Tukukkk

Update: I have figured out how to do this, but it only works in the HTML viewer pane in R-Studio.

The map pane works fine in the HTML viewer, but is slow and 9/10 times disconnects from the server (I imagine it times out) when deployed.

I have tried to use isolate() and actionButtons(), but this didn't help.

My repo: https://github.com/MirandaLupion/GOV_1005_Final_Project
(app is in navbarApp folder)

Deployed app: https://mlupion.shinyapps.io/Russian_crime_data/

The data itself is large. I use the filter feature in the reactive to filter for only the year needed and then select only the variable needed. This worked fine when the only input option was year. Might is be causing the issue, now that it also facilitates the indicator input? Should I do this in two reactive statements?

Original post:

I am new to Leaflet and Shiny, and I haven't found a suitable answer to this question, but my apologies if someone has already asked this.

I want the user to select the variable, which is then used to generate a choropleth map in my shapefile. The shapefile and map works fine when I manually insert the variable (replacing the variable map_var here with CRIMESHARE for instance) in the code. However, when I try to replace that variable with input$y, Shiny throws an era: no applicable method for 'rescale' applied to an object of class "character"

In the current code, I try to save the input$y as a variable map_var. This doesn't work. I have also tried saving the input this way in a reactive statement, but it also failed.

The reactive year input works correctly.

I am not sure I can create a reproducible example, as it involves a shape file. I appreciate any help/suggestions.

Here are the relevant parts of my code below:

Data prep

# Load libraries 



library(shiny)

library(tidyverse)

library(stringr)

library(rsconnect)

library(leaflet)

library(rgdal)

library(shinythemes)

library(plotly)



# Read in the data



crime_master <- read_rds("r_4_tidy.rds")



# Prepare two data sets 

# one for the plot (not shown) and one for the map 



crime_plot <- crime_master

crime_map <- crime_master %>%

  mutate(YEAR = as.character(YEAR))





# Prepare the shape file for the map 

# Read it in

# Project the shape file 



rf_map <- readOGR(dsn = "/Users/me/Desktop/folder 

/Project/RUS_adm", layer = "RUS_adm1")

rf_map <- spTransform(rf_map, CRS("+init=epsg:4326"))



crime_options <- c("Road accidents" = "ROADACCIDENT", 

               "Victims of road accidents" = "ROADVICTIM",

               "Crime share" = "CRIMESHARE", 

               "Murders" = "MURDER",

               "Incidences of rape" = "RAPE",

               "Robberies" = "ROBBERY",

               "Incidences of hooliganism" = "HOOLIGANISM",

               "White-collar crimes" = "ECONCRIME",

               "Incidences of juvenile crime" = "JUVENILECRIME") 

The UI

ui <- fluidPage(theme = shinytheme("cerulean"),



sidebarLayout( 

 sidebarPanel( 



   # Let users select the year to map



   selectInput(inputId = "year", #internal label 

               label = "Year to map", #label that user sees

               choices = c(crime_map$YEAR), #vector of choices for user to pick from 

               selected = "1990"),



   # Let users select the indicator to map



   selectInput(inputId = "y", # internal label 

               label = "Indicator to display on map", # label that user sees

               choices = crime_options, # vector of choices for user to pick from 

              selected = crime_options[3])),



mainPanel(



   tabsetPanel(type = "tabs",

               tabPanel("Map an indicator", 

               leafletOutput("map", 

                             width = "100%", 

                            height = "500px"))))))

The server

server <- function(input, output){



  # Reactive that filters the crime_map data for the user-selected year



  map_subset <- reactive({

    req(input$year)

    filter(crime_map, YEAR == input$year) 





  })



  # Map output

  # Merge the shapefile with the sub_setted map data

  # Color by the selected indicator 

  # Set the options for the leaflet viewer 

  # Allow the user to drag

  # Add a CartoDB base map

  # Set the default view

  # Set the max bounds

  # Add the shapefile with labels

  # Color by the coloring set up



  output$map <- renderLeaflet({



    map_var <- input$y



    rf_map <- merge(rf_map, map_subset(), by = "ID_1", duplicateGeoms = 

TRUE)

    coloring <- colorNumeric(palette = "Blues",

                         domain = rf_map@data$map_var)

    m <- rf_map %>%

      leaflet(options = leafletOptions(dragging = TRUE)) %>%

      addProviderTiles(provider = "CartoDB") %>%

      setView(lng = 37.618423, lat = 55.751244, zoom = 3) %>%

     setMaxBounds(lng1 = 40, lat1 = 30, lng2 = 150, lat2 = 100) %>%

     addPolygons(weight = 1, 

              label = ~paste0(NAME, ", ", map_var),

              color = ~coloring(map_var)) %>%



  # Add a legend in the bottom



  addLegend("bottomright", 

            pal = coloring, 

            values = ~map_var,

            title = "title here",

            opacity = 1)

m})}



shinyApp(ui = ui, server = server)

Thank you!