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rggplot2shinypie-chart

Best way to label pie charts (ggplot2) which respond to user input in R Shiny

I've created faceted pie charts which respond to user input from a drop down menu and am struggling to find a tidy way to label them.

enter image description here

I've tried the method used here: R Shiny: Pie chart shrinks after labeling and other versions of this but the result is still not what I am after, as the labels are not aligning properly.

Thanks in advance :)

Download csv: https://drive.google.com/file/d/1g0p4MpZGzNjVgB2zbAruHYfUkjXzzESA/view?usp=sharing

Attempt #1

ui <- shiny::fluidPage(
selectInput("division", "",
                 label="Select an electorate, graphs will be updated.",
                 choices = df.ind$Elect_div),  #downloaded csv from googledrive
plotOutput("indBar",height="550px", width = "700px"))


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


    df.ind.calc<-reactive ({
     a<-subset(df.ind, Elect_div==input$division)%>%
     group_by(Elect_div, variable3,variable2) %>% 
     summarise(sum_value=sum(value)) %>% 
     mutate(pct_value=sum_value/sum(sum_value)*100)%>%
     mutate(pos_scaled = cumsum(pct_value) - pct_value / 2,
         perc_text = paste0(round(pct_value), "%")) 
    return(a)
  })

  output$indBar <- renderPlot({
  indplot<-ggplot(df.ind.calc(),
  #subset(df.ind.cal,df.ind.cal$Elect_div==input$division),
   aes(x = "",y=pct_value, fill = variable2))+  
   geom_bar(width = 1,stat="identity")+  
   facet_grid(~variable3)+
   coord_polar(theta = "y")+  
   labs(title= "Industry of employment", color="Industries", x="", y="")+
   theme_void()+ #+geom_text(aes(label =percent(pct_value/100), size =5 ), 
   position = position_stack(vjust = 0.5))+
    geom_text(aes(x = 1.25, y = pos_scaled, label = perc_text), size = 4) +
    guides(fill = guide_legend(title = "Industry"))+
   scale_fill_brewer(palette = ("RdBu"))+ labels=c("Agri/Forest/Fish","Arts & Rec","Finance & Insurance","Health",
                                                # "Logistics","Media & Telecomms","Mining","Public Admin & Safety",
                                                # "Real estate", "Retail","Science & tech"))+
  theme(plot.title = element_text(size = 20,hjust = 0.5),strip.text = element_text(size = 15))
indplot})


}


shinyApp(ui, server)

Attempt#2

#calculate sums and percentages for the pie chart
df.ind.cal<-df.ind %>% 
  group_by(Elect_div, variable3,variable2) %>% 
  summarise(sum_value=sum(value)) %>% 
  mutate(pct_value=sum_value/sum(sum_value)*100)%>%
  mutate(pos_scaled = cumsum(pct_value) - pct_value / 2,
     perc_text = paste0(round(pct_value), "%")) 



ui <- shiny::fluidPage(
selectInput("division", "",
                 label="Select an electorate, graphs will be updated.",
                 choices = df.ind$Elect_div),  #downloaded csv from googledrive
plotOutput("indBar",height="550px", width = "700px"))


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



  output$indBar <- renderPlot({
  indplot<-ggplot(df.ind.cal,
  subset(df.ind.cal,df.ind.cal$Elect_div==input$division),
   aes(x = "",y=pct_value, fill = variable2))+  
   geom_bar(width = 1,stat="identity")+  
   facet_grid(~variable3)+
   coord_polar(theta = "y")+  
   labs(title= "Industry of employment", color="Industries", x="", y="")+
   theme_void()+ #+geom_text(aes(label =percent(pct_value/100), size =5 ), 
   position = position_stack(vjust = 0.5))+
    geom_text(aes(x = 1.25, y = pos_scaled, label = perc_text), size = 4) +
    guides(fill = guide_legend(title = "Industry"))+
   scale_fill_brewer(palette = ("RdBu"), labels=c("Agri/Forest/Fish","Arts & Rec","Finance & Insurance","Health",
                                                 "Logistics","Media & Telecomms","Mining","Public Admin & Safety",
                                                 "Real estate", "Retail","Science & tech"))+
  theme(plot.title = element_text(size = 20,hjust = 0.5),strip.text = element_text(size = 15))
indplot})


}


shinyApp(ui, server)

Answer I found a solution that didnt involve calculating the position of the label:

output$indBar <- renderPlot({
   indplot<-ggplot(df.ind.calc(),
  #subset(df.ind.cal,df.ind.cal$Elect_div==input$division),
  aes(x = "",y=pct_value, fill = variable2))+  
  geom_bar(width = 1,stat="identity")+  
  facet_grid(~variable3)+
  coord_polar(theta = "y")+  
  labs(title= "Industry of employment", color="Industries", x="", y="")+
  theme_void()+ 
  geom_text(aes(x=1.6,label = perc_text), size = 4,position = position_stack(vjust = 0.5))+ #NEW SOLUTION THAT WORKS :)
         guides(fill = guide_legend(title="",nrow=3,byrow=TRUE))+
  theme(legend.position="bottom")+
  scale_fill_brewer(palette = "RdBu", labels=c("Agri/Forest/Fish","Arts & Rec","Finance & Insurance","Health",
                                                 "Logistics","Media & Telecomms","Mining","Public Admin & Safety",
                                                 "Real estate", "Retail","Science & tech"))+
  theme(plot.title = element_text(size = 20,hjust = 0.5),strip.text = element_text(size = 15), legend.text=element_text(size=13))
indplot})
Solution

  • Found a solution that doesn't involve calculating that position for each label. But as Antoine suggested in the comments the reason why it wasn't working for me is that the labels and the variables were in different orders.

    enter image description here

     output$indBar <- renderPlot({
   indplot<-ggplot(df.ind.calc(),
  #subset(df.ind.cal,df.ind.cal$Elect_div==input$division),
  aes(x = "",y=pct_value, fill = variable2))+  
  geom_bar(width = 1,stat="identity")+  
  facet_grid(~variable3)+
  coord_polar(theta = "y")+  
  labs(title= "Industry of employment", color="Industries", x="", y="")+
  theme_void()+ 
  geom_text(aes(x=1.6,label = perc_text), 
  size = 4,position = position_stack(vjust = 0.5))+ ###SOLUTION for labeling###
  guides(fill = guide_legend(title="",nrow=3,byrow=TRUE))+
  theme(legend.position="bottom")+
  scale_fill_brewer(palette = "RdBu", labels=c("Agri/Forest/Fish","Arts & Rec","Finance & Insurance","Health",
                                                 "Logistics","Media & Telecomms","Mining","Public Admin & Safety",
                                                 "Real estate", "Retail","Science & tech"))+
  theme(plot.title = element_text(size = 20,hjust = 0.5),strip.text = element_text(size = 15), legend.text=element_text(size=13))
indplot})