Interactive renderplot graph with multidimensional dataset - r

Question

I am trying to run an interactive rshiny plot. I have this output:
I want to be able to subset and plot by country, by scenario, by variable, by year (4 selections). I also want to be able to add value points by year and not have the whole plot by year done immediately.
I am only able to subset by country. My scenario and variable dropdowns are not reactive. And it plots all variables with all scenarios although I want one variable plot by one scenario and one country
How can I make my graph interactive?
library(reshape2)
library(lattice)
library(plyr)
library(shiny)
library(dplyr)
library(abind)
library(ggplot2)
ui <- fluidPage(
titlePanel("Comparing Trend and PP policies by MDGs and funding"),
sidebarLayout(
sidebarPanel(
radioButtons("radio", label = h3("Country"),choices=unique(dmiubf$country), selected = ""),
selectInput("Senario","Show senario:", choices = unique(dmiubf$scn)),
selectInput("var","Show senario:", choices = unique(dmiubf$var)),
selectInput("year","Show vertical line in year(s):", choices = unique(dmiubf$year),multiple=TRUE)
),
mainPanel(
plotOutput("chart")
)
)
)
server <- function(input, output) {
cr <- reactive({
a = dmiubf[dmiubf$var==input$var, dmiubf$scn==input$senario]<-dmiubf[dmiubf[,"country"]=="Costa Rica",input$senario]<-"base"
dmiubf
})
output$chart <- renderPlot({
req(input$radio)
if (input$radio==c("Costa Rica")) {
plot0<-ggplot(data=cr()) + geom_point(aes(x=year,y=pcn, fill=scn),
size = 6)
print(plot0)
}
})
}
shinyApp(ui = ui, server = server)

Answer 1

I tried fixing your app, but without knowing how the input data looks like, its a bit hard. So i created a random dummy dataset. Therefore it is not always showing a plot, as no data is left after the filtering process.
But as a starting point I think this should help you:
library(shiny)
library(dplyr)
library(ggplot2)
dmiubf <- data.frame(
country=c(rep("Costa Rica",8), rep("England",8), rep("Austria",8), rep("Latvia",8)),
scn = rep(c("base","high","low","extra"),8),
year = sample(c(1998, 1999, 2000, 2001), 32, replace = T),
var = sample(c(1,2,3,4), 32, replace = T),
pcn = sample(c(10,20,30,40), 32, replace = T)
)
ui <- fluidPage(
titlePanel("Comparing Trend and PP policies by MDGs and funding"),
sidebarLayout(
sidebarPanel(
radioButtons("radio", label = h3("Country"),choices= as.character(unique(dmiubf$country)), selected = ""),
selectInput("Senario","Show senario:", choices = as.character(unique(dmiubf$scn))),
selectInput("var","Show senario:", choices = sort(unique(dmiubf$var))),
selectInput("year","Show vertical line in year(s):", choices = sort(unique(dmiubf$year)), multiple=TRUE)
),
mainPanel(
plotOutput("chart")
)
)
)
server <- function(input, output) {
cr <- reactive({
a <- dmiubf[as.character(dmiubf$country)==input$radio &
dmiubf$var %in% as.numeric(input$var) &
dmiubf$year %in% as.numeric(input$year) &
as.character(dmiubf$scn)==input$Senario
,]
a
})
output$chart <- renderPlot({
validate(
need(nrow(cr())!=0, "No Data to plot")
)
ggplot(data=cr()) + geom_point(aes(x=year, y=pcn, fill=scn), size = 6)
})
}
shinyApp(ui = ui, server = server)