r - Unable to append cluster membership from kmeans to the raw data in Shiny -

i trying small shiny kmeans exercise download csv file , run kmeans on (ignoring required preprocessing steps)---after getting cluster, want append these cluster numbers original data , output in interactive datatable(from dt package)......but running error....code below....

library(shiny)   # loading required packages   pacman::p_load(amelia,broom,caret,cluster,clustertend,clvalid,corrplot,dbscan,dplyr,dt,data.table,forecast,fpc,fpdclustering,fpp,ggally,ggfortify,ggraph,ggplot2,ggrepel,ggthemes,gmodels,googlevis,gridextra,igraph,knitr,mice,missforest,nbclust,optcluster,pacman,plyr,purrr,qcc,randomforest,rcharts,reshape2,tibble,tidyr,tidyverse,tsa,tseries,vegan,vim,zoo) # add 'caret',`iipr`,'ggthemes','ggraph',igraph,vim,missforest list when using script in spark envir #comparegroups  library(markdown) library(imputets)  # define ui application  ui <- navbarpage(    # application title   titlepanel("shinyapp "),    # sidebar layout input , output definitions ----   sidebarlayout(      # sidebar panel inputs ----     sidebarpanel(        # input: select file ----       fileinput("dataset", "choose csv file",                 multiple = true,                 accept = c("text/csv",                            "text/comma-separated-values,text/plain",                            ".csv")),       # include clarifying text ----       helptext("note: first select dataset of csv format app give insight!!"),       # horizontal line ----       tags$hr(),        # input: checkbox if file has header ----       checkboxinput("header", "header", true),        # input: select separator ----       radiobuttons("sep", "separator",                    choices = c(comma = ",",                                semicolon = ";",                                tab = "\t"),                    selected = ","),        # horizontal line ----       tags$hr(),         # input: actionbutton() defer rendering of output ----       # until user explicitly clicks button (rather       # doing when inputs change). useful if       # computations required render output inordinately       # time-consuming.       actionbutton("update", "update button", class = "btn-primary"),       tags$hr()       ),        mainpanel(         tabsetpanel(           navbarmenu("kmeans",                      tabpanel("raw data cluster membership",                               # output: interactive dt table ----                               h4("cluster table"),                               dt::datatableoutput("cluster_table")                      )           ),           tabpanel("random forest", "this panel intentionally left blank")          )    ) )  )  # define server logic  server <- function(input, output) {    datasetinput <- eventreactive(input$update, {     read.csv(input$dataset$datapath,              header = input$header,              sep = input$sep)   }, ignorenull = false)    #selecting numeric variables   ms.num<- reactive({sapply(datasetinput(), is.numeric)})   ms.data.in.num <- reactive({datasetinput()[ , ms.num()]})   # imputing nas zeros   df<- reactive({imputets::na.replace(ms.data.in.num(), 0)})   # keeping sample of 10k modeling   sample_data <-reactive({df()[1:10000,]})    #### kmeans    opt.cluster=9   set.seed(115)   ms.data.kmeans.mdl <- reactive({kmeans(scale(sample_data()),opt.cluster,nstart=25)})    # appending clusters raw sample data   ms.data_kmeans<-reactive({     x<-ms.data.kmeans.mdl()$cluster     sample_data()$cluster.kmeans <-x    })    output$cluster_table <- renderdatatable({     dt::datatable(ms.data_kmeans())   })    }  # run application  shinyapp(ui = ui, server = server) 

i getting following error:

error in <-: invalid (null) left side of assignment stack trace (innermost first):     96: <reactive:ms.data_kmeans> [c:\users\admin\documents\shiny_test/app.r#124]     85: ms.data_kmeans     84: base::rownames     83: dt::datatable     82: exprfunc [c:\users\admin\documents\shiny_test/app.r#128]     81: widgetfunc     80: func     79: origrenderfunc     78: renderfunc     77: origrenderfunc     76: output$cluster_table      1: runapp 

dont know doing wrong??

found solution...

appending clusters raw sample data

x<-reactive({     cluster<-ms.data.kmeans.mdl()$cluster     cluster   })    output$x1 <- renderprint({     dataset <- x()     table(dataset)   })    add_to_df <- reactive({     sample_data1<-cbind(sample_data(),x())     sample_data1    })    output$cluster_table <- renderdatatable({     dt::datatable(add_to_df())   }) 

just had use cbind() here....