metaltoaster
Reputation: 378
Selecting variables from columns in dataframe to plot in Shiny R
I'm trying to create an EDA tab for a Shiny app in R but have already fallen at the first hurdle. In my app, I would like it so that the user can select as many or as few variables from each column in the data to analyse. Here is a mock dataframe and the relevant libraries:-
library(wakefield)#for generating the Status variable
library(dplyr)
library(shiny)
library(shinydashboard)
library(funModeling)
set.seed(1)
Date<-seq(as.Date("2015-01-01"), as.Date("2015-12-31"), by = "1 day")
Date<-sample(rep(Date,each=10),replace = T)
Shop<-r_sample_factor(x = c("Shop_A", "Shop_B", "Shop_C","Shop_D", "Shop_E","Shop_F","Shop_G"), n=length(Date))
Product<-r_sample_factor(x=c("Meat","Fruit","Vegetables","Toiletries","Kitchenware","CleaningProducts"), n=length(Date))
Profit<-sample(1:150, length(Date), replace=TRUE)
Profit
data<-data.frame(Date,Shop,Product,Profit)
levels(data$Shop)
#[1] "Shop_A" "Shop_B" "Shop_C" "Shop_D" "Shop_E" "Shop_F" "Shop_G"
levels(data$Product)
#[1] "Meat" "Fruit" "Vegetables" "Toiletries" "Kitchenware" "CleaningProducts"
View(data)
And here is some Shiny code:-
#UI
ui<-fluidPage(
tabPanel("EDA",
sidebarLayout(
sidebarPanel(width = 4,
dateRangeInput("eda_daterange","Select date range", format="yyyy-mm-dd",
start=min(data$Date),
end=max(data$Date)),
pickerInput("eda_col", "Select variable",
choices = c("Shop",
"Product")),
varSelectInput("level_choice", "Select factors to include",
input$eda_col, multiple = T),
actionButton("run_eda", "Run analysis")),
mainPanel(
column(width = 8, box("Frequency plot", plotOutput("frequencyplot_eda"), width = "100%")),
column(width = 8, box("Profit plot", plotOutput("density_eda"), width = "100%"))
)
)
))
#SERVER
server<-function(input,output,session){
#Calls_new_reac<-reactive(Calls_new)
variables<-unique(input$eda_col)
observeEvent(input$run_eda,{
output$frequencyplot_eda<-renderPlot({
if(input$eda_col=="Shop"){
data<-data%>%
filter(Date>=input$eda_daterange[1] & Date<=input$eda_daterange[2])%>%
filter(variables %in% input$level_choice)
freqplot<-freq(data = data, input =input$eda_col )
return(freqplot)
}else{
if(input$eda_col=="Product"){
data<-data%>%
filter(Date>=input$eda_daterange[1] & Date<=input$eda_daterange[2])%>%
filter(variables %in% input$level_choice)
freqplot<-freq(data = data, input =input$eda_col )
return(freqplot)
}
}
})
output$density_eda<-renderPlot({
if(input$eda_col=="Shop"){
data<-data%>%
filter(Date>=input$eda_daterange[1] & Date<=input$eda_daterange[2])%>%
filter(variables %in% input$level_choice)
densplot<-ggplot(data, aes(x=Profit,group=input$eda_col,colour=input$eda_col))+geom_density()+scale_x_log10()
return(densplot)
}else{
if(input$eda_col=="Product"){
data<-data%>%
filter(Date>=input$eda_daterange[1] & Date<=input$eda_daterange[2])%>%
filter(variables %in% input$level_choice)
densplot<-ggplot(data, aes(x=Profit,group=input$eda_col,colour=input$eda_col))+geom_density()+scale_x_log10()
return(densplot)
}
}
})
})#end of observe event
}
shinyApp(ui, server)
The first pickerInput allows the user to select a column to analyse. The varSelectInput was my attempt to allow the user to pick which variable from the selected column to analyse. However, the error message (caused by this):-
varSelectInput("level_choice", "Select factors to include",
input$eda_col, multiple = T)
is this:-
Error in is.data.frame(x) : object 'input' not found
My Shiny expertise is not great as you can see. How can I tidy this up so it would allow me to pick columns and pick the relevant variables that I want to analyse?
Upvotes: 0
Views: 1116
Answers (1)
YBS
Reputation: 21287
One way to do it is to use renderUI() to select the factors. Try this
data<-data.frame(Date,Shop,Product,Profit)
ui<-fluidPage(
tabPanel("EDA",
sidebarLayout(
sidebarPanel(width = 4,
dateRangeInput("eda_daterange","Select date range", format="yyyy-mm-dd",
start=min(data$Date),
end=max(data$Date)),
pickerInput("eda_col", "Select variable",
choices = c("Shop", "Product")),
uiOutput("varselect"),
actionButton("run_eda", "Run analysis")),
mainPanel(
# DTOutput("t1"),
column(width = 8, box("Frequency plot", plotOutput("frequencyplot_eda"), width = "100%")),
column(width = 8, box("Profit plot", plotOutput("density_eda"), width = "100%"))
)
)
))
#SERVER
server<-function(input,output,session){
output$varselect <- renderUI({
vars <- data[[as.name(input$eda_col)]]
selectInput("level_choice", "Select factors to include", unique(vars) , multiple = T)
})
output$t1 <- renderDT({
req(input$level_choice)
data %>%
filter(Date>=input$eda_daterange[1] & Date<=input$eda_daterange[2]) %>%
filter(.data[[input$eda_col]] %in% input$level_choice)
})
observeEvent(input$run_eda,{
req(input$level_choice)
output$frequencyplot_eda<-renderPlot({
data1<-data%>%
filter(Date>=input$eda_daterange[1] & Date<=input$eda_daterange[2])%>%
filter(.data[[input$eda_col]] %in% input$level_choice)
freqplot<-freq(data = data1, input = data1[[input$eda_col]] )
return(freqplot)
})
output$density_eda<-renderPlot({
data2 <- data %>%
filter(Date>=input$eda_daterange[1] & Date<=input$eda_daterange[2])%>%
filter(.data[[input$eda_col]] %in% input$level_choice)
densplot<-ggplot(data2, aes(x=Profit,group=.data[[input$eda_col]],colour=input$eda_col))+
geom_density()+scale_x_log10()
return(densplot)
})
})#end of observe event
}
shinyApp(ui, server)
Upvotes: 3
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