cheatsheets VS voila

If you're an R user, stringr + its cheatsheet gets you very close to remembering what to do without needing to look further!

For more information on how to use ggplot2 and create charts consult the ggplot2 official page or the ggplot2 cheat graphic.

I'd suggest you have a look at cheatsheets (or download them from GitHub) if you want to get to know your way around a package or set if functions, it saves you a lot of time.

You could use geom_hline and geom_vline, geom_abline, or geom_segment for this. (The ggplot cheat sheet is very useful for answering these kinds of questions, BTW.)

I can't say for sure because I don't know what your ultimate aim is for your visualization. Check out the cheat sheet for ggplot2 here.

Finally just do your analysis. You should also should give a try and see the cheat sheet for data importing on the tidyverse package.

That said, when I’m trying to come up with an interesting way to visualize data, I find the ggplot cheat sheet very helpful: https://github.com/rstudio/cheatsheets/raw/main/data-visualization-2.1.pdf

Here's a cheat sheet: https://github.com/rstudio/cheatsheets/blob/main/strings.pdf

The cheat sheet of the stringr package should give you good overview of string manipulation/ regex in R.

I would very highly recommend that rather than trying to get started by translating an existing graph, you check out some documentation about ggplot first. If nothing else, the ggplot cheat sheet from RStudio should help explain what the component parts of the code are, and that might help you figure out what you actually want to do.

Quick link: https://github.com/voila-dashboards/voila

Humbly recommend when you share a product, you include a link to it ;)

https://voila.readthedocs.io/en/stable/

> Works with CI/CD out of the box. Deploy to vercel, netlify, your own infra.

Jupyter is suited for whatever you want to do with it. Voila exists to enable the use case of re-generating notebooks on a CI/CD system: https://github.com/voila-dashboards/voila

Anyways, seems like the templating is more powerful than the one being offered by Jupyter Notebooks.

Good luck and much success with it :)

i don't understand why everyone isn't just using voila. it's so much better than streamlit or gradio. but that's just my opinion i guess.

Ill have to check it out and see how it compares to voilà and holoviz panel. What I like about Holoviz panel is you can create a data web app from code that resides in a notebook or create a completely standalone app from just plain py scripts, and it supports many different visualization backends. I have found it to be the more flexible and generalizable data web app framework among the others I have come across (like Voilà, Dash, Plotly, and Streamlit).

Any insights what the differences between this and Voila are? https://github.com/voila-dashboards/voila

A nifty little alternative to voila, one might say.

Markdown and/or Voilà https://github.com/voila-dashboards/voila

If you are comfortable working in a Jupyter Notebook you can combine ipywidgets & Voila.