You can step up your data visualization game with {ggiraph} & {patchwork}. Two premier tools for creating interactive, connected plots with click events and tool-tips. (And they're super easy to use too.) Code: #rstats #dataviz

If you liked this post, you may enjoy my 3-minute newsletter too. Every week, my newsletter shares insights on - dataviz, - Shiny web apps - stats Reading time: 3 minutes or less You can join at

Very nice! First time seeing pipes used within 'summarise' and they make the code very readable.

It looks amazing. That's definitely something I gotta learn.

Yeah this package is a fun one 🙃 and it's easy to learn. In fact, my upcoming newsletters will talk about that more

I just realised that this package has similar output as in R plotly. What are the main differences between the plotly and ggiraph packages in terms of functionality and usability for creating interactive plots?

@DanilyanEdo I find {ggiraph} to be a bit closer to ggplot which makes it easier to work with. With {plotly} once you call ggplotly() it's all plotly syntax which I think is harder to work with coming from a ggplot background

Mira @RosanaFerrero Parecido a lo q comentabamos el otro dia (una serie de gráfico funcionando como selector de otro) pero SIN crosstalk

Without using any JavaScript?!

Super impressive 👍. Had no idea ggiraph could plot a {patchwork}. Nice

Beautiful job!! Is there a way to register packages at OpenAI with enough taggage such that someone could request code to show x vs y from source() ?