Software Alternatives, Accelerators & Startups

ggplot2 VS Shiny

Compare ggplot2 VS Shiny and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

ggplot2 logo ggplot2

Application and Data, Libraries, and Charting Libraries

Shiny logo Shiny

Shiny is an R package that makes it easy to build interactive web apps straight from R.
  • ggplot2 Landing page
    Landing page //
    2023-02-27
  • Shiny Landing page
    Landing page //
    2023-06-30

ggplot2 features and specs

No features have been listed yet.

Shiny features and specs

  • Interactive Web Applications
    Shiny allows for the creation of interactive web applications directly from R, facilitating dynamic data visualization and user engagement without requiring extensive web development knowledge.
  • Ease of Use
    Shiny provides a high-level interface that allows users to create complex applications with minimal code, leveraging R's capabilities and intuitive declarative syntax.
  • Integration with R
    As a product of Posit (formerly RStudio), Shiny seamlessly integrates with the R ecosystem, enabling users to incorporate statistical analysis and machine learning models into their web applications.
  • Customizable UI
    Shiny offers a range of UI components and the ability to integrate custom HTML, CSS, and JavaScript, allowing for highly customized and polished web applications.
  • Reactive Programming
    Shiny’s reactive programming model simplifies the process of building interactive applications by automatically updating output whenever input changes, reducing the need for manual event handling.
  • Community Support
    Shiny has a large and active community, offering plentiful resources such as tutorials, examples, and forums for troubleshooting and learning.

Possible disadvantages of Shiny

  • Performance
    Shiny applications may suffer from performance issues, especially with large datasets or complex operations, as R is single-threaded by nature and may not handle high concurrency well.
  • Scalability
    Scaling Shiny applications to handle large numbers of users can be challenging and may require additional infrastructure, such as Docker containers or server clusters, and careful resource management.
  • Limited Language Support
    Shiny primarily supports R, which may be a limitation for teams or projects that rely on other languages for data analysis or web development.
  • Learning Curve
    Despite its user-friendly design, there is still a learning curve for users new to R or web development concepts, particularly when dealing with more advanced features or customizations.
  • Dependency Management
    Managing dependencies and ensuring version compatibility can become complex, particularly as applications grow in size and sophistication.
  • Deployment Complexity
    Deploying Shiny applications for production use can be complex, requiring knowledge of server environments, containerization, and continuous integration/continuous deployment (CI/CD) practices.

ggplot2 videos

Learn R: An Introduction to ggplot2

More videos:

  • Review - Review ggplot2 Line Graph Exercise
  • Review - Code-through and review of Ggplot2 in 2

Shiny videos

SHINY - PS4 REVIEW

More videos:

  • Review - My Opinion on EVERY Shiny Pokémon [Generation 1 to 7]
  • Review - Review: Shiny (PlayStation 4) - Defunct Games
  • Tutorial - R Shiny Overview & Tutorial

Category Popularity

0-100% (relative to ggplot2 and Shiny)
Technical Computing
100 100%
0% 0
Web Frameworks
0 0%
100% 100
Data Visualization
60 60%
40% 40
Developer Tools
0 0%
100% 100

User comments

Share your experience with using ggplot2 and Shiny. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare ggplot2 and Shiny

ggplot2 Reviews

5 Best Python Libraries For Data Visualization in 2023
ggplot is a system for creating graphics declaratively. It’s based on the Grammar of Graphics of R programming language and is tightly integrated with Pandas. ggplot just requires you to declare how to map the variables to aesthetics and primitives to use and handles the rest automatically. Remember, ggplot is not recommended for creating highly customized graphics.
Top 8 Python Libraries for Data Visualization
Ggplot is a Python data visualization library that is based on the implementation of ggplot2 which is created for the programming language R. Ggplot can create data visualizations such as bar charts, pie charts, histograms, scatterplots, error charts, etc. using high-level API. It also allows you to add different types of data visualization components or layers in a single...

Shiny Reviews

We have no reviews of Shiny yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Shiny should be more popular than ggplot2. It has been mentiond 34 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

ggplot2 mentions (11)

  • Ask HN: What plotting tools should I invest in learning?
    For random, quick and dirty, ad-hoc plotting tasks my default is GNUPlot[1]. Otherwise I tend to use either Python with matplotlib, or R with ggplot2. I keep saying I'm going to invest the time to properly learn D3[4] or something similar for doing web-based plotting, but somehow never quite seem to find time to do it. sigh [1]: http://www.gnuplot.info/ [2]: https://matplotlib.org/ [3]:... - Source: Hacker News / almost 2 years ago
  • Relative frequency of letters in five-letter English words (Wordle aid) [OC]
    I got the list of five-letter words from the words package in R, created the QWERTY keyboard grid with base R and tibble, and visualized the data with geom_tile in the ggplot2 package. Source: almost 2 years ago
  • [OC] U.S. News & World Report Best Colleges: 2002 to 2023
    Thanks, it's an interesting idea! I definitely could implement this with scale_fill_gradientn) in ggplot2. Source: almost 2 years ago
  • Facts about Aaron Boone's Ejections as Manager
    I used the ggplot2 package in R to create these figures. Source: almost 2 years ago
  • Fueling Innovation and Collaborative Storytelling
    This might not be at the top of your list, but science fiction often presents advanced data analysis and visualization technologies. Open source data analysis tools such as Python's Pandas and R's ggplot2 have revolutionized the field, making complex data manipulation and visualization accessible to all. In the science fiction novel The Martian, astronaut Mark Watney uses a variety of data analysis and... - Source: dev.to / almost 2 years ago
View more

Shiny mentions (34)

  • Big Book of R
    There is a lot of way and the most common is shiny (https://shiny.posit.co/) but with a biais towards data app. Not having a Django-like or others web stack python may have talks more about the users of R than the language per se. Its background was to replace S which was a proprietary statistics language not to enter competition with Perl used in CGI and early web. R is very powerful and is Lisp in disguise... - Source: Hacker News / 24 days ago
  • React for R
    In R, you can build Single Page Applications with Shiny, created by Posit https://shiny.posit.co/ It is very useful, if you don't know HTML,JS,CSS and want to create an interactive dashboard, showcasing your analysis, models, visualizations, or even to create an internal tool for your organization. It seems that reactR provides functions for building react components directly from R that can be used in Shiny apps. - Source: Hacker News / 8 months ago
  • R: Introduction to Data Science
    A lighterweight alternative to renv is to use Posit Public Package Manage (https://packagemanager.posit.co/) with a pinned date. That doesn't help if you're installing packages from a mix of places, but if you're only using CRAN packages it lets you get everything as of a fixed date. And of course on the web side you have shiny (https://shiny.posit.co), which now also comes in a python flavour. - Source: Hacker News / about 1 year ago
  • Reflex – Web apps in pure Python
    Sometimes the war is lost even before the battle begins. During grad school, I wrote a whole bunch of web apps entirely in R using Shiny. It was clunky as hell, but yeah, it worked. I went looking for what's up with Shiny these days and found this - https://shiny.posit.co/ So yeah, full on pivot into python. Pip install shiny. Alright! "No web development skills required. Develop web apps entirely in R I mean... - Source: Hacker News / almost 2 years ago
  • PSA: You don't need fancy stuff to do good work.
    Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: almost 2 years ago
View more

What are some alternatives?

When comparing ggplot2 and Shiny, you can also consider the following products

Matplotlib - matplotlib is a python 2D plotting library which produces publication quality figures in a variety...

Node.js - Node.js is a platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications

Plotly - Low-Code Data Apps

Django - The Web framework for perfectionists with deadlines

GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.

Ruby on Rails - Ruby on Rails is an open source full-stack web application framework for the Ruby programming...