pygal
matplotlib
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| pygal | matplotlib | |
|---|---|---|
| 3 | 36 | |
| 2,600 | 19,262 | |
| 0.3% | 1.9% | |
| 7.7 | 10.0 | |
| 3 months ago | 3 days ago | |
| Python | Python | |
| GNU Lesser General Public License v3.0 only | Python License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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)
matplotlib
- How and where is matplotlib package making use of PySide?
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/matplotlib/matplotlib
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Tkinter, PyGame windows too large on Mac
as suggested here.
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[OC] Attempted & Completed Suicide Rate in Canada, 1998/99
Tool: Matplotlib Pyplot
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Help unpickling an old dataset
The issue was described here: https://github.com/matplotlib/matplotlib/issues/8409, but the "solution" was just "this is fixed" which was not helpful to me.
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The Python Packages That Gave Me Nightmares: A Guide to Overcoming Common Challenges
Matplotlib: Matplotlib is a 2D plotting library that allows you to create visualizations of your data. It's a powerful tool for data analysis, but the syntax can be complex and the customization options can be overwhelming. GitHub - https://github.com/matplotlib/matplotlib
- pcolormesh very slow when using "log" axes
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Question: What is matplotlib short for?
A quick google shows: this history.txt:
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Linear Regression
Let's take a small subset i.e 20 data points of our prediction and compare it with actual output using matplotlib library
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Where to find a dynamic charge density animation/simulation?
I will think more about what I want to say next, but for now, I would like to say that I need the super-particles and PIC methods as I think that is the way forward for me. Are there ways to implement these methods in matplotlib, Visit or Paraview? Do I take existing code and import it into those programs to visualize it? Or can I directly program/simulate something in those visualizion tools without needing to import any code?
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
bokeh - Interactive Data Visualization in the browser, from Python
seaborn - Statistical data visualization in Python
bqplot - Plotting library for IPython/Jupyter notebooks
Altair - Declarative statistical visualization library for Python
plotnine - A Grammar of Graphics for Python
GooPyCharts - A Google Charts API for Python, meant to be used as an alternative to matplotlib.
VisPy - Main repository for Vispy