Add Select columns dynamically in R with ends_with in Shiny App - r

Question

Using stackoverflow, I created a shiny app which uploads a csv file and then displays a datatable.
After selecting columns dynamically, where some columns have "_down" end.
I require help in shortening the dataframe (as in the code below) and also remove duplicates by ID column (if present).
# install.packages("shiny")
# install.packages("DT")
# install.packages("shinycssloaders")
library(DT)
library(shiny)
library(shinycssloaders)
UI code
##Creating the UI as a fluidPage,
##fluidPage allows scaling components of the browser in realtime to fill all available broswer width
##This is standard
ui <- fluidPage(
# Title of app
titlePanel("Upload file to table"),
# Main panel for displaying outputs
mainPanel(
#fileInput with acceptance of text/csv and more
fileInput('file', 'Choose file to upload',
accept = c(
'text/csv',
'text/comma-separated-values',
'text/tab-separated-values',
'text/plain',
'.csv',
'.tsv',
'.html'
)),
# Output: datatable
DT::dataTableOutput("data_as_table")%>%withSpinner(),
#Download button
downloadButton("downloadData", "Download")
)
)
Server Code
Creating server
server <- function(input, output) {
#Data is a reactive element meaning it will update when the reactive input inside it change
#Data will update when input$file changes
#input$file is the uploaded file (se fileInput in ui)
data <-reactive({
#Store input$file as inFile
inFile <- input$file
#if its empty return nothing
if (is.null(inFile))
return(NULL)
#read in the file as a csv, with headers, comma seperated
dd = read.csv(inFile$datapath, header = T,
sep = ",")
dd = as.data.frame(dd)
#Shortening dataframe
#dd= dd[apply(dd[, endsWith(colnames(dd), "_down")], 1, function(x) any(x == "TRUE")), ]
#Remove duplicates by ID column, and show unique
#xxx
return(dd)
})
#Make the output data_as_table a datatable containing the reactive element data
output$data_as_table<-DT::renderDataTable({
data()
})
# Downloadable csv of reactive data() object
output$downloadData <- downloadHandler(
filename = function() {
paste("Download", Sys.date(), ".csv", sep = "")
},
content = function(file) {
write.csv(data(), file, row.names = FALSE)
}
)
}
#Launch shiny app
shinyApp(ui = ui, server = server)

Answer 1

You can remove duplicates using dplyr::distinct. It'll only keep the first instance of the ID and remove others. In your case add this before return(dd) in data reactive -
if("ID" %in% names(dd)) {
dd <- dplyr::distinct(dd, ID, .keep_all = T)
}