r - Error in UseMethod("xtable") -

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i trying load multiple files , merge using reduce function... tried several options got same error got 'xtable' applied object of class "character"

server.r

library(shiny)  shinyserver(function(input,output) {     output$data <- renderui({         res <- lapply(             1:input$fnos,             function(i) {                 fileinput(paste("file", i),                 "load file",                 accept=c(                     'text/csv',                     'text/comma-separated-values',                     'text/tab-separated-values',                     'text/plain','.csv','.tsv' ))}         )         do.call(sidebarpanel,res)        })      output$multi <- rendertable({         infile <- list(             lapply(1:input$fnos, function(i) {input[[paste("file",i)]]})         )[[1]]          # data frame names         df <- (letters[1:input$fnos])          # trying use assign function create         # different dataframes using read.csv         (i in 1:input$fnos) {assign(df[i], read.csv(infile[[c(i,4)]]))}          #merging using reduce function         merged <- reduce(function(x,y) merge(x,y), list(df))         # getting error here     })  })

ui.r

library(shiny)  shinyui(fluidpage(     titlepanel(title="multiple file load"),     sidebarlayout(         sidebarpanel(             numericinput("fnos","files input",1)),         mainpanel(uioutput("data"), tableoutput("multi"))     ) ))

you reduce wrong thing. assuming have 2 files 'file1.csv', 'file2.csv' should work larger number of files well:

> write.csv(structure(list(id = 1:3, x = 4:6), .names = c("x", "y"), class = "data.frame", row.names = c(na, -3l)), 'file1.csv', row.names=false) > write.csv(structure(list(id = 1:2, y = 9:10), .names = c("x", "z"), class = "data.frame", row.names = c(na, -2l)), 'file2.csv', row.names=false) > dfs <- lapply(list.files(pattern="file[1-2]\\.csv$"), read.csv) > dfs [[1]]   x y 1 1 4 2 2 5 3 3 6  [[2]]   x  z 1 1  9 2 2 10

you can use either reduce: 

> reduce(merge, dfs)   x y  z 1 1 4  9 2 2 5 10

or better simple do.call:

> do.call(merge, dfs)   x y  z 1 1 4  9 2 2 5 10

if want translate app can use this:

reduce(     merge, lapply(         paste('file', 1:input$fnos),         function(x) read.csv(input[[x]]$datapath) ))

just remember checking if input set.


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