Rshiny : displaying chart when clicking on a polygon - r

Question

I'm a Rshiny newbie very eager to learn but right now I'm facing an issue I cannot overcome alone and I would greatly appreciate if someone could help me out ! :)
My problem is (I guess) quite simple:
I have created a map with my polygons and I've managed to display some basic informations when I click on them (have a look on here) but I have no idea how to add a barplot (for example) below my map for each polygon I click.
Could someone help me on how doing that please ? (after hours and hours of attempts my eyesballs are really about to pop out of their sockets !!!)
Many thanks in advance !
Romain
My code:
library(shiny)
library(leaflet)
library(dplyr)
library(magrittr)
library(devtools)
library(RColorBrewer)
library(rgdal)
library(sp)
communes <- readOGR("G:/Ateliers/Projet/communes.shp")
commmunes#data
nom_commune INSEE Variable_1 Variable_2 Variable_3 area_sqkm
1 AUZEVILLE-TOLOSANE 31035 289 8.727212 9.336384 6.979758
2 CASTANET-TOLOSAN 31113 85 4.384877 8.891650 8.460724
3 LABEGE 31254 288 5.047406 2.031651 7.663404
4 PECHBUSQUE 31411 443 6.577743 8.120896 3.099422
5 RAMONVILLE-SAINT-AGNE 31446 95 2.601305 8.909278 6.236784
>
ui <- fluidPage(
leafletOutput("mymap"))
#### SERVEUR R #####
bins <- c(3,3.5,6,6.5,7,7.5,8,8.5)
pal <- colorBin("YlOrRd", domain = communes$area_sqkm, bins = bins)
labels <- sprintf(
"<strong>%s</strong><br/>%g km2",
communes$nom_commun, communes$area_sqkm
) %>% lapply(htmltools::HTML)
server <- function(input, output, session) {
output$mymap<-renderLeaflet(
leaflet(communes) %>%
addProviderTiles(providers$Stamen.TonerLite,
options = providerTileOptions(noWrap = TRUE)
) %>%
setView(1.50, 43.54, zoom = 12) %>%
addTiles() %>%
addPolygons(fillColor = ~pal(area_sqkm),
weight = 2,
opacity = 1,
color = "white",
dashArray = "3",
fillOpacity = 0.7,
highlight = highlightOptions(
weight = 5,
color = "#666",
dashArray = "",
fillOpacity = 0.7,
bringToFront = TRUE),
label = labels,
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto")) %>%
addLegend(pal = pal, values = ~area_sqkm, opacity = 0.7, title = NULL,
position = "bottomright")
)
}
shinyApp(ui = ui, server=server)
The data I would like to display in my barplots are the variable 1,2 and 3 :
data <- read.csv("G:/Ateliers/Projet/communes.csv", sep=";")
data
nom_commune INSEE Variable_1 Variable_2 Variable_3 area_sqkm
1 AUZEVILLE-TOLOSANE 31035 289 8.727212 9.336384 6.979758
2 CASTANET-TOLOSAN 31113 85 4.384877 8.891650 8.460724
3 LABEGE 31254 288 5.047406 2.031651 7.663404
4 PECHBUSQUE 31411 443 6.577743 8.120896 3.099422
5 RAMONVILLE-SAINT-AGNE 31446 95 2.601305 8.909278 6.236784
>

Answer 1

Here is an example shiny app with other data, since I do not have access to your shape data for the map. I believe this might do what you need it to do and can be adapted for your needs.
I would create a reactiveVal to store the id of the polygon region that is clicked on (this variable stores input$mymap_shape_click$id). You data used in addPolygons should have an id to reference.
In your plot (or in a separate reactive expression), you can filter the data based on the reactiveVal containing the id.
library(shiny)
library(leaflet)
library(rgdal)
library(sf)
library(ggplot2)
library(tidyverse)
arcgis_data = st_read("http://data.phl.opendata.arcgis.com/datasets/bc2b2e8e356742568e43b0128c344d03_0.geojson")
arcgis_data$id <- 1:nrow(arcgis_data) ## Add an 'id' value to each shape
plot_data <- read.table(text =
"id nom_commune INSEE Variable_1 Variable_2 Variable_3 area_sqkm
1 AUZEVILLE-TOLOSANE 31035 289 8.727212 9.336384 6.979758
2 CASTANET-TOLOSAN 31113 85 4.384877 8.891650 8.460724
3 LABEGE 31254 288 5.047406 2.031651 7.663404
4 PECHBUSQUE 31411 443 6.577743 8.120896 3.099422
5 RAMONVILLE-SAINT-AGNE 31446 95 2.601305 8.909278 6.236784", header = T, stringsAsFactors = F
)
ui <- fluidPage(
leafletOutput(outputId = "mymap"),
plotOutput(outputId = "myplot")
)
server <- function(input, output){
## use reactive value to store the id from observing the shape click
rv <- reactiveVal()
output$mymap <- renderLeaflet({
leaflet() %>%
addPolygons(data = arcgis_data %>% slice(1:5), layerId = ~id) %>%
addProviderTiles("CartoDB.Positron")
})
observeEvent(input$mymap_shape_click, {
rv(input$mymap_shape_click$id)
})
## you can now plot your plot based on the id of region selected
output$myplot <- renderPlot({
plot_data %>%
filter(id == rv()) %>%
pivot_longer(cols = starts_with("Variable"), names_to = "Variable", values_to = "Value") %>%
ggplot(aes(x = Variable, y = Value)) +
geom_col()
})
}
shinyApp(ui, server)
Edit: For your uploaded data, you don't need to add a separate id for communes. Instead, you could match by name (nom_commune). You can use that in your layerId instead. This looks like it should work. I did take out some of the additional label information as this appeared to be missing from the .shp file I downloaded.
library(shiny)
library(leaflet)
library(rgdal)
library(sf)
library(ggplot2)
library(tidyverse)
communes <- readOGR("communes_ok.shp")
ui <- fluidPage(
leafletOutput(outputId = "mymap"),
plotOutput(outputId = "myplot")
)
server <- function(input, output){
## use reactive values to store the id from observing the shape click
rv <- reactiveVal()
output$mymap<-renderLeaflet(
leaflet(communes) %>%
addProviderTiles(providers$Stamen.TonerLite,
options = providerTileOptions(noWrap = TRUE)) %>%
setView(1.50, 43.54, zoom = 12) %>%
addTiles() %>%
addPolygons(fillColor = "blue",
weight = 2,
opacity = 1,
color = "white",
dashArray = "3",
fillOpacity = 0.3,
highlight = highlightOptions(
weight = 5,
color = "#666",
dashArray = "",
fillOpacity = 0.7,
bringToFront = TRUE),
layerId = ~nm_cmmn)
)
observeEvent(input$mymap_shape_click, {
rv(input$mymap_shape_click$id)
})
## you can now 'output' your generated data however you want
output$myplot <- renderPlot({
if (is.null(rv())) return (NULL)
plot_data %>%
filter(nom_commune == rv()) %>%
pivot_longer(cols = starts_with("Variable"), names_to = "Variable", values_to = "Value") %>%
ggplot(aes(x = Variable, y = Value)) +
geom_col()
})
}
shinyApp(ui, server)