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Announcing preview of R Visuals in Power BI Desktop | Microsoft Power BI-blog | Microsoft Power BI
Office 365 + Power BI
Te Power BI Team
In a previous blog post, we showed you how to run R scripts in Power BI to get data, transform it, and then consume it for sharing, visualization and refresh. In this blog post, we expand on that and show how to use your data, which is already in Power BI, to create R visuals and interact with them.
Note: This feature is a Preview feature in te December 2015 release of Power BI Desktop .
Te R visuals in this post are calculated on a local R installation, which must be installed independently of Power BI Desktop. While you can create R visuals and interact with them in Power BI Desktop, once those visuals are published to te Power BI service, those R visual become static images. Don’t worry – we’re working to enable live rendering of R visuals in te Power BI service as well, so in te meanwhile, you can play around with te awesomeness of R visuals in this Power BI Desktop preview!
Four reasons why we’re excited about te power of R Visuals
There are all sorts of reasons to be excited about using R with Power BI Desktop, and to create really cool visuals with R visuals. Because we all like numbers, though, here is a number – four, in this case – of specific reasons we’re really excited about all this:
1. Te voluminous and growing number of “out of te boks” plots available in R. In te image at te beginning of this post, you can see an example of a correlation plot, which shows correlation strength between different data fields. That’s just one example, and te richness and community involvement in R allows reuse of an endless amount of visuals and functions.
2. Te level of customization you can easily reach with R visuals. If you know exactly how you want to tailor your visual, in R, you can code your way to just that customization. With R visuals you have all te flexibility to take existing concepts in R, and code your way to full customization. For example: In te following image, we created a map showing different flight routes for a travel dataset.
3. Te power to combine advanced analytics in visuals. You can now perform regressions, clustering, machine learning, or any calculation available in R, and use that when plotting. For example: Te chart below predicts te probability of getting into differently ranked schools by performing a regression. It then displays te predicted probability with confidence interval bands.
4. You can interact with R visuals in Power BI Desktop in two ways. First, you can modify te R code, and second, you can play with te Power BI controls – change selected data, filter, cross-highlight from other visuals, or refresh data. Te combination of these two ways to interact with te visual create a unique experience in which you can iteratively tweak which data you’re presenting, and customize te R visual. Once te visual is complete, you can still interact with it, cross filter, and always present fresh data with it.
How do I generate an R visual in Power BI Desktop?
In this help article you can find a step by step description of how to generate te visual shown above.
It’s important to remember te first steps mentioned there:
Install R on te same machine on which you’re running Power BI Desktop (if it’s not already installed)
Enable te preview of this feature under File > Options and settings > Options > Preview Features > R Scripting.
In this blog post we saw te first steps of using R to create visualizations over Power BI data. Te functionality described here is released under preview, and there is more to come, but hopefully this gives you a taste of te powerful things you can now do with R and Power BI.
R visuals are another step in enabling you to do more with R and Power BI. It’s still in preview, so stay tuned for more updates, as it will only get better!
Learn more about te Power BI Personal Gateway
Join te conversation at te Power BI Community
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