Pass data from another source as input to the R.Execute () function

[deldersveld3]

The R.Execute () Power Query function only allows you to use R for ingesting data. Ideally, make R.Execute () more powerful by making it a data transformation function as well as data source. Let data be loaded from other sources, and then R.Execute () could be called in a subsequent step in the Power Query query. let Source = Excel.Workbook(File.Contents("C:\[...].xlsx"), null, true), Custom1 = R.Execute("df<-data.frame(Source) [...]") in Custom1 Transformations could all be done in R first, but it's slower in general, and you lose the convenience of blending data in Power BI itself.

[andrea_cuneo]

This is blocking for us since R doesn't support our data sources natively while Power BI does.

[jabrahams]

I second this idea. This would make Power Query a real winner

[Imke]

If I'm not mistaken we could use this functionality also to push data from Power BI to Excel. Although the ability to connect to a PBI model via Excel is great, this is a pull-mechanism and sometimes there is a requirement to push data in a table-format to Excel. There are also requirements to export more than 1.1 Mio rows - to csv or text - R could be used as a workaround for these cases. At the moment the only way to go is via a visualisation and there we're experiencing a row-limit of 150k. Folks sometimes like to use the transformations they've done in PBI (desktop!) not only in visualisations there, but also (reuse) for other tasks.

[ankitpatira]

Really great feature to have.

[deldersveld3]

AWESOME! It's working in Desktop!

[hugoberry31]

I think this feature has already been implemented. Here is an example let Source = #table({"num"},List.Accumulate({1..10},{},(s,c)=>s&{{c}})), RScript = R.Execute("df<-dataset#(lf)df$fact<-factorial(df$num)",[dataset=Source]), out = RScript{[Name="df"]}[Value] in out