我正在使用 “ selectInput（” Region“，” Region“，choices = unique（dat $ Region））”创建selectInput，还使用updateSelectInput根据每个过滤器进行过滤。但是我正面临以下问题。
unique（dat $ Region）中的错误：找不到对象'dat'
代码流： 1，使用过滤器对数据进行子集 2.为此显示rhansontable和图表 3.输入调整后的入站和调整后的出站值 4.按保存按钮后，将rhosonson表写入数据框 5.更改过滤器后，用户可以再次写
d<-list(1,2,3,4)
ui<-dashboardPage(
dashboardHeader(title ="Interim daily flow"),
dashboardSidebar(
selectInput("Region","Region", choices = unique(dat$Region)),
selectInput("DC_Network","DC Network", choices = unique(dat$DC_Network)),
selectInput("DC_nbr","DC", choices = unique(dat$DC_nbr)),
selectInput("Dept_nbr","DEPARTMENT", choices = unique(dat$Dept_nbr)),
selectInput("Chamber","CHAMBER", choices = unique(dat$Chamber)),
selectInput("Catg_nbr","CATEGORY", choices = unique(dat$Catg_nbr)),
selectInput("Timeframe","TIMEFRAME(Weeks)",choices = d),
dateInput("Startweek","START DATE",daysofweekdisabled=c(0,1,2,3,4,5),value=min(dat$Date),weekstart = 0,min = min(dat$Date),max = max(dat$Date))
),
dashboardBody(
div(
tabsetPanel(type = "tabs",
tabPanel("Input tab",
fluidRow(column(12,plotOutput('graph'))
),
br(),
fluidRow(
column(12,rHandsontableOutput("myTable")),
column(12,actionButton("Save","Save changes"))
)
),tabPanel("Accuracy",
column(12,selectInput("Timeframe_ac","Timeframe",choices = d)),
column(12,dateInput("Startweek_ac","START DATE",daysofweekdisabled=c(0,1,2,3,4,5),value = min(acc_data$Date),min = min(acc_data$Date),max = max(acc_data$Date))),
column(12,plotOutput('acc_plot'))
)
)
)
))
server<-function(session,input,output) {
a<-Sys.time()
data_n<-read.csv("/data/forecast_ui_data/data.csv",stringsAsFactors = F)
acc_data_n<-read.csv("/data/forecast_ui_data/acc_data.csv",stringsAsFactors = F)
c<-Sys.time()
print("load time")
print(c-a)
data_n<- data.frame(lapply(data_n,as.character),stringsAsFactors = F)
acc_data_n<-data.frame(lapply(acc_data_n,as.character),stringsAsFactors = F)
data_n[,c(10:17)]<-data.frame(lapply(data_n[,c(10:17)],as.integer),stringsAsFactors = F)
acc_data_n[,c(10:19)]<-data.frame(lapply(acc_data_n[,c(10:19)],as.integer),stringsAsFactors = F)
if(grepl("-",data_n$Date[1])){
data_n$Date<-as.Date(data_n$Date,"%Y-%m-%d")
}else{data_n$Date<-as.Date(data_n$Date,"%m/%d/%Y")}
if(grepl("-",acc_data_n$Date[1])){
acc_data_n$Date<-as.Date(acc_data_n$Date,"%Y-%m-%d")
}else{acc_data_n$Date<-as.Date(acc_data_n$Date,"%m/%d/%Y")}
dat<<-data_n
acc_data<<-acc_data_n
observeEvent(input$Region,{
x <-dat %>% filter(Region %in% input$Region) %>% select(DC_Network)
updateSelectInput(session, "DC_Network","DC Network",choices = unique(x$DC_Network))
})
observeEvent(input$DC_Network,{
x <-dat %>% filter(DC_Network %in% input$DC_Network) %>% select(DC_nbr)
updateSelectInput(session, "DC_nbr","DC",choices = unique(x$DC_nbr))
})
observeEvent(input$DC_nbr,{
y<- dat %>% filter(DC_Network %in% input$DC_Network) %>% filter(DC_nbr %in% input$DC_nbr) %>% select(Dept_nbr)
updateSelectInput(session, "Dept_nbr","DEPARTMENT",choices = unique(y$Dept_nbr))
})
observeEvent(input$Dept_nbr,{
z<- dat %>% filter(DC_Network %in% input$DC_Network) %>% filter(DC_nbr %in% input$DC_nbr)%>% filter(Dept_nbr %in% input$Dept_nbr) %>% select(Chamber)
updateSelectInput(session, "Chamber","CHAMBER", choices = unique(z$Chamber))
})
observeEvent(input$Chamber,{
z<- dat %>% filter(DC_Network %in% input$DC_Network) %>% filter(DC_nbr %in% input$DC_nbr)%>% filter(Dept_nbr %in% input$Dept_nbr) %>% filter(Chamber %in% input$Chamber) %>% select(Catg_nbr)
updateSelectInput(session,"Catg_nbr","CATEGORY",choices = unique(z$Catg_nbr))
})
fa<-reactive({
a<-as.integer(input$Timeframe)*7
dat %>%filter(DC_nbr %in% input$DC_nbr) %>% filter(Dept_nbr %in% input$Dept_nbr) %>% filter(Catg_nbr %in% input$Catg_nbr) %>% filter(Chamber %in% input$Chamber) %>% filter(Date >= input$Startweek & Date < input$Startweek+days(a))
})
acc<-reactive({
a<-as.integer(input$Timeframe_ac)*7
acc_data %>%filter(DC_nbr %in% input$DC_nbr) %>% filter(Chamber %in% input$Chamber) %>% filter(Date >= input$Startweek_ac & Date < input$Startweek_ac+days(a))
})
output$graph <- renderPlot({
f<-fa()
f<- f %>% select(Date,inbound_volume,outbound_volume)
f1<-melt(f,id.vars="Date")
titl<-"Unconstrained Inbound and Outbound Volume"
fill=c("#003896","#f47b20")
plot_fun(f1,titl,fill)
})
output$myTable<-renderRHandsontable({
fa<-fa()
final_editable<-fa[,c("Date","Week","DC_Network","DC_nbr","Catg_nbr","Chamber","inbound_volume","outbound_volume","adjust_ib","adjust_ob")]
rhandsontable(final_editable)%>% hot_col(c("Date","Week","DC_Network","DC_nbr","Catg_nbr","Chamber","inbound_volume","outbound_volume"), readOnly = TRUE)})
nw_values <- reactiveValues()
observeEvent(input$Save,{
nw_values$data <- hot_to_r(input$myTable)
chngd_tbl<-data.frame(nw_values$data)
chngd_tbl<-chngd_tbl[,c("Date","DC_nbr","Catg_nbr","Chamber","adjust_ib","adjust_ob")]
colnames(chngd_tbl)<-c("Date","DC_nbr","Catg_nbr","Chamber","adjust_ib_nw","adjust_ob_nw")
str(chngd_tbl)
s<-merge(dat,chngd_tbl,by=c("Date","DC_nbr","Catg_nbr","Chamber"),all.x = TRUE)
s$adjust_ib<-coalesce(s$adjust_ib_nw,s$adjust_ib)
s$adjust_ob<-coalesce(s$adjust_ob_nw,s$adjust_ob)
s<-s[,!(colnames(s) %in% c("adjust_ib_nw","adjust_ob_nw"))]
dat<-s
r<-try(write.csv(s,"/data/forecast_ui_data/data.csv",row.names = F))
print(r)
if(is.null(r)){
#shinyalert(title="Saved!", "Given inputs are saved",type = "success")
showNotification("Given inputs are saved!",type = "message")
}else{
showNotification("something went wrong",type="error")}
})
}
shinyApp(ui = ui, server = server)
我期望selectInput中列的所有唯一值