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Shiny VS Matplotlib

Compare Shiny VS Matplotlib and see what are their differences

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  2. » Videos
  3. » Reviews
  4. » Alternatives

Shiny logo Shiny

Shiny is an R package that makes it easy to build interactive web apps straight from R.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Shiny Landing page
    Landing page //
    2023-06-30
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Shiny videos

+ Add

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

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Shiny and Matplotlib)

Shiny

Matplotlib

Web Frameworks
100 100%
Web Frameworks
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
Developer Tools
100 100%
Developer Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100

User comments

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Reviews

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

Shiny Reviews

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Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
Source: www.technotification.com
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Source: searchbusinessanalytics.techtarget.com
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesn’t support all file formats.
Source: www.analyticsvidhya.com
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...
Source: www.geeksforgeeks.org

Social recommendations and mentions

Based on our record, Matplotlib should be more popular than Shiny. It has been mentiond 98 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.

Shiny mentions (32)

  • 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 / 3 months 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 / 10 months 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: about 1 year ago
  • A project to show off my basic R skills
    We work along side bio-statisticians and data analysts, from my experience in this world I recommend to build some plots/graphs in R based on some information you find appealing. After you have some work to show off to potential employers , learn Shiny and publish those graphs online as your portfolio. Source: about 1 year ago
  • Greatest projects that you have done?
    One of the most difficult yet most fun projects I’ve done. Using Shiny to make an app, all coded in R! Source: over 1 year ago
View more

Matplotlib mentions (98)

  • Implementing semantic image search with Amazon Titan and Supabase Vector
    Matplotlib: for displaying our image result. - Source: dev.to / about 2 months ago
  • Releasing The Force Of Machine Learning: A Novice’s Guide 😃
    Matplotlib: Acomprehensive library for creating static, animated, and interactive visualizations in Python. - Source: dev.to / 3 months ago
  • How to retrieve and analyze crypto order book data using Python and a cryptocurrency API
    Data visualization: utilizing Python's Matplotlib for visualizing order book information. - Source: dev.to / 6 months ago
  • 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 / 10 months 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: about 1 year ago
View more

What are some alternatives?

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

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

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

Django - The Web framework for perfectionists with deadlines

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

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

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

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