VisPy
matplotlib
| VisPy | matplotlib | |
|---|---|---|
| 6 | 39 | |
| 3,515 | 22,140 | |
| 0.8% | 1.1% | |
| 7.8 | 9.9 | |
| 8 days ago | 4 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Python License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
VisPy
- Help shape the future of VisPy 2.0 – ideas, feedback, and contributors welcome
- Pygfx
- Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
VisPy - High-performance scientific visualization based on OpenGL.
- Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/vispy/vispy
- Seeking library recommendation for 3D visualization of crystal structure
Two similar alternatives you could look at are PyVista which is based on the same framework as Mayavi and VisPy. Mayavi is strongly dependent on the whole Enthought suite which can be a disadvantage if you don’t really use its abilities.
- Show HN: MPL Plotter – Python library to make technical plots more efficiently
2. I recommend Datashader (https://datashader.org/) (HoloViz is super cool) and Vispy (https://vispy.org/). I found Vispy's documentation a bit lacking some time ago, but they probably have improved it since then, and it's very capable. Lastly, check Taichi (https://taichi.graphics/), might not be a conventional data representation library (or rather, not only), but it's amazing and worth a look.
To add some more depth to the Seaborn comparison, and not being an expert Seaborn user, I'd say:
1. MPL Plotter is lighter (but also with less wide-ranging plot options)
matplotlib
- How to Get Started with Scikit-Learn: A Beginner-Friendly Guide to Machine Learning in Python
As is the case with most Python libraries, it is open-source and free-to-use, making it easily accessible by anyone willing to learn machine learning, and it is built upon other open-source libraries within Python, like SciPy for advanced scientific operations, NumPy for efficient numerical computations, Matplotlib for data visualization, and Cython for increased efficiency and speed, similar to that of C/C++.
- BUILDING DATA VISUALIZATION WITH PYTHON: A BEGINNER'S GUIDE TECHNIQUES
The source code for Matplotlib is located at this github repository https://github.com/matplotlib/matplotlib
- Using Rust to corrode insane Python run-times
Difficult to draw conclusions with no code here.
An interesting thing they didn't mention is that Matplotlib's point-in-path code is actually already in C. So this isn't really a case of Rust being X times faster than Python, it's X times faster than some other C algorithm. That's probably why X is only ~4 (they don't actually give a single-thread comparison), instead of ~50.
https://github.com/matplotlib/matplotlib/blob/cb487f3c077c93...
I expect the Rust code is faster because that code is waaaaay more complicated than what they probably need (https://stackoverflow.com/q/11716268/265521) - e.g. it handles stroke widths.
IMO this result is not very interesting.
- How and where is matplotlib package making use of PySide?
- Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/matplotlib/matplotlib
- Tkinter, PyGame windows too large on Mac
as suggested here.
- [OC] Attempted & Completed Suicide Rate in Canada, 1998/99
Tool: Matplotlib Pyplot
- Help unpickling an old dataset
The issue was described here: https://github.com/matplotlib/matplotlib/issues/8409, but the "solution" was just "this is fixed" which was not helpful to me.
- The Python Packages That Gave Me Nightmares: A Guide to Overcoming Common Challenges
Matplotlib: Matplotlib is a 2D plotting library that allows you to create visualizations of your data. It's a powerful tool for data analysis, but the syntax can be complex and the customization options can be overwhelming. GitHub - https://github.com/matplotlib/matplotlib
- pcolormesh very slow when using "log" axes
What are some alternatives?
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
pyvista - 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK)
plotly - The interactive graphing library for Python :sparkles:
bokeh - Interactive Data Visualization in the browser, from Python