Software Alternatives, Accelerators & Startups

CodeBeautify VS Matplotlib

Compare CodeBeautify VS Matplotlib and see what are their differences

CodeBeautify logo CodeBeautify

Online Tools like Beautifiers, Editors, Viewers, Minifier, Validators, Converters for Developers: XML, JSON, CSS, JavaScript, Java, C#, MXML, SQL, CSV, Excel

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • CodeBeautify Landing page
    Landing page //
    2023-05-07
  • Matplotlib Landing page
    Landing page //
    2023-06-14

CodeBeautify features and specs

  • User-Friendly Interface
    The platform provides an intuitive and easy-to-navigate interface, which makes it accessible for both beginners and experienced users.
  • Wide Range of Tools
    CodeBeautify offers a variety of tools for different programming tasks, such as code formatting, validation, and conversion for multiple languages.
  • No Installation Required
    Being a web-based tool, CodeBeautify does not require any software installation, allowing for quick access and use directly from the browser.
  • Free to Use
    Many of the tools and features on CodeBeautify are available for free, making it an economical choice for developers.
  • Cross-Platform Compatibility
    Since it's a web-based platform, it works on any operating system with a modern web browser, offering flexibility across different devices.

Possible disadvantages of CodeBeautify

  • Internet Dependency
    As an online tool, CodeBeautify requires an active internet connection, which may be a limitation in areas with poor connectivity.
  • Limited Offline Support
    CodeBeautify does not offer offline capabilities, restricting its use in situations where internet access is unavailable.
  • Potential Privacy Concerns
    As with any online platform, there may be privacy concerns related to data that is processed in the cloud.
  • Performance Limitations
    Web-based tools might not perform as efficiently as dedicated desktop applications for large-scale projects or very complex tasks.
  • Ads and Distractions
    The free version of CodeBeautify might include advertisements, which can be distracting for users trying to focus on their coding tasks.

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 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.

CodeBeautify videos

No CodeBeautify videos yet. You could help us improve this page by suggesting one.

Add video

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to CodeBeautify and Matplotlib)
Developer Tools
100 100%
0% 0
Data Science And Machine Learning
Productivity
100 100%
0% 0
Technical Computing
0 0%
100% 100

User comments

Share your experience with using CodeBeautify and Matplotlib. 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 CodeBeautify and Matplotlib

CodeBeautify Reviews

  1. James Malvi
    ยท Tech Lead at EINFOCHIPS LTD ยท
    Amazing site for developers

    It has tons of tools for developers with lots of bells and whistles

    ๐Ÿ‘ Pros:    Super simple|Super fast|Clean ui
    ๐Ÿ‘Ž Cons:    Should have better search functionality for site

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.
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.
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.
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...

Social recommendations and mentions

Based on our record, Matplotlib seems to be a lot more popular than CodeBeautify. While we know about 114 links to Matplotlib, we've tracked only 6 mentions of CodeBeautify. 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.

CodeBeautify mentions (6)

  • 22 Unique Developer Resources You Should Explore
    URL: https://codebeautify.org What it does: A suite of tools for formatting, beautifying, and validating JSON, XML, HTML, and CSS. Why it's great: Say goodbye to messy code! It ensures your files are clean and error-free. - Source: dev.to / over 1 year ago
  • Top 5 best JavaScript beautifier in 2025 | All-time-dev
    It is a very good website that provides different tools like JSON and JavaScript beautifier, SEO inspector which I personally use, and also recommend, and more tools it provides for different types of users. They also provide beautifiers for XML, CSS, and more languages and their JavaScript beautifier supports more different languages like JavaScript, Java, and XML, and more languages and frameworks like jQuery,... - Source: dev.to / over 1 year ago
  • 19 Handy Websites for Web Developers
    Code Beautify is a handy tool for developers looking to format and beautify their code. It improves code readability and maintainability, contributing to better collaboration and understanding among team members. - Source: dev.to / over 2 years ago
  • Top 10 Websites Every Developer Needs to Know About
    CodeBeautify is an online Code Beautifier and Code Formatter that allows you to beautify your source code. Along with this feature, it also supports some converters such as Image to base64, not only this it has tons of functionality as shown in the following image:. - Source: dev.to / about 3 years ago
  • zkSync Mainnet Guid
    We go to this site - https://codebeautify.org/ and paste the copied CID phrase as in the screenshot. Then we download the file. - Source: dev.to / over 3 years 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 / 6 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 / 9 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 / 9 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 / 10 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 / 11 months ago
View more

What are some alternatives?

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

iLovePDF - Premium online PDF tool set

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

10015.io - 10015.io is an all-in-one toolbox offering many tools from various categories.

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

JSONFormatter.org - Online JSON Formatter and JSON Validator will format JSON data, and helps to validate, convert JSON to XML, JSON to CSV. Save and Share JSON

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