GR
pygal
GR | pygal | |
---|---|---|
- | 3 | |
326 | 2,600 | |
0.0% | 0.3% | |
9.4 | 7.7 | |
9 days ago | 3 months ago | |
C | Python | |
GNU General Public License v3.0 or later | GNU Lesser General Public License v3.0 only |
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GR
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Tracking mentions began in Dec 2020.
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?
matplotlib - matplotlib: plotting with Python
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
VisPy - Main repository for Vispy
bokeh - Interactive Data Visualization in the browser, from Python
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
seaborn - Statistical data visualization in Python
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
Altair - Declarative statistical visualization library for Python
bqplot - Plotting library for IPython/Jupyter notebooks