R Shiny tableOutput() and renderTable() does not generate a summary table output

[JoeMark]

###Description
I am trying to build a Shiny app for the education sector but I am wrestling with renderTable(). The output I wish to see in ShinyApp I see in RStudio. The code fails to generate a 2 by 2 table in Shiny.

An example of the code view successfully in RStudio is: info %>% group_by(campus) %>% summarise(funded = n()), where 'campus' is 1 of the variables. In RStudio a summary table (2 by 2) is generated with 2 named columns and 2 rows.

In Shiny the user must be able to choose any of the variables contained in names(info). I achieve this by using the function `selectInput()'.

For the code below, renderTable() does not output a summary table. Instead it is a total count - a count of the total rows, not a summary of the totals of each unique element in a variable.

I think the error is in my renderTable() function code.
Please take a look if you have a moment or direct me to a route that will take me toward a solution.

Thank you.

My sessionInfo appears after the code below.

    library(shiny)
    library(tidyverse)

    info <- check_data <- structure(list(campus = c("athlone", "athlone", "athlone", "athlone","pinelands", "pinelands", "pinelands", "pinelands", "pinelands","pinelands"),
              block = c("l0", "l0", "l0", "l0", "l0", "l0", "l0","ys", "ys", "ys"),
              qualification = c("l2: automotive repair & maintenace nqf","l2: automotive repair
              & maintenace nqf", "l2: automotive repair & maintenace nqf","l2: automotive repair
              & maintenace nqf", "l2: electrical engineering nqf","l2: electrical engineering
              nqf", "l2: electrical engineering nqf","ncv3: electrical infrastructure cnstr l3", "ncv3: electrical infrastructure cnstr l3","ncv3: electrical infrastructure cnstr l3"),
              type = c("f", "f","f", "f", "f", "f", "f", "e", "e", "e"),
              employer = c("null","null", "null", "null", "null", "null", "null", "null", "null","null")), row.names = c(NA, 10L), class = "data.frame")
              
              
    info <- info %>% select(c(2, 3, 4, 8, 10))

    ui <- fluidPage(
  
      selectInput(inputId = "choice",
              label = "Select group",
              choices = names(info),
              selected = c("qualification")),
  
      tableOutput(outputId = "fund")
    )

    server <- function(input, output) {
      headcount <- reactive({
        req(input$choice)
        info %>% group_by(input$choice) %>% summarise(funded = n())
      })
  
    # Headcount
    output$fund <- renderTable({
        headcount()
     })
    }

    shinyApp(ui = ui, server = server)

My sessionInfo() is below:

>R version 3.5.1 (2018-07-02)
>Platform: x86_64-apple-darwin15.6.0 (64-bit)
>Running under: macOS High Sierra 10.13.6

>Matrix products: default
>BLAS: 

>/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecL>ib.framework/Versions/A/libBLAS.dylib
>LAPACK: >/Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dyli>b

>locale:

>[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8

>attached base packages:

>[1] stats, graphics, grDevices utils, datasets, methods, base     

>other attached packages:

 >[1] bindrcpp_0.2.2, forcats_0.3.0, stringr_1.3.1, dplyr_0.7.6    
 >[5] purrr_0.2.5, readr_1.1.1, tidyr_0.8.1, tibble_1.4.2   
 >[9] ggplot2_3.0.0, tidyverse_1.2.1, shiny_1.1.0    

>loaded via a namespace (and not attached):
 >[1] tidyselect_0.2.4, haven_1.1.2, lattice_0.20-35, colorspace_1.3-2
 >[5] htmltools_0.3.6, yaml_2.2.0, utf8_1.1.4, rlang_0.2.1     
 >[9] later_0.7.3, pillar_1.3.0, withr_2.1.2, glue_1.3.0      
>[13] modelr_0.1.2, readxl_1.1.0, bindr_0.1.1, plyr_1.8.4      
>[17] munsell_0.5.0, gtable_0.2.0, cellranger_1.1.0, rvest_0.3.2     
>[21] httpuv_1.4.5, fansi_0.2.3, broom_0.5.0, Rcpp_0.12.18    
>[25] xtable_1.8-2, promises_1.0.1, scales_0.5.0, backports_1.1.2 
>[29] jsonlite_1.5, mime_0.5, hms_0.4.2, digest_0.6.15   
>[33] stringi_1.2.4, grid_3.5.1, cli_1.0.0, tools_3.5.1     
>[37] magrittr_1.5, lazyeval_0.2.1, crayon_1.3.4, pkgconfig_2.0.1 
>[41] Matrix_1.2-14, xml2_1.2.0, lubridate_1.7.4, assertthat_0.2.0
>[45] httr_1.3.1, rstudioapi_0.7, R6_2.2.2, nlme_3.1-137    
>[49] compiler_3.5.1  

[jcblum]

Hi @JoeMark! Welcome!

Thanks very much for writing up a well-put-together question with a great example .

So you've run smack into one of the trade-offs that comes with dplyr's use of non-standard evaluation. That's the trick that lets you write group_by(campus) in your pipeline without having to explain to R where in the world campus is supposed to come from — compare to other situations where you'd have to write info$campus. The trade-off is that group_by() expects to receive a bare symbol as an argument — something that's easy to supply by typing directly, but a little tricky to pass around inside other variables.

The other half of the problem is that input$choice supplies a character string, not a bare symbol. It's evaluating to "campus", not campus, and these turn out to be very different things from R's perspective. If you try running:

info %>% group_by("campus") %>% summarise(funded = n())

you'll see that you get the same unhelpful result as your shiny app is giving you. To understand why, look at the result before summarizing:

info %>% group_by("campus")
#> # A tibble: 10 x 6
#> # Groups:   "campus" [1]
#>    campus   block qualification                  type  employer `"campus"`
#>    <chr>    <chr> <chr>                          <chr> <chr>    <chr>     
#>  1 athlone  l0    "l2: automotive repair &\n  m… f     null     campus    
#>  2 athlone  l0    l2: automotive repair & maint… f     null     campus    
#>  3 athlone  l0    "l2: automotive\n  repair & m… f     null     campus    
#>  4 athlone  l0    l2: automotive repair & maint… f     null     campus    

Confronted with a character string, group_by() assumed you wanted to create and then group on a new variable named "campus" (quotes included!) whose values are all the same — therefore there's only one group.

Here's a version of your shiny app that works the way you want:

library(shiny)
library(tidyverse)

info <- structure(list(campus = c("athlone", "athlone", "athlone",
  "athlone","pinelands", "pinelands", "pinelands", "pinelands",
  "pinelands","pinelands"), block = c("l0", "l0", "l0", "l0", "l0", "l0",
  "l0","ys", "ys", "ys"), qualification = c("l2: automotive repair &
  maintenace nqf","l2: automotive repair & maintenace nqf", "l2: automotive
  repair & maintenace nqf","l2: automotive repair & maintenace nqf", "l2:
  electrical engineering nqf","l2: electrical engineering nqf", "l2:
  electrical engineering nqf","ncv3: electrical infrastructure cnstr l3",
  "ncv3: electrical infrastructure cnstr l3","ncv3: electrical infrastructure
  cnstr l3"), type = c("f", "f","f", "f", "f", "f", "f", "e", "e", "e"),
  employer = c("null","null", "null", "null", "null", "null", "null", "null",
  "null","null")), row.names = c(NA, 10L), class = "data.frame")

ui <- fluidPage(
  
  selectInput(inputId = "choice",
              label = "Select group",
              choices = names(info),
              selected = c("qualification")),
  
  tableOutput(outputId = "fund")
)

server <- function(input, output) {
  headcount <- reactive({
    req(input$choice)
    info %>% group_by(!! sym(input$choice)) %>% summarise(funded = n())
  })
  
  # Headcount
  output$fund <- renderTable({
    headcount()
  })
}

shinyApp(ui = ui, server = server)

(I simplified it a bit — the select() step was trying to select non-existent columns of the data frame)

This code does two things:

1. It converts the string supplied by input$choice into a symbol using the sym() function
2. It uses the !! (bang-bang) operator to tell group_by() "OK, now evaluate that expression I gave you" (sym(input$choice), which evaluates to the selected variable as a bare symbol).

Both steps are necessary:

info %>% group_by(sym(input$choice)) %>% summarise(funded = n())
#> Error in mutate_impl(.data, dots): Column `sym(input$choice)` is of unsupported type symbol

Just like when we passed in a string, group_by() is trying to make a new column and group on it, but this time it fails because dplyr doesn't support a column full of bare symbols.

The bigger picture

The system for working with non-standard evaluation that dplyr is using is called tidy evaluation. It's a relatively new thing that's gradually rolling out to the whole tidyverse, so it's worth wrapping your head around.

Some starting points:

The vignette on programming with dplyr.

A short list of places to get help with tidy eval in ggplot2 (videos!)

Using a Variable Where Quotes Are Needed in Function Argument

Like @mishabalyasin mentioned, @eoppe1022, this is a perfect use case for tidy eval. I find @Edwin's post on this (see link below) to be incredibly helpful. I've also rounded up some other posts/examples of tidy evaluation here:

Good luck with your app!

An aside on testing shiny code...

You are definitely on the right track with the general pattern of working on your code logic outside of shiny! Here's a little trick that can help you catch problems like these sooner.

When you're testing code outside of shiny, try defining a list called input with elements that mimic the structure of input inside of shiny. Then pass input$thing_name into your code where the input values belong. This will make you more aware of when your code is expecting a directly-typed symbol and getting a string or a number from an input, instead.

For this example, the mocked-up input might look like:

input <- list(
  choice = names(info)[1]
)

[JoeMark]

Dear JCBlum

Thank you for nudging me in the right direction. I shall certainly look closely at tidy evaluation, especially with the objective of understanding the solution you have kindly submitted.
Sincerely
JoeMark