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GIMP VS Matplotlib

Compare GIMP VS Matplotlib and see what are their differences

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

GIMP logo GIMP

GIMP is a multiplatform photo manipulation tool.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • GIMP Landing page
    Landing page //
    2018-09-30
  • Matplotlib Landing page
    Landing page //
    2023-06-14

GIMP features and specs

  • Free and Open Source
    GIMP is completely free to use and open source, allowing users to download, modify, and distribute the software without any cost.
  • Cross-Platform Compatibility
    GIMP is compatible with multiple operating systems including Windows, macOS, and Linux, providing flexibility for users on different platforms.
  • Extensive Plugin Support
    GIMP supports a wide range of plugins, which can be used to enhance functionality and customize the software to suit specific needs.
  • Powerful Editing Tools
    GIMP offers a comprehensive set of image editing tools for tasks such as photo retouching, image composition, and image authoring, suitable for both beginners and advanced users.

Possible disadvantages of GIMP

  • Complex Interface
    The user interface can be overwhelming and not as intuitive as other commercial software, which can pose a steep learning curve for new users.
  • Performance Issues
    Some users experience performance issues, such as slow rendering times, especially when working with large files or applying multiple layers and effects.
  • Limited Professional Features
    Compared to industry-standard software like Adobe Photoshop, GIMP lacks some advanced features and tools that professionals might need for high-end work.
  • Inconsistent Updates
    Updates and new features can be inconsistent, as the development relies on a community of volunteers rather than a dedicated team.

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 GIMP

Overall verdict

  • GIMP is generally considered a good alternative to commercial image editing software, especially for those who are looking for a cost-effective solution. While it may not have all the advanced features or polished interface of some paid options, it is powerful enough for most editing tasks and keeps improving with regular updates.

Why this product is good

  • GIMP (GNU Image Manipulation Program) is a free and open-source image editor that offers a wide range of tools and features for photo retouching, image composition, and image authoring. It is highly customizable and supports various plugins, making it a flexible option for different design needs. Its active community provides extensive support and resources for users.

Recommended for

    GIMP is recommended for beginners, hobbyists, and professionals who need a robust image editor without a financial commitment. It's suitable for users who are comfortable with learning open-source software and those who need a tool for basic to mid-level image editing tasks.

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.

GIMP videos

+ Add

Gimp vs Photoshop - Photo Editing Software - COMPARISON 2018

More videos:

  • Review - GIMP 2020 Preview and GIMP 2019 Recap
  • Review - 10 Reasons to Use GIMP in 2020 Over Photoshop

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to GIMP and Matplotlib)

GIMP

Matplotlib

Graphic Design Software
100 100%
Graphic Design Software
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Image Editing
100 100%
Image Editing
0% 0
Technical Computing
0 0%
Technical Computing
100% 100

User comments

Share your experience with using GIMP 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 GIMP and Matplotlib

GIMP Reviews

  1. Clipping Path universe
    ยท Working at Clipping Path ยท
    A great site

    This is a great site for photo editing and the software is supper.

    ๐Ÿ‘ Pros:    Trusted
12 Best Free PosterMyWall Alternatives and Competitors
You can use GIMP as a basic paint tool, a high-quality photo editor, a tool to process many images at once online, a way to make lots of images, or even to change the format of an image. GIMP can do even more because you can add extra features to it using plugins and extensions. You can make it do just about anything you like.
Source: mockey.ai
10 Best Photopea Software Alternatives in 2024 (Free & Paid)
There are 1,439 votes for GIMP and 14 votes for Photopea. GIMP gets 4.3/5, and Photopea gets 4.8/5. These rankings come from real user reviews and can help you choose between the two based on your industryโ€™s needs.
Source: www.geeksforgeeks.org
Best Adobe Photoshop alternatives of 2024
In our experience, GIMP was slightly less responsive and used a few more resources than its proprietary counterpart, but this can be easily forgiven on the basis that GIMP always has been and always will be free and open source.
Source: www.techradar.com
10 Best Adobe Illustrator Alternatives
Check out GIMP, one of the best free Illustrator alternatives which is ideal for any creative.
Source: www.ebaqdesign.com
16+ Best Web Design Software in 2022 (Ranked by a Trusted Expert)
GIMP stands for GNU Image Manipulation Program. Itโ€™s a free and open-source software for editing images and a valuable tool to have in your arsenal.
Source: onehourprofessor.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 GIMP. 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.

GIMP mentions (59)

  • Yurt Calculator
    Image Creative Commons (CC) BY-SA-NC 2005-2017, developed, designed and written by Renรฉ K. Mรผller Graphics & illustrations made with Inkscape, Tgif, Gimp, PovRay, GD.pm Web-Site powered by FreeBSD & Debian/Linux - 100% Open Source. Source: about 3 years ago
  • I just cannot understand why they did Paint so bad
    Paint.NET for a familiar paradigm with nicer features. Pinta for an old school, simple Paint experience. Krita for more advanced drawing. Gimp for editing/manipulating photos. Source: over 3 years ago
  • Had to make This after seeing all the post over and over again
    If you don't want to pay for photoshop, check out the Gnu Image Manipulation Program at http://gimp.org which is free. It has most of what you'd want photoshop for. Source: over 3 years ago
  • Super, just Super.
    As good as this suggestion is, without proper links and explanation it means nothing. GEGL is a type of plugins for GIMP, which can adjust the settings of already present effects and create new ones. The most notable ones are made by LinuxBeaver. Source: over 3 years ago
  • Useful apps for Ux designers
    GIMP: FOSS alternative to Photoshop. Like Inkscape, itโ€™s not directly related to UI, but might be handy. 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 / 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 / 7 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 / 8 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 GIMP and Matplotlib, you can also consider the following products

Adobe Photoshop - Adobe Photoshop is a webtop application for editing images and photos online.

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

Krita - Krita is a professional FREE and open source painting program. It is made by artists that want to seaffordable art tools for everyone. Concept art. texture and matte painters, illustrations and comics.

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

Affinity Photo - Affinity is the imaging and design suite for creative professionals exclusively for Mac.

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

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