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The first thing that comes to everyone’s mind when we say data is Python. We often forget that we code in JavaScript when we develop web apps. We can view, edit, code everything in the same browser in real-time. Yes, JavaScript is the default programming language of the web, and it will be for the next 5–10 years (least to say). It runs everywhere on the web. The same web where we learn stuff. So, if we want to do data analysis, visualization, or machine learning, we should think of JavaScript and not Python. We developers always say one thing in software development- Never try to reinvent the wheel unless necessary. If something exists, add it as a dependency. If not, try to find a similar open-source project and tweak it according to your own needs. Well, I don’t know about you, but I seriously believe that. When it comes to JavaScript development, there are tons of cool awesome open-source projects and packages listed in the npm registry that you may find handy for your projects. Here I am discussing seven npm packages that I find most helpful to developers for manipulating data, visualization, and performing machine learning.
1 Tidy.js
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Tidy.js is a data wrangling library developed in JavaScript from scratch. It It is the easiest to start with when it comes to doing data manipulation in your JavaScript apps. If you have an existing knowledge of JavaScript arrays and objects, this library would be the easiest to learn for you. Link to Tidy.js
2. Apache Arrow
The project aims to build an arrow technology that makes deserialization of data from the big cluster of data formats to an in-memory solution like Pandas library in Python or any other, easier and faster than the existing solutions available. Apache Arrow is a cross-language development platform for in-memory analytics. The APIs are available in multiple languages, such as JavaScript, Python, Java, etc.
3. TensorFlow.js
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TensorFlow is a well-known library to almost everyone in the software industry. No kidding! Tensorflow is now available in JavaScript too. It allows developers to directly build machine learning models in the browser or the backend through Node.js. Link to Tensorflow.js
4. Cytoscape.js
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Cytoscape is a rich JavaScript library to analyze graphs. It is a lesser-known library that allows developers to visualize the graph data in the browser in a unique way. It includes all the gestures that one would expect to have in a visualization library like pinch to zoom, box selection, and panning. It supports both web and mobile applications. Link To Cytoscape.js
5. D3.js
screenshot It is a common and the most matured data visualization library. Even Google uses it to create data experiments and visualizations with this library. D3.js helps you bring data to life using HTML, SVG, and CSS. It easily integrates with any modern JavaScript web framework like React, Angular, Vue.js, etc. Link To D3.js
6. Three.js
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Three.js is a 3d visualization library for creative developers. Have you ever wondered how Github made that creative globe on its landing page? Yes, they took a little help from three.js to ease their job. If you want to bring your 3d models alive on the web, this library is a must-try for you. Link To Three.js
7. Chart.js
As the name suggests, It is a charting library for the web. It has an offline library and supports in-browser API to create attractive and interactive charts on the modern browser without any trouble. Link To Chart.js That’s it for this post. I hope you liked it. Did you find this article useful? Will you use the libraries in your next project? Let me know in the comments section. I would love to know your opinion on the same.
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