plotly
pygal
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plotly | pygal | |
---|---|---|
65 | 3 | |
15,201 | 2,598 | |
2.0% | 0.2% | |
9.4 | 7.7 | |
7 days ago | 3 months ago | |
Python | Python | |
MIT License | 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.
plotly
- Yes, Python and Matplotlib can make pretty charts
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/plotly/plotly.py
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How to Create a Pareto Chart 📐
First we need to install the Plotly. To create some very dynamic graphics, this tool helps a lot.
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For all you computational people: What’s your favorite plotting software?
my good dude wake up and smell the plotly. Knowing the ins and outs of matplotlib is helpful but doing interactive stuff with jupyter I always use plotly.
- What does Power BI offer?
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Other programing options?
Plotly documentation (https://plotly.com/python/)
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Advice on upgrading my Presentation template
I don´t know your workflow, but I use 2 markdown based presentations: obsidian advance slides and Quarto presentations. The former is a plugin for Obsidian, which is the software I use to take all my notes, write my thesis, etc., so It makes it extremely easy to make presentations since all my information is in Obsidian. In the other hand, Quarto is a publishing system (articles, presentations, websites books) that can be easily integrated with python and R. This makes it supper convenient for showing my data to my PI since I can analyze my data and at the same time make a presentation for the data. Besides this, Quarto also integrates with my Zotero library, so I can insert citations. Lastly, one thing that made my Quarto presentations infinitely better that the powerpoints, Is that I can insert interactive graphs with plotly, so when I'm showing my data, my PI is able to explore the data inside the presentation.
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[OC] Clustering Images with OpenAI CLIP, T-SNE, UMAP & Plotly
Plotly GitHub repository: https://github.com/plotly/plotly.py
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Could you recommend some graphing GitHub Repo. for JupyterLab?
I'm using plotly.py now. This is why I love this community.
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Anyone else feel ‘trapped’ in power bi?
Depending on the nature of your reporting requirements, you could output a formatted Excel document with Python and a library such as openpyxl, and shove that into your SharePoint environment. This would be less dynamic than PBI reports can be, but may be sufficient. If you want viz as well, you can use something like ggplot or Plotly. Again, less dynamic than PBI for the same effort.
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?
Altair - Declarative statistical visualization library for Python
matplotlib - matplotlib: plotting with Python
bokeh - Interactive Data Visualization in the browser, from Python
seaborn - Statistical data visualization in Python
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
folium - Python Data. Leaflet.js Maps.
GooPyCharts - A Google Charts API for Python, meant to be used as an alternative to matplotlib.
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
bqplot - Plotting library for IPython/Jupyter notebooks