An #introduction post! I'm Danielle, a data scientist and generative artist 🎨 working in #rstats and #python. I'm a developer advocate at Voltron Data and help out with #ApacheArrow 🏹

These are me:

- Blog: https://blog.djnavarro.net/
- Art: https://art.djnavarro.net/
- Website: https://djnavarro.net/
- Art-only account: @djnavarro

Oh and so are these:

- Arrow: https://arrow-user2022.netlify.app/
- Art: https://art-from-code.netlify.app/
- R and stats: https://learningstatisticswithr.com/
- ggplot2: https://ggplot2-book.org/

Hi! 💕

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MORE #bayesian CONTENT. Finished my tidyverse / brms #rstats translation of *Bayes Rules!* ch. 16 on multilevel models.

They do a *masterful* job of explaining pooling, within/between variation, random offsets, and shrinkage.

READ THIS BOOK, PEOPLE! #statsodon #statTootstics https://bayesf22-notebook.classes.andrewheiss.com/bayes-rules/16-chapter.html

Things are coming together for #ArviZ's InferenceData (https://github.com/arviz-devs/InferenceObjects.jl) to be a supported output type for #Turing and #JuliaLang's  #Stan interface, similarly to how it is for #PyMC.

For details, see https://github.com/TuringLang/MCMCChains.jl/issues/381 and https://github.com/StanJulia/StanSample.jl/issues/60

#statistics #mcmc_stan #bayesian

Text might be the most neglected part of #dataviz. We talk a lot about how the right chart type and colors can improve visualizations – but not enough about how to use words well.

So I wrote about that in my latest article: https://blog.datawrapper.de/text-in-data-visualizations/