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JSFiddle VS Matplotlib

Compare JSFiddle VS Matplotlib and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

JSFiddle logo JSFiddle

Test your JavaScript, CSS, HTML or CoffeeScript online with JSFiddle code editor.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • JSFiddle Landing page
    Landing page //
    2022-07-11
  • Matplotlib Landing page
    Landing page //
    2023-06-14

JSFiddle features and specs

  • Easy Sharing and Collaboration
    JSFiddle allows users to share and collaborate on code snippets effortlessly by generating unique URLs for each project.
  • Real-Time Editing
    Changes made to HTML, CSS, and JavaScript are displayed in real-time, providing instant feedback and streamlining the development process.
  • Supports Multiple Frameworks
    JSFiddle supports various JavaScript frameworks and libraries such as jQuery, Vue.js, and React, allowing developers to experiment with different technologies.
  • Embed Feature
    Users can embed their fiddles directly into websites or blogs, enabling easy demonstration of code and concepts.
  • Version Control
    JSFiddle offers version control, allowing users to save different versions of their code and revert to previous versions if needed.

Possible disadvantages of JSFiddle

  • Limited Backend Support
    JSFiddle is primarily focused on frontend development and does not provide robust backend development capabilities.
  • Performance Issues
    With complex or resource-intensive projects, JSFiddle can experience performance lag, impacting the user experience.
  • Basic IDE Features
    Compared to full-fledged Integrated Development Environments (IDEs), JSFiddle lacks advanced features such as code linting, debugging tools, and extensive plugins.
  • File Management
    JSFiddle does not offer comprehensive file management, making it challenging to work on larger projects with multiple files.
  • Dependency Management
    Managing dependencies can be cumbersome, as JSFiddle does not provide built-in tools to handle package management seamlessly.

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of JSFiddle

Overall verdict

  • JSFiddle is a highly useful and reliable tool for web developers looking for a quick and easy way to test and share code snippets. Its ease of use and collaborative features make it a popular choice in the developer community.

Why this product is good

  • JSFiddle is widely used for testing and showcasing user-created HTML, CSS, and JavaScript code.
  • It provides a simple interface to quickly collaborate and share code snippets.
  • Real-time collaboration features make it easier to work with others.
  • Supports various JavaScript frameworks and extensions, enhancing flexibility.
  • Allows saving and managing public or private code snippets for future reference.

Recommended for

  • Web developers needing a fast way to prototype and demonstrate web functionality.
  • Educators and students in fields related to web development and programming.
  • Teams looking for an online collaborative platform for frontend code examples.
  • Individuals wanting to share code examples with others or ask for debugging help.

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

JSFiddle videos

+ Add

Dashboard JSFiddle Online JavaScript Editor jQuery, Angular, Backbone, Underscore, Knockout, Y

More videos:

  • Review - 1.3 Using JSFiddle to Create a Simple Web Page

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to JSFiddle and Matplotlib)

JSFiddle

Matplotlib

Text Editors
100 100%
Text Editors
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Programming
100 100%
Programming
0% 0
Technical Computing
0 0%
Technical Computing
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 JSFiddle and Matplotlib

JSFiddle Reviews

8 Best Replit Alternatives & Competitors in 2022 (Free & Paid) - Software Discover
Test your javascript, CSS, HTML or coffeescript online with jsfiddle code editor. Jsfiddle โ€“ code playground.
Source: www.softwarediscover.com
12 Best Online IDE and Code Editors to Develop Web Applications
JSFiddle cannot be used to host code on your server. The code has to be on JSFiddle and is public all the time.
Source: geekflare.com
6 Coding Playgrounds For Web Developers
What is missing from JSFiddle is live previews. You have to basically refresh the page by clicking on the play button. And compared to other playgrounds, JSFiddle is probably the slowest. Another slightly frustrating quirk of JSFiddle is its run button, sometimes clicking on it doesnโ€™t work, so youโ€™ll have to click a couple more times before it actually runs the code (and...
Source: www.hongkiat.com

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 doesnโ€™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, JSFiddle should be more popular than Matplotlib. It has been mentiond 203 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.

JSFiddle mentions (203)

  • HTML Made Easy: A Beginner-Friendly Introduction
    Coding is like learning a new languageโ€”you must practice by writing code, not just reading about it. Use free online editors like CodePen, JSFiddle, or Replit to experiment. - Source: dev.to / 12 months ago
  • Can I Build Useful Projects with Only HTML and CSS?
    As you embark on these projects, take your time to familiarize yourself with HTML tags and CSS properties. Use online tools like CodePen or JSFiddle to experiment with your code and visualize your results. - Source: dev.to / about 1 year ago
  • Imagine telling 2010 devs that in 2025, collapsing a div would require $8M
    > This specific example, https://jsfiddle.net, is not a monopoly and has many suitable replacements (e.g. https://livecodes.io/, https://liveweave.com). The other two don't even have sidebars... They are suitable replacements in the same way that crickets are a suitable replacement for beef โ€“ It'll get the job done. But often the customer wants more, like the whole experience, and jsfiddle does have a... - Source: Hacker News / over 1 year ago
  • HTML Basics: A Beginner's Guide
    Open a code editor (or an online editor like CodePen or JSFiddle) and try this:. - Source: dev.to / over 1 year ago
  • Embedding JSFiddle in dev.to Articles
    Save your work to get a unique URL like https://jsfiddle.net/yourusername/yourfiddleID/. - Source: dev.to / over 1 year ago
View more

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 10 months ago
View more

What are some alternatives?

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

CodePen - A front end web development playground.

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

CodeSandbox - Online playground for React

NumPy - NumPy is the fundamental package for scientific computing with Python

Pastebin.com - Pastebin.com is a website where you can store text for a certain period of time.

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.

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