GooPyCharts
pygal
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GooPyCharts | pygal | |
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0 | 3 | |
205 | 2,598 | |
- | 0.3% | |
0.0 | 7.7 | |
over 6 years ago | about 2 months ago | |
Python | Python | |
Apache License 2.0 | GNU Lesser General Public License v3.0 only |
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GooPyCharts
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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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[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!
bokeh - Interactive Data Visualization in the browser, from Python
seaborn - Statistical data visualization in Python
SnakeViz - An in-browser Python profile viewer
Altair - Declarative statistical visualization library for 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.
bqplot - Plotting library for IPython/Jupyter notebooks
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
ggplot - ggplot port for python