Almost anything (within reason) you want to do with data can be done in an R application ... if you can just find the correct libraries and functions.
A program I'm writing in R, using the Shiny web framework, needs to both display and export a data frame. Ordinarily, this would be straightforward: I would use datatable(), renderDT() and dataTableOutput() from the DT library for display, and something like write.csv from the utils library to export the data frame in a spreadsheet format. Unfortunately, none of that works this time. The problem is that the data frame comes from an HTTP POST request, with the data arriving as a JSON object. The JSON object contains nested structures, which results in a data frame where some cells contain lists or data frames. Even after applying the flatten() function from the jsonlite library, the nesting persisted.
The data frame would render in Shiny as a table, but in cells where nested structures hid the rendered table would just say something like "list()" or maybe "1 entry". The write.csv function refused to write the table to a file. I noticed, though, that if I viewed the data frame in RStudio (using the View() command), the nested structures would still say something like "list()" but clicking them would open them in a new window and hovering over them with the mouse would give an indication of the content. A quick check of the help entry for View() showed that it uses the format.data.frame() function from the base library. So I tried applying that function to my data frame before displaying or exporting it, and both problems were fixed. The displayed table showed the contents of each cell, and the flattened table could be exported to a CSV file. The structure of the nested data frames and lists was not preserved, but the user could at least see what was in those cells, which was good enough for my application.
