Altair
vega-lite
Altair | vega-lite | |
---|---|---|
43 | 17 | |
8,946 | 4,509 | |
1.1% | 1.5% | |
9.0 | 9.2 | |
6 days ago | 2 days ago | |
Python | TypeScript | |
BSD 3-clause "New" or "Revised" 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.
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.
vega-lite
- FLaNK-AIM Weekly 06 May 2024
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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.
- Vega-Lite – A Grammar of Interactive Graphics
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Vega-Altair: Declarative Visualization in Python
Box zoom would need to be added to Vega-Lite first, and there has been some discussion around it in https://github.com/vega/vega-lite/issues/4742. Bottom line is that there's nothing blocking its implementation, someone just needs to do the work in Vega-Lite. And once released in Vega-Lite, Altair would pick it up automatically with how we generate the Altair API from the Vega-Lite schema.
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Gnuplotlib: Non-Painful Plotting for NumPy
I also have difficulties with Gnuplot and Matplotlib. I like Vega that allows me to create visualisations in a declarative way. If I really need something special I go with d3.js, which had a really steep learning curve but with ChatGPT it should have become easier for beginners.
[1] https://vega.github.io/vega-lite/
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Elixir Livebook is a secret weapon for documentation
To ensure you do not miss this: LiveBook comes with a Vega Lite integration (https://livebook.dev/integrations -> https://livebook.dev/integrations/vega-lite/), which means you get access to a lot of visualisations out of the box, should you need that (https://vega.github.io/vega-lite/).
In the same "standing on giant's shoulders" stance, you can use Explorer (see example LiveBook at https://github.com/elixir-explorer/explorer/blob/main/notebo...), which leverages Polars (https://www.pola.rs), a very fast DataFrame library and now a company (https://www.pola.rs/posts/company-announcement/) with 4M$ seed.
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Observable Plot: The JavaScript library for exploratory data visualization
Nice, would be nice to have it integrated in GitHub markdown.
Looks similar to Vega or Vega-lite(https://vega.github.io/vega-lite/). Definitely as rich as D3.js but gets the job done for simple visualisations.
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[AskJS] Javascript statistics library with period selection
Vega-lite can do this https://vega.github.io/vega-lite/
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2022 FIFA World Cup finishing position probability per team [OC]
The underlying data is from an online betting site. Data analysis was done in Python and I used Vega/Altair for the visualisation.
What are some alternatives?
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
graphic-walker - An open source alternative to Tableau. Embeddable visual analytic
bokeh - Interactive Data Visualization in the browser, from Python
vega-tooltip - Tooltip Plugin for Vega-Lite
seaborn - Statistical data visualization in Python
lightning - High performance, interactive statistical graphics engine for the web.
ggplot - ggplot port for python
py4cl2 - Call python from Common Lisp
plotnine - A Grammar of Graphics for Python
d3 - Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:
matplotlib - matplotlib: plotting with Python
ggplot2 - An implementation of the Grammar of Graphics in R