- Echarts & Highcharts
- React Virtualized + React Vis + Victory
- Raw graphs
With 80,000 stars in the hub’s gateway, D3.js is built to create data-driven documents and create data into life using HTML, SVG, and CSS. The D3 emphasis on web standards allows you to create modern browsers without connecting to a dedicated framework, combining visual components, and a data-driven approach for the DOM. This allows you to assign arbitrary data to an Object Model (DOM) and then apply the transformations to the document.
With 40,000 stars in the Github, this Chart.js open-source library is built with HTML5 and canvas standards. It provides various graphs, graph axes and beautiful animations. Simple and elegant designs with 8 types of base diagrams and you can combine the library with moment.js for the time axis.
With 47,000 stars in the Github, this Three.js library is made to create 3D animations using WebGL. The flexibility and abstraction of the project means that it is useful for data visualization in two or three dimensions.
Highcharts JS with 8,000 stars in the Goethe Hub, this library is based on SVG, with VBI and band for older browsers. Claims that 72 of the 100 world’s companies use the library, such as Facebook and Twitter.
With 7,000 stars in the GitHub, MetricGraphics.js is a library that is optimized for visualization and estimation of time series data. With a volume of 80 KB, it provides a slim but beautiful selection of line charts, sparse pages, histograms, bar graphs and data tables, as well as features such as linear regression carpet.
Recharts – With 10,000 stars in the GitHub, there is a React and D3 structural library that allows you to apply as React Announcement components. With support for native SVG, the lightweight dependency tree (submodules D3) provides highly customizable through the component booth.
With 10,000 stars in the GitHub, the “vector library” is designed to work with vector graphics on the web. This Raphael library uses the SVG W3C Recommendation and VML as the basis for creating graphics, so any graphical object is also a DOM object, and you can attach Java event categories. Raphael now supports Firefox 3.0+, Safari 3.0+, Chrome 5.0+, Opera 9.5+ and Internet Explorer 6.0+.
With 8,000 stars in the Github, C3.js is a D3-based integrated chart library for web applications. This library provides classes for each element, so you can define a custom style by class and directly expand the structure of D3. It also provides a variety of programming interface and callbacks to access the chart state. With them, you can update the chart even after rendering.
With 4,000 stars in the Github, React Virtualized + React Vis + Victory is a set of React Uber components is suited for displaying data in a consistent manner, including line / area / bar graphs, heat maps, scatter plates, meter plots, hexagonal heaters, and much more. This library has no previous knowledge with D3 or any other information library, and provides modular building block components such as the X / Y axis.
With a 12,000 star in the GitHub, there is a set of React components for rendering large lists and tabular data. ES6, CommonJS and UMD are available in each distribution, and the project supports Webpack.
Victory is a collection of composite reactions designed to create interactive data visualization that is created using the same web programming interface for the Web and React Native applications for simple and cross-platform applications. A delicate and flexible method for levering React Components in favor of practical information visualization.
With 2000 stars in the GitHub, Carto is a smart tool and visual information to discover insights based on location data. You can upload geographic data (Shapefiles, GeoJSON, etc.) using a web form and view it in a dataset or map, search it using SQL, and use the map styles Apply CartoCSS.
RAWGraphs – With 5000 stars in the Github, there is a link between spreadsheets and data visualization created to create custom vector images for the d3.js library. This works with tabular data (spreadsheets and comma separated values) as well as texts copied and pasted from other programs. Based on the SVG format, visualizations can be embedded with vector graphics programs for further refinement, or directly on web pages.
With 11,000 stars in the Github, Metabase is a quick and easy way to create a data warehouse without knowing SQL. You can create focal areas and criteria, send information to Slack. It’s probably a great tool to visualize data internally for your team, although some maintenance may be needed.