![]() ![]() Here, we have specified this to be Blfrtip, where: 2 I usually think of these as ‘expanded features’ that aren’t / haven’t been built into the DT package yet, but are available in the ‘source’ JavaScript library DataTables.ĭom: This argument defines the table control elements to appear on the page and in what order. Options: this argument is where you feed in all the additional customisation options, which is specified in a list. Iris %>% datatable( extensions = 'Buttons',īuttons = c( 'copy', 'csv', 'excel', 'pdf', 'print'),Īnd here is a brief explanation for each of the arguments used in the above code:Įxtensions: this takes in a character vector of the names of DataTables plug-ins, but only plugins supported by the DT package can be used here. (Credits to Jonathan Ng for sharing this trick with me in the first place! His original video tutorial that first mentions this is available here) This will be implemented using the DT package created by RStudio, which provides an R interface to the JavaScript library DataTables. In this post, I am going to share a trick on how to implement this feature within RMarkdown (and therefore means you can do this in flexdashboard) such that the users of your dashboards can export/download your source data. Moreover, having the data available within the dashboard itself helps with reproducibility, in the sense that one can more easily trace back the relationship between the source data and the reported analysis or visualisation. This enables any keen user to extract the source data to produce charts or analysis on their own “off-dashboard”. Traditionally, people also like Excel dashboards for another reason, which is that all the data that is reported in the dashboard is usually self-contained and available in the Excel file in itself, provided that the source data within Excel isn’t hidden and protected. This is an advantage that you don’t really get with other dashboarding solutions such as Tableau and Shiny, as far as I’m aware. Since it’s possible to (i) export these ‘flexdashboards’ as static HTML files that can be opened on practically any computer (virtually no dependencies), (ii) shared as attachments over emails, and (iii) run without relying on servers and Internet access, they rival ‘traditional’ Excel dashboards on portability. In an earlier post April this year, I discussed using flexdashboard (with RMarkdown) as an appealing and practical R alternative to Excel-based reporting dashboards. ![]()
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