我想要做一个小闪亮的Kmeans练习，我下载一个csv文件并在其上运行kmeans（忽略任何所需的预处理步骤）---获取群集，我想附加这些群集数字的原始数据，并在互动datatable（从DT包）输出这个......但我遇到了一个错误....下面的代码....无法将群集成员资格从kmeans添加到Shiny中的原始数据

library(shiny) 

# Loading the 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 to the list when using the script in spark envir 
#compareGroups 

library(markdown) 
library(imputeTS) 

# Define UI for application 
ui <- navbarPage(

    # Application title 
    titlePanel("ShinyApp "), 

    # Sidebar layout with input and output definitions ---- 
    sidebarLayout(

    # Sidebar panel for inputs ---- 
    sidebarPanel(

     # Input: Select a 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 the dataset of csv format only for the App to give any 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() to defer the rendering of output ---- 
     # until the user explicitly clicks the button (rather than 
     # doing it immediately when inputs change). This is useful if 
     # the computations required to render output are inordinately 
     # time-consuming. 
     actionButton("update", "Update button", class = "btn-primary"), 
     tags$hr() 
    ), 

     mainPanel(
     tabsetPanel(
      navbarMenu("Kmeans", 
        tabPanel("Raw data with cluster membership", 
           # Output: Interactive DT table ---- 
           h4("Cluster Table"), 
           DT::dataTableOutput("cluster_table") 
        ) 
     ), 
      tabPanel("Random Forest", "This panel is 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 only numeric variables 
    MS.num<- reactive({sapply(datasetInput(), is.numeric)}) 
    MS.DATA.IN.NUM <- reactive({datasetInput()[ , MS.num()]}) 
    # imputing NAs by zeros 
    df<- reactive({imputeTS::na.replace(MS.DATA.IN.NUM(), 0)}) 
    # Keeping a sample of 10k for 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 to the 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 the application 
shinyApp(ui = ui, server = server)

我收到以下错误：

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

不知道我在做什么错？

来源

2017-08-20 Nishant

我不知道它会解决所有问题，但'renderDataTable'来自'shiny'包，而不是'DT'。你写了'DT :: renderDataTable'。 – Smich7

@纠正了......仍然出现错误.... – Nishant

找到了解决办法...

附加集群的原始样本数据

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()) 
    })

就只好用cbind（）返回这里....

来源

2017-08-20 13:32:49 Nishant

无法将群集成员资格从kmeans添加到Shiny中的原始数据

回答

附加集群的原始样本数据

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