ggvis vs D3.js

Struggling to choose between ggvis and D3.js? Both products offer unique advantages, making it a tough decision.

ggvis is a Data Visualization solution with tags like r, ggplot2, interactive, data-visualization, graphics, web-browser.

It boasts features such as 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 pros including 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.

On the other hand, D3.js is a Development product tagged with javascript, data-binding, svg, graphs, charts.

Its standout features include Data-Driven DOM Manipulation, Powerful Visualization Components, Animated Transitions, Highly Customizable and Flexible, Wide Browser Support, and it shines with pros like Open source and free, Large and active community support, Integrates well with other JS libraries, High performance with canvas rendering, Supports large datasets and real-time updates.

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.

ggvis

ggvis

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.

Categories:
Data Visualization Interactive Graphics
r ggplot2 interactive data-visualization graphics web-browser

Ggvis Features

  1. Grammar of Graphics-based visualization using the ggplot2 API
  2. Interactivity through linking graphical elements to data
  3. Built on top of Shiny for reactive programming
  4. Can embed plots in R Markdown documents and Shiny apps
  5. Supports faceting, zooming, panning, etc.
  6. Exporting plots to SVG and PNG format

Pricing

  • Open Source

Pros

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

Cons

Limited adoption compared to static ggplot2

Interactivity requires knowledge of reactivity in Shiny

Less customizable than D3.js for web-based graphics

D3.js

D3.js

D3.js is a JavaScript library for visualizing data with HTML, SVG, and CSS. It allows developers to bind arbitrary data to DOM elements and apply data-driven transformations to the document. Common uses are for creating interactive graphs, charts, maps, and data visualizations.

Categories:
Development Data Visualization
javascript data-binding svg graphs charts

D3.js Features

  1. Data-Driven DOM Manipulation
  2. Powerful Visualization Components
  3. Animated Transitions
  4. Highly Customizable and Flexible
  5. Wide Browser Support

Pricing

  • Open Source

Pros

Open source and free

Large and active community support

Integrates well with other JS libraries

High performance with canvas rendering

Supports large datasets and real-time updates

Cons

Steep learning curve

Complex documentation

Requires knowledge of SVG

Not optimized for mobile platforms

Version 3.0 has breaking changes from 2.0