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Matplotlib VS Dillinger

Compare Matplotlib VS Dillinger and see what are their differences

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Matplotlib logo Matplotlib

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

Dillinger logo Dillinger

joemccann has 95 repositories available. Follow their code on GitHub.
  • Matplotlib Landing page
    Landing page //
    2023-06-14
  • Dillinger Landing page
    Landing page //
    2024-10-09

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.

Dillinger features and specs

  • Real-time Markdown Rendering
    Dillinger provides live rendering of Markdown text, allowing users to see a side-by-side preview of their formatted text.
  • Cloud Integration
    It offers integration with cloud services like Dropbox, Google Drive, OneDrive, and GitHub, making it easy to save and manage documents.
  • User-friendly Interface
    The platform boasts an intuitive and clean interface, which makes it easy for both beginners and experienced users to navigate and use effectively.
  • Export Options
    Dillinger supports exporting documents in multiple formats, including Markdown, HTML, and PDF, providing flexibility in how users can use their content.
  • Open Source
    As an open-source platform, Dillinger allows developers to contribute to the project or customize the tool for their specific needs.

Possible disadvantages of Dillinger

  • Limited Offline Support
    Dillinger is primarily a web-based application and requires an internet connection for full functionality, limiting its usability offline.
  • Basic Markdown Features
    While it covers the basics well, advanced Markdown features or plugins might be missing compared to more comprehensive editors.
  • Dependency on External Services
    Heavy reliance on third-party cloud services may be a drawback for users who prefer to keep their data localized or have privacy concerns.
  • No Native Desktop Application
    Dillinger does not offer a native desktop application, which might be a disadvantage for users who prefer or require desktop-based tools.
  • Limited Customization
    While the interface is user-friendly, it offers limited customization options in terms of themes and editor settings compared to some other Markdown editors.

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.

Analysis of Dillinger

Overall verdict

  • Dillinger is considered a good Markdown editor, especially for users who need a straightforward tool with cloud integration capabilities. Its user-friendly design and ability to handle Markdown documents effectively make it a reliable choice.

Why this product is good

  • Dillinger is a cloud-enabled, mobile-ready, offline-storage compatible, Markdown editor. It is known for its simplicity, ease of use, and ability to integrate with cloud storage services such as Dropbox, Google Drive, and GitHub. Users appreciate its clean interface and the ability to preview Markdown files in real-time. It also supports exporting documents in formats like HTML and PDF.

Recommended for

    Dillinger is recommended for developers, writers, and anyone who frequently works with Markdown documentation. It's particularly useful for those who need access to their documents across different devices or want to store them in the cloud.

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Dillinger videos

The Dillinger Escape Plan - Dissociation ALBUM REVIEW

More videos:

  • Review - The Dillinger Escape Plan - One Of Us Is The Killer ALBUM REVIEW
  • Review - DILLINGER ESCAPE PLAN Dissociation Album Review | Overkill Reviews

Category Popularity

0-100% (relative to Matplotlib and Dillinger)
Data Science And Machine Learning
Markdown Editor
0 0%
100% 100
Technical Computing
100 100%
0% 0
Text Editors
0 0%
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 Matplotlib and Dillinger

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...

Dillinger Reviews

We have no reviews of Dillinger yet.
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Social recommendations and mentions

Based on our record, Matplotlib should be more popular than Dillinger. It has been mentiond 114 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.

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
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Dillinger mentions (27)

  • 5 Killer FREE Markdown Editors You Need in 2025
    Dillinger (Online - https://dillinger.io/): For a straightforward online experience, Dillinger is a solid choice. It offers split-screen viewing with live preview and supports saving to various platforms. It's a no-frills option that gets the job done efficiently. - Source: dev.to / 12 months ago
  • Markdown Syntax & Features: A Comprehensive 2025 Guide
    Dillinger - A cloud-enabled, mobile-ready, offline-storage, AngularJS-powered, HTML5 Markdown editor. - Source: dev.to / over 1 year ago
  • 100+ Must-Have Web Development Resources
    Dillinger: An online editor that offers cloud storage and supports various export formats like HTML5 and PDF. - Source: dev.to / almost 2 years ago
  • Converting Markdown to PDF
    Simply access https://dillinger.io and paste your markdown code there. It has the option to export to PDF, as well as some other formats. - Source: dev.to / almost 2 years ago
  • Building a simple but scalable blog using Astro
    I have used Markdown before (https://dillinger.io/) so wouldn't have a problem with using it again as long as on page SEO isn't any extra effort. I am not sure how I would use Markdown and then add the content to the blog to be deployed and if that is going to be much harder than a headless CMS, I would go for the headless. Source: over 2 years ago
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What are some alternatives?

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

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

Typora - A minimal Markdown reading & writing app.

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

StackEdit - Full-featured, open-source Markdown editor based on PageDown, the Markdown library used by Stack Overflow and the other Stack Exchange sites.

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

Markdown by DaringFireball - Text-to-HTML conversion tool/syntax for web writers, by John Gruber