对rShiny中的空白ggplot图进行故障排除

Question

当我运行此代码时，ggplot'ventoutcomes'将不会显示，它会显示为空白图表。当我在RStudio中为ventoutcomes运行单独的代码时，它成功创建了图形。有疑难解答的想法吗？由于患者的机密性，我无法发布数据集。谢谢

library(shiny)
library(semantic.dashboard)
library(ggplot2)
library(plotly)
library(DT)
##devtools::install_github("ropensci/plotly")
##packages needed to create the dashboard


setwd ("/Users/k/Desktop/HMHCOVID")
## set working directory. You can also do it in R Studio under Session...Set Working Directory. If you do that, delete this line. 


library(dplyr)
library(ggplot2)
library(tidyr)
##load the packages 

cols<-c("AmbientAir"="lightblue","LowFlow"="blue","HighFlow"="orange","NIPPV"="purple","MechanicalVentilation"="red","ECMO"="black")
##this is setting the colors

Figure<-read.csv("Figure.csv",header=TRUE)
Figure_Event<-read.csv("Figure_Event.csv",header=TRUE)
##load files

Figure_Event %>% filter(Event=="Discharged" | Event=="Death") %>% filter(Patient<26)-> Figure_Event
##filter the Figure_Event file to relevant rows

##

##Figure <- Figure[!apply(is.na(Figure) | Figure == "", 1, all),]
##remove blank and NA data

##above is the code for ventilation outcomes, to prepare the data



##setwd("/Users/k/Desktop/HMHCOVID")
##set the working directory

library(readr)
library(dplyr)
library(ggplot2)
library(scales)
library(shiny)
library(grid)
library(tidyverse)
library(stringr)
library (lubridate)
library (tinytex)
#install.packages("anytime")
#install.packages("devtools")
library(devtools)
#load the packages needed for donors_time graph


o2outcomes <- read.csv(
  file="patients_transfused.csv",
  stringsAsFactors = FALSE)

o2outcomes <- o2outcomes[!apply(is.na(o2outcomes) | o2outcomes == "", 1, all),]
##remove blank and NA data

view (o2outcomes)

(names(o2outcomes)[10] <- "transfusion_date")
##rename column 8 to see if it helps with transferring from 'character' to 
'date'


o2outcomes <- transform(o2outcomes,
                        td = anytime::anytime(gsub("/20 ","/2020 ",transfusion_date))
)

o2outcomes$transfusion_date <- parse_date_time(o2outcomes$transfusion_date,
                                               orders = "%m/%d/%y %H%M")
##convert data from character into date


o2outcomes <- o2outcomes[order(o2outcomes$transfusion_date),]
##sort by date


o2outcomes <- o2outcomes[order(o2outcomes$transfusion_date), ]
o2outcomes$ID <- seq_len(nrow(o2outcomes))
##create ID to track cumulative cases

##above is the code preparing the data for the donors_time graph




library(plotly)
fig <- plot_ly(midwest, x = ~percollege, color = ~state, type = "box")
fig

ui <- dashboardPage(
  dashboardHeader(color = "blue",title = "HMH Convalescent Plasma Transfusion Therapy", inverted = TRUE),
  dashboardSidebar(
    size = "thin", color = "teal",
    sidebarMenu(
      menuItem(tabName = "main", "Recipient Data", icon = icon("home")),
      menuItem(tabName = "extra", "Donor Data", icon = icon("table"))
    )
  ),
  dashboardBody(
    tabItems(
      selected = 1,
      tabItem(
        tabName = "main",
        fluidRow(
          box(width = 8,
              title = "Graph 1",
              color = "green", ribbon = TRUE, title_side = "top left",
              column(width = 8,
                     plotOutput("ventoutcomes")
              )
          ),
          box(width = 8,
              title = "Graph 2",
              color = "red", ribbon = TRUE, title_side = "top right",
              column(width = 8,
                     plotOutput("donors_time")
                    
              )
          )
        )
      ),
      tabItem(
        tabName = "extra",
        fluidRow(
          dataTableOutput("carstable")
        )
      )
    )
  ), theme = "cerulean"
)

server <- shinyServer(function(input, output) {  
  output$ventoutcomes <- renderPlot({  
    Figure %>% drop_na(Requirement) %>% ggplot() + geom_line(aes(x=Day,y=Patient,group=Patient,col=Requirement),lwd=2.5) + scale_color_manual(values=cols) + scale_y_continuous(trans="reverse",breaks=seq(1,50,1))+scale_x_continuous(breaks=seq(-14,24,1))+theme(panel.grid.major = element_blank(),panel.grid.minor = element_blank(),panel.background = element_blank()) + geom_vline(xintercept=0) + geom_point(data=Figure_Event, aes(x=Day,y=Patient,shape=Event),size=4) + scale_shape_manual(values=c(15,22)) + scale_color_discrete(breaks=c("AmbientAir","LowFlow","HighFlow", "NIPPV","MechanicalVentilation","ECMO"))
  })
})
  
server <- shinyServer(function(input, output) {  
  output$donors_time <- renderPlot({  
    ggplot(data=o2outcomes, aes(x=transfusion_date, y=ID, group=1)) +
      geom_line()+
      ylim(0, 100)+labs(y= "Number of Patients Transfused", x = "Transfusion Date")+ggtitle("Number of Patients Transfused Over Time") 
    ##create line graph 
  })
})

shinyApp(ui, server)

我想我在这行上遇到了麻烦：

Figure %>% drop_na(Requirement) %>% 

Answer 1

我认为您对导致问题的原因是正确的，而且我很确定这是环境问题。就是说，我的意思是说我看到Figure是通过脚本中的read.csv()分配的，但它在应用程序的server部分之外。这实际上意味着它将在运行时从server中隐藏。

尝试将这些行移动到server内：

Figure<-read.csv("Figure.csv",header=TRUE)
Figure_Event<-read.csv("Figure_Event.csv",header=TRUE)

这会将它们加载到应用程序的环境中，并使其可访问。如此说来，请确保要加载的任何其他数据集在server部分中也具有该代码。

EDIT：我还注意到您有两个呼叫server<- shinyserver(function(input,output) {。 See here提供了一些示例和基础知识，但您只应具有一个server函数，并将所有output$对象放入其中。这是一个伪代码示例，它可能为您显示：

# library calls
library(...)
library(...)

ui <- dashboardPage(...

    # ui stuff here already

)


server <- shinyserver(function(input,output) {

    # your prep code goes here.  That's EVERYTHING about preparation
    # of your data...load all datasets here or it will not be visible to the app.
    # almost consider this part your console commands to the app that should
    # be there before the program is run (or during).
    # so, any user-defined functions also go here, or reading of files...
    # if you have to add some columns to that data after reading.. .goes here too

    output$ventoutcomes <- renderPlot({...
        })

    output$donors_time <- renderPlot({...
        })