Vega-Lite VS nbviewer.org

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... - Source: Hacker News / 4 days ago

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/. - Source: Hacker News / 3 months ago

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... - Source: Hacker News / 9 months ago

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. - Source: Hacker News / about 1 year ago

The underlying data is from an online betting site. Data analysis was done in Python and I used Vega/Altair for the visualisation. Source: over 1 year ago

Example notebooks are included in the repo and can be previewed using nbviewer:. Source: over 1 year ago

Nbviewer (https://nbviewer.org/): very easy to use for smaller jupyter notebook that does not require heavy rendering. Source: over 1 year ago

Nbconvert renders everything exactly as it looks in your notebook app into a read-only HTML version and is what GitHub uses for notebooks. Interactive plots from Bokeh, Holoviews, etc can still work if you trust the JS, and since editing notebooks while showing them during a meeting usually doesn't go well, read-only is probably good enough (eager to hear feedback on this point though). The nice thing is that... Source: over 1 year ago

Just as a heads up, I used plotly to generate a lot of the charts, so you'll need to view it from an nbviewer like nbviewer.org. Source: about 2 years ago

I used a lot of plotly not knowing that Github wouldn't show it, so you'll need notebook viewer like nbviewer.org to see some of the charts. Source: about 2 years ago