Plotly vs ggvis

Professional comparison and analysis to help you choose the right software solution for your needs. Compare features, pricing, pros & cons, and make an informed decision.

Plotly icon
Plotly
ggvis icon
ggvis

Expert Analysis & Comparison

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.

Why Compare Plotly and ggvis?

When evaluating Plotly versus ggvis, both solutions serve different needs within the data visualization ecosystem. This comparison helps determine which solution aligns with your specific requirements and technical approach.

Market Position & Industry Recognition

Plotly and ggvis have established themselves in the data visualization market. Key areas include python, r, javascript.

Technical Architecture & Implementation

The architectural differences between Plotly and ggvis significantly impact implementation and maintenance approaches. Related technologies include python, r, javascript, excel.

Integration & Ecosystem

Both solutions integrate with various tools and platforms. Common integration points include python, r and r, ggplot2.

Decision Framework

Consider your technical requirements, team expertise, and integration needs when choosing between Plotly and ggvis. You might also explore python, r, javascript for alternative approaches.

Feature Plotly ggvis
Overall Score N/A N/A
Primary Category Data Visualization Data Visualization
Target Users Developers, QA Engineers QA Teams, Non-technical Users
Deployment Self-hosted, Cloud Cloud-based, SaaS
Learning Curve Moderate to Steep Easy to Moderate

Product Overview

Plotly
Plotly

Description: 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.

Type: Open Source Test Automation Framework

Founded: 2011

Primary Use: Mobile app testing automation

Supported Platforms: iOS, Android, Windows

ggvis
ggvis

Description: 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.

Type: Cloud-based Test Automation Platform

Founded: 2015

Primary Use: Web, mobile, and API testing

Supported Platforms: Web, iOS, Android, API

Key Features Comparison

Plotly
Plotly Features
  • Interactive data visualization
  • Support for Python, R, JavaScript, Excel
  • 2D and 3D plotting
  • Statistical charts
  • Dashboards
  • Collaboration tools
  • Exporting and sharing
ggvis
ggvis Features
  • 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

Pros & Cons Analysis

Plotly
Plotly
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
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

Pricing Comparison

Plotly
Plotly
  • Freemium
  • Subscription-based
ggvis
ggvis
  • Open Source

Get More Information

Plotly
Plotly
Plotly
Learn More About Plotly
ggvis
ggvis
ggvis
Learn More About ggvis

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