Struggling to choose between CanvasJS Charts and ggvis? Both products offer unique advantages, making it a tough decision.
CanvasJS Charts is a Development solution with tags like charts, graphs, data-visualization, javascript.
It boasts features such as 30+ chart types including line, area, column, bar, pie, doughnut, funnel, polar charts, Interactive data visualization, Animations, zooming, panning, Touch support for mobile devices, Canvas rendering for better performance, Export charts as images, Drill down charts, Real-time charts with streaming data and pros including Easy to use API, Good documentation, Open source and free, Good performance, Lots of chart types and customization options, Works across devices and browsers.
On the other hand, ggvis is a Data Visualization product tagged with r, ggplot2, interactive, data-visualization, graphics, web-browser.
Its standout features include Grammar of Graphics-based visualization using the ggplot2 API, Interactivity through linking graphical elements to data, Built on top of Shiny for reactive programming, Can embed plots in R Markdown documents and Shiny apps, Supports faceting, zooming, panning, etc., Exporting plots to SVG and PNG format, and it shines with pros like Leverages ggplot2 syntax for easy plotting, Interactivity enables exploration of data, Tight integration with Shiny apps, Can create standalone visualizations to embed in web pages.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
CanvasJS Charts is a JavaScript charting library that enables interactive charts, graphs and data visualizations in web applications. It offers 30+ chart types including line, area, column, bar, pie, doughnut, funnel, polar charts and more.
ggvis is an R package for creating interactive data visualizations and graphics in a web browser. It builds on the popular ggplot2 package but allows users to add interactivity, make visualizations reusable, and embed them in web pages.