bokeh
pygal
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| bokeh | pygal | |
|---|---|---|
| 24 | 3 | |
| 18,812 | 2,598 | |
| 1.0% | 0.2% | |
| 9.5 | 7.7 | |
| 6 days ago | 3 months ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License |
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.
bokeh
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Bokeh - Interactive Web Plotting for Python.
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/bokeh/bokeh
- Bokeh Python Library for Interactive Visualizations
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Best data visualisation library
If you don’t mind passing html around this library allows you to share full interactive plot:
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Emerging Rust GUI libraries in a WASM world
It sounds like you want BokehJS. It was one of the alternatives I was recommended while I was exploring, but for various reasons my particular use case is not so easy to integrate (plus my backend was already in Rust).
https://github.com/bokeh/bokeh
I did do a basic test, and the raw rects-on-screen performance is roughly comparable to my final solution.
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What Python modules can I use to create my own indicators? Like the indicator below, I very new to Python so please don’t be rude
I just came across this: https://bokeh.org/
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Interactive plots
Take a look at Bokeh. https://bokeh.org/
- December goals
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[OC] The Criminal Podcast's intros have gotten longer over time
I recorded all 200 "I'm Phoebe Judge, this is Criminal" intros from the Criminal podcast, measured the length, and plotted using python's Bokeh package.
- What's the most scalable visualization library?
pygal
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ECharts for Python
> There is a snapshot library for pyecharts that allows you to convert the HTML produced by the library into formats like JPEG, PNG, PDF and SVG.
One alternative is Pygal: https://github.com/Kozea/pygal/
Even though the library is not actively "developed" but it is a complete library in my opinion.
I feel like with d3.js and eCharts, modern data visualization requires you to run analytics processes first then outputting a JSON then writing the visualization code with JavaScript.
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Homebrew Crafting rules and analysis
I used Pygal to generate the charts, and it uses a unique colour per dataset, so 20 colours for each level. I just didn't see a need to change it.
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[OC] I created graphs that show the page count per chapter for the top 20 most popular manga on MyAnimeList. (Notes and interactive charts in comments)
pygal (To generate the png and interactive charts)
What are some alternatives?
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
matplotlib - matplotlib: plotting with Python
seaborn - Statistical data visualization in Python
Altair - Declarative statistical visualization library for Python
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
bqplot - Plotting library for IPython/Jupyter notebooks
folium - Python Data. Leaflet.js Maps.
GooPyCharts - A Google Charts API for Python, meant to be used as an alternative to matplotlib.