pygal
manga-page-count
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| pygal | manga-page-count | |
|---|---|---|
| 3 | 1 | |
| 2,600 | 0 | |
| 0.3% | - | |
| 7.7 | 0.0 | |
| 3 months ago | over 3 years ago | |
| Python | HTML | |
| GNU Lesser General Public License v3.0 only | - |
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.
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)
manga-page-count
What are some alternatives?
matplotlib - matplotlib: plotting with Python
pytmangadex - an library to scrape data from mangadex.org
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
Altair - Declarative statistical visualization library for Python
bqplot - Plotting library for IPython/Jupyter notebooks
GooPyCharts - A Google Charts API for Python, meant to be used as an alternative to matplotlib.
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
ggplot - ggplot port 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.