ipyvizzu
VisPy
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| ipyvizzu | VisPy | |
|---|---|---|
| 7 | 4 | |
| 923 | 3,213 | |
| 1.6% | 0.7% | |
| 9.1 | 8.8 | |
| about 2 months ago | 3 days ago | |
| Jupyter Notebook | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
ipyvizzu
- IPyVizzu: Build animated charts with simple Python syntax
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Show HN: Build, present and share animated data stories in Jupyter Notebook
We built this presentation extension of our open-source charting tool ipyvizzu (https://github.com/vizzuhq/ipyvizzu) because we learnt from the interviews and feedback from data scientists that they struggle with presenting and sharing the results of their analysis with less tech savvy people.
Here's a live example: https://vizzuhq.github.io/ipyvizzu-story/examples/demo/ipyvi...
What do you think?
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Hacker News top posts: Apr 3, 2022
Show HN: ipyvizzu – open-source animated charts in Jupyter Notebooks\ (0 comments)
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Show HN: Ipyvizzu – animated charts in Jupyter Notebooks
Not yet, unfortunately, I've opened an issue in our tracker for slideshow support: https://github.com/vizzuhq/ipyvizzu/issues/102
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ipyvizzu - create animated charts in Jupyter Notebook using Python with this open-source tool
More info, tutorial & examples: https://github.com/vizzuhq/ipyvizzu
VisPy
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
VisPy - High-performance scientific visualization based on OpenGL.
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/vispy/vispy
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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.
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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)
What are some alternatives?
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
matplotlib - matplotlib: plotting with Python
folium - Python Data. Leaflet.js Maps.
dash - Data Apps & Dashboards for Python. No JavaScript Required.
pyrender - Easy-to-use glTF 2.0-compliant OpenGL renderer for visualization of 3D scenes.
ggplot - ggplot port for python
bokeh - Interactive Data Visualization in the browser, from Python
Flask JSONDash - :snake: :bar_chart: :chart_with_upwards_trend: Build complex dashboards without any front-end code. Use your own endpoints. JSON config only. Ready to go.