Plotly vs ggvis

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

Plotly is a Data Visualization solution with tags like python, r, javascript, excel, data-analysis, data-visualization, interactive, charts, graphs, dashboards.

It boasts features such as Interactive data visualization, Support for Python, R, JavaScript, Excel, 2D and 3D plotting, Statistical charts, Dashboards, Collaboration tools, Exporting and sharing and pros including User-friendly, High-quality visualizations, Cross-platform compatibility, Open source and free, Large gallery of examples, Active community support.

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.

Plotly

Plotly

Plotly is an open-source graphing library for Python, R, JavaScript, and Excel. It allows users to create interactive, publication-quality graphs, charts, and dashboards that can be embedded in websites and apps. Plotly is useful for data analysis and visualization.

Categories:
Data Visualization Interactive Charting
python r javascript excel data-analysis data-visualization interactive charts graphs dashboards

Plotly Features

  1. Interactive data visualization
  2. Support for Python, R, JavaScript, Excel
  3. 2D and 3D plotting
  4. Statistical charts
  5. Dashboards
  6. Collaboration tools
  7. Exporting and sharing

Pricing

  • Freemium
  • Subscription-based

Pros

User-friendly

High-quality visualizations

Cross-platform compatibility

Open source and free

Large gallery of examples

Active community support

Cons

Steep learning curve

Limited customization compared to matplotlib

Online dependency for full functionality

Freemium pricing model limits features

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