pandas-profiling
Altair
| pandas-profiling | Altair | |
|---|---|---|
| 1 | 43 | |
| 8,962 | 8,927 | |
| - | 0.8% | |
| 8.5 | 9.0 | |
| almost 2 years ago | 7 days ago | |
| Python | Python | |
| MIT License | BSD 3-clause "New" or "Revised" License |
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.
pandas-profiling
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Mito – Excel-like interface for Pandas dataframes in Jupyter notebook
For those who are going through the thread finding new tools: pandas-profiling[0] is a library for automatic EDA (part of what bamboolib[1] does).
[0]: https://github.com/pandas-profiling/pandas-profiling
Altair
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Ask HN: What's the best charting library for customer-facing dashboards?
I like Vega-Lite: https://vega.github.io/vega-lite/
It’s built by folks from the same lab as D3, but designed as “a higher-level visual specification language on top of D3” [https://vega.github.io/vega/about/vega-and-d3/]
My favorite way to prototype a dashboard is to use Streamlit to lay things out and serve it and then use Altair [https://altair-viz.github.io/] to generate the Vega-Lite plots in Python. Then if you need to move to something besides Python to productionize, you can produce the same Vega-Lite definitions using the framework of your choice.
- FLaNK AI Weekly 18 March 2024
- FLaNK AI for 11 March 2024
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Vega-Altair: Declarative Visualization in Python
Feel free to open an issue to let us know which parts of the documentation you find obscure and if you have suggestions for how to improve them. We did a larger overhaul a few months back and are always open to feedback on how to improve it further! https://altair-viz.github.io/
(disclaimer: I'm a co-maintainer of Altair)
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Gnuplotlib: Non-Painful Plotting for NumPy
Vega-Altair is pretty great as well. It uses a grammar of graphics that’s slightly different from ggplot, but has most of the same advantages.
https://altair-viz.github.io/
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Altair - Declarative statistical visualization library for Python.
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Top 10 growing data visualization libraries in Python in 2023
Github: Altair
- What python library you are using for interactive visualisation?(other than plotly)
- Libs para gráficos
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If you had to pick a library from another language (Rust, JS, etc.) that isn’t currently available in Python and have it instantly converted into Python for you to use, what would it be?
Yeah, that's one of the main reasons I like altair. It has 10M downloads per month and the newest Git update is from two days ago.
What are some alternatives?
lux - Automatically visualize your pandas dataframe via a single print! 📊 💡
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
barfi - Python Flow Based Programming environment that provides a graphical programming environment.
bokeh - Interactive Data Visualization in the browser, from Python
qgrid - An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks
seaborn - Statistical data visualization in Python
datasette - An open source multi-tool for exploring and publishing data
ggplot - ggplot port for python
data_algebra - Codd method-chained SQL generator and Pandas data processing in Python.
plotnine - A Grammar of Graphics for Python
python - 🚀 Curated collection of Amazing Python scripts from Basics to Advance with automation task scripts using Libraries and Logic. These things everyone should know in their journey with programming.
matplotlib - matplotlib: plotting with Python