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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

Albert Rapp

11,572 subscribers

147,485 views • 3 years ago •via X (Twitter)

#rstats #dataviz

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10 Comments

Albert Rapp3 years ago

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

erdi3 years ago

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

Rafael López3 years ago

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

Albert Rapp3 years ago

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

Edo Danilyan3 years ago

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?

Albert Rapp3 years ago

@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

[email protected]3 years ago

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

FranktheTank3 years ago

Without using any JavaScript?!

Lefkios Paikousis3 years ago

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

brucearonow3 years ago

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() ?

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