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GoJS VS Matplotlib

Compare GoJS 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

GoJS logo GoJS

GoJS is a JavaScript library for building interactive diagrams on HTML web pages. Build apps with flowcharts, org charts, BPMN, UML, modeling, and other visual graph types.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • GoJS Landing page
    Landing page //
    2023-03-21
  • Matplotlib Landing page
    Landing page //
    2023-06-14

GoJS features and specs

  • Rich Feature Set
    GoJS offers a comprehensive set of features designed for creating interactive diagrams, charts, and complex visualizations. This includes node and link modeling, custom styling, data binding, automatic layouts, and more.
  • Extensive Documentation
    The library is well-documented, providing developers with thorough guides, a detailed API reference, and numerous examples to assist in the implementation and troubleshooting of applications.
  • High Performance
    GoJS is optimized for performance, enabling the creation of responsive web applications that can handle a large number of nodes and complex interactions efficiently.
  • Flexibility and Customization
    GoJS offers great flexibility, allowing developers to customize the appearance and behavior of diagrams entirely, which makes it suitable for a wide range of use cases.
  • Active Support and Community
    The GoJS team provides active support to users through their forum and is responsive to issues and feature requests. This is complemented by a growing community of users sharing insights and solutions.

Possible disadvantages of GoJS

  • Commercial Licensing
    GoJS is a commercial product, and while it offers a free trial, a license is required for sustained use. This might be a constraint for projects with limited budgets.
  • Steep Learning Curve
    Due to its extensive capabilities and myriad of options, there can be a steep learning curve for developers new to GoJS to understand and effectively use all its features.
  • Complexity for Simple Diagrams
    While GoJS is powerful for complex diagrams, it might be considered overkill for simpler visualizations, where a lightweight library might suffice.
  • Browser Compatibility
    Although modern browsers are generally supported, there might be some compatibility issues or performance differences to manage when targeting older or less common browsers.
  • File Size
    The library's comprehensive feature set comes with a relatively large file size, which could impact loading times, particularly in environments with limited bandwidth.

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 GoJS

Overall verdict

  • GoJS is considered a good choice for developers needing a versatile and feature-rich library for developing complex diagramming applications. Its performance, flexibility, and extensive support make it a reliable tool for both small and large-scale projects.

Why this product is good

  • GoJS is widely regarded as a powerful JavaScript and TypeScript library for building interactive diagrams and graphs. It offers a comprehensive set of features, including customizable templates, support for a variety of diagram types, and intuitive drag-and-drop functionality. The library is optimized for performance with large datasets and provides a robust API for creating complex visual representations. It also boasts thorough documentation and a range of examples to help developers get started quickly.

Recommended for

  • Developers working on data visualization apps
  • Teams creating interactive diagrams or flowcharts
  • Projects requiring complex and scalable diagram solutions
  • Organizations needing customizable and high-performance diagram libraries

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.

GoJS videos

+ Add

GoJS in 12 Minutes: JavaScript Diagramming Library Tutorial

More videos:

  • Tutorial - What's in a GoJS JavaScript Application? | GoJS Beginner Tutorial #1
  • Review - [GOJS] Design Patterns em Javascript

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to GoJS and Matplotlib)

GoJS

Matplotlib

Javascript UI Libraries
100 100%
Javascript UI Libraries
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Flowcharts
100 100%
Flowcharts
0% 0
Technical Computing
0 0%
Technical Computing
100% 100

User comments

Share your experience with using GoJS and Matplotlib. For example, how are they different and which one is better?
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Reviews

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

GoJS Reviews

20+ JavaScript libraries to draw your own diagrams (2022 edition)
GoJS offers many advanced features for user interactivity such as drag-and-drop, copy-and-paste, transactional state and undo management, palettes, overviews, data-bound models, event handlers, and an extensible tool system for custom operations. They provide over 150 interactive samples to help you get started with diagrams such as BPMN, flowchart, state chart, visual...
Source: modeling-languages.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, Matplotlib should be more popular than GoJS. 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.

GoJS mentions (13)

  • Ask HN: What do you use to create diagrams?
    Well I make https://gojs.net, so I just use the GoJS diagramming library to make diagrams :D Of course, its made for developers trying to make applications, not end users. - Source: Hacker News / over 1 year ago
  • Ask HN: What is the best software to visualize a graph with a billion nodes?
    My library (https://gojs.net) can do that easily. Give it a look, and if you think the price is acceptable for your project, contact us and we can make you a proof-of-concept. - Source: Hacker News / about 2 years ago
  • Your 14-Day Free Trial Ain't Gonna Cut It
    If you click on their username, it takes you to their profile. https://news.ycombinator.com/user?id=simonsarris. - Source: Hacker News / over 2 years ago
  • Burning money on paid ads for a dev tool โ€“ what we've learned
    Have spent six figures yearly on ads, mostly for reach for the developer-focused diagram library GoJS (https://gojs.net) > Each experiment will need ~$500 and 2 weeks I would add a zero if you want serious data. I would also double the timescale. $5,000 over 4 weeks I second the uselessness of Google Display, it might look like conversions numbers are good but they are 100% too good to be true. As soon as you look... - Source: Hacker News / almost 3 years ago
  • Any Ideas How to Create a Graph Builder UI in React?
    Used goJS in one project and konva in another. Source: 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 / 5 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 / 8 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 GoJS and Matplotlib, you can also consider the following products

mxGraph - mxGraph is a fully client side JavaScript diagramming library - jgraph/mxgraph

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

jsPlumb - jsPlumb is an advanced, standards-compliant and easy to use JS library for building connectivity based applications, such as flowcharts, process flow diagrams, sequence diagrams, organisation charts, etc. More than just a diagram library.

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

Konva - Konva is 2d Canvas JavaScript framework for drawings shapes, animations, node nesting, layering, filtering, event handling, drag and drop and much more.

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

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