 1 | Licensed under the [Creative Commons Zero license](https://creativecommons.org/publicdomain/zero/1.0/). 2 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Awesome Browser Data Science Libraries [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome) 2 | 3 | A curated list of awesome libraries for doing data science that can run in your 4 | browser. That doesn't just mean Javascript: thanks to WebAssembly, many data 5 | science libraries from other languages are now available in the browser. 6 | 7 | If you want to contribute to this list (please do), file a pull request. 8 | 9 | Also, a listed repository should be deprecated if: 10 | 11 | * Repository's owner explicitly say that "this library is not maintained". 12 | * Not committed for long time (2~3 years). 13 | 14 | # Environments 15 | 16 | - [HASH](https://hash.ai/): create and run multi-agent simulations in your browser 17 | - [Observable](https://observablehq.com/): The magic notebook for Exploring Data 18 | - [Runkit](https://runkit.com/home): A Node Playground in your Browser 19 | - [Iodide](https://alpha.iodide.io/): lets you do data science entirely in your browser 20 | - [Carbide](https://alpha.trycarbide.com): A Reactive Javascript programming environment 21 | - [Kaggle Notebooks](https://www.kaggle.com/kernels): Run Analyses on Google Cloud using Python or R 22 | 23 | # Data Formats 24 | 25 | - [Papa Parse](https://www.papaparse.com/): Powerful, in-browser CSV parser 26 | - [js-xlsx](https://github.com/SheetJS/js-xlsx): Parser and writer for various spreadsheet formats 27 | - [Apache Arrow](https://github.com/apache/arrow/tree/master/js): Enable big data systems to process and transfer data quickly 28 | 29 | # Data Munging 30 | 31 | - [sql.js](https://github.com/kripken/sql.js/): SQLite compiled to JavaScript through Emscripten 32 | - [Lodash](https://lodash.com/): A modern JavaScript utility library delivering modularity, performance & extras 33 | - [jq-web](https://github.com/fiatjaf/jq-web): the command-line JSON processor, compiled with emscripten and exposed as JavaScript library 34 | - [datalib](http://vega.github.io/datalib/): a JavaScript data utility library 35 | - [zebras](https://github.com/nickslevine/zebras): a data manipulation and analysis library written in JavaScript offering the convenience of pandas or R 36 | 37 | # Math/Statistics 38 | 39 | - [mathjs](https://mathjs.org/): An extensive math library for JavaScript and Node.js 40 | - [bluemath](https://github.com/bluemathsoft/bluemath): Math kernel in Javascript 41 | - [libRmath.js](https://github.com/jacobbogers/libRmath.js/): Javascript Pure Implementation of Statistical R "core" numerical libRmath.so 42 | - [stdlib](https://github.com/stdlib-js/stdlib): A standard library for Javascript, with an emphasis on numerical and scientific computing applications. 43 | - [Simple Statistics](https://simplestatistics.org/): Statistical methods in readable JavaScript for browsers, servers, and people 44 | - [jStat](http://jstat.github.io/): perform advanced statistical operations 45 | 46 | # Machine learning 47 | 48 | - [mljs](https://github.com/mljs/ml): Machine learning tools in JavaScript 49 | - [machinelearn.js](https://www.machinelearnjs.com/): Machine Learning library for the web and Node 50 | 51 | # Natural Language Processing 52 | 53 | - [Natural](https://github.com/NaturalNode/natural): general natural language facilities for node 54 | - [node-nlp](https://github.com/axa-group/nlp.js#readme): A Fork of Natural with many additional capabilities 55 | - [sentiment](https://github.com/thisandagain/sentiment): AFINN-based sentiment analysis for Node.js 56 | - [compromise](http://compromise.cool/): interprets and pre-parses English 57 | - [wink](https://winkjs.org/): Open Source packages for NLP, ML and Statistics in Node JS to build production grade solutions 58 | - [twitter-text-js](https://github.com/twitter/twitter-text/tree/master/js): A JavaScript utility that provides text processing routines for Tweets 59 | - [Knwl.js](https://github.com/benhmoore/Knwl.js): Find Dates, Places, Times, and More. A .js library for parsing text for specific information 60 | - [Talisman](http://yomguithereal.github.io/talisman/): A straightforward & modular NLP, machine learning & fuzzy matching library for JavaScript 61 | - [Franc](https://github.com/wooorm/franc): Natural language detection 62 | - [Underscore.string](http://epeli.github.io/underscore.string/): Not actually an NLP library, but a useful toolkit for working with strings in Javascript 63 | 64 | # Deep Learning 65 | 66 | - [TensorFlow.js](https://www.tensorflow.org/js): TensorFlow.js is a library for developing and training ML models in JavaScript, and deploying in browser or on Node.js 67 | - [ml5](https://ml5js.org/): Friendly Machine Learning for the Web 68 | - [WebDNN](https://mil-tokyo.github.io/webdnn/): Fastest DNN Execution Framework on Web Browser 69 | - [brain.js](https://brain.js.org/): Neural networks in JavaScript 70 | 71 | # Visualization 72 | 73 | - [D3](https://d3js.org): Data-driven documents 74 | - [C3.js](https://c3js.org/): D3-based reusable chart library 75 | - [Vega](https://vega.github.io/vega/): A Visualization Grammar 76 | - [Plotly.js](https://plot.ly/javascript/): General-purpose data visualization 77 | - [Nivo](https://nivo.rocks/): A rich set of dataviz components, built on top of the awesome d3 and Reactjs libraries 78 | - [Chart.js](https://www.chartjs.org/): Simple yet flexible JavaScript charting for designers & developers 79 | - [sigmajs](http://sigmajs.org/): a JavaScript library dedicated to graph drawing 80 | - [falcon](https://github.com/uwdata/falcon): Interactive Visual Analysis for Big Data. Crossfilter millions of records without latencies 81 | 82 | # Other languages 83 | 84 | - [Pyodide](https://github.com/iodide-project/pyodide): The scientific Python stack, compiled to WebAssembly. 85 | --------------------------------------------------------------------------------