FLaNKAI-Boston
vega-lite
| FLaNKAI-Boston | vega-lite | |
|---|---|---|
| 5 | 17 | |
| 2 | 4,532 | |
| - | 1.2% | |
| 6.8 | 9.2 | |
| 29 days ago | 11 days ago | |
| HTML | TypeScript | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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FLaNKAI-Boston
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?
frawk - an efficient awk-like language
graphic-walker - An open source alternative to Tableau. Embeddable visual analytic
grobid - A machine learning software for extracting information from scholarly documents
vega-tooltip - Tooltip Plugin for Vega-Lite
open_clip - An open source implementation of CLIP.
lightning - High performance, interactive statistical graphics engine for the web.
api-samples - Code samples for YouTube APIs, including the YouTube Data API, YouTube Analytics API, and YouTube Live Streaming API. The repo contains language-specific directories that contain the samples.
plot - A vega-lite DSL for Common Lisp
parquet-wasm - Rust-based WebAssembly bindings to read and write Apache Parquet data
ggplot2 - An implementation of the Grammar of Graphics in R
examples - Analyze the unstructured data with Towhee, such as reverse image search, reverse video search, audio classification, question and answer systems, molecular search, etc.
d3 - Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada: