Add filter for detail. Layout tweaks.

howTo/openGeogAPI/app.R

@@ -5,6 +5,8 @@ library(sf)
 library(htmltools)
 library(leaflet)
 library(plotly)
+library(dplyr)
+library(reshape2)
 
 las_to_load <- c("Southampton","Portsmouth","Winchester",
                  "Eastleigh","Isle of Wight","Fareham",
@@ -22,14 +24,36 @@ download.file(url_to_get, tempf, method = "curl")
 
 dt <- readxl::read_xlsx(tempf, sheet = "Full dataset",skip = 1)
 
-head(dt)
+lvl_detail <-  "high"
 
-library(dplyr)
+filter_detail <- function(lvl_detail =  lvl_detail){
+  
+  if(lvl_detail == "low"){  
+    dt <- dt %>%
+      filter(Name %in% las_to_load) %>%
+      select(`CTRY18NM/RGN18NM`,`Second Tier Authority`,Name,
+             Code,Year,`Industry and Commercial Total`,
+             `Domestic Total`,`Transport Total`,`LULUCF Net Emissions`)
+  }
+  
+  if(lvl_detail == "high"){
     dt <- dt %>%
-  filter(Name %in% las_to_load)
+      filter(Name %in% las_to_load) %>%
+      select(`CTRY18NM/RGN18NM`,`Second Tier Authority`,Name,Code,Year,
+             `A. Industry and Commercial Electricity`,`B. Industry and Commercial Gas`,
+             `C. Large Industrial Installations`,`D. Industrial and Commercial Other Fuels`,
+             `E. Agriculture`,
+             `F. Domestic Electricity`,`G. Domestic Gas`,`H. Domestic 'Other Fuels'`,
+             `I. Road Transport (A roads)`,`J. Road Transport (Motorways)`,`K. Road Transport (Minor roads)`,
+             `L. Diesel Railways`,`M. Transport Other`,
+             `LULUCF Net Emissions`)
+  }
   
-library(reshape2)
   ghg_emissions <- melt(dt, id.vars = c("CTRY18NM/RGN18NM","Second Tier Authority","Name","Code","Year"))
+  return(ghg_emissions)
+}
+
+ghg_emissions <- filter_detail(lvl_detail = "low")
 rm(dt)
 
 # Load LA geography ----
@@ -60,30 +84,31 @@ sf_data$popup_text <-
         '<br/>', 'Local authority: ', '<b>', sf_data$lad18nm, '</b>', ' ') %>%
   lapply(htmltools::HTML)
 
-## Subset data
-area <- "Hart"
-
+## Subset data - Southampton by default
+ghg_subset <- function(auth_area = "Southampton"){
   ghg_emissions_sub <- ghg_emissions %>%
-  filter(ghg_emissions$Name %in% area) 
+    filter(ghg_emissions$Name %in% auth_area)
+  # add filter for categories with input$
+}
 
-# area <- input$map_shape_click$lad18nm
-#area <- "Hart"
+ghg_emissions_sub <- ghg_subset()
 
+# App layout ----
 
 ui <- fluidPage(
   
   
-  titlePanel("Hello Shiny!"),
-  
-  verticalLayout(
-    
-    wellPanel(textOutput("selected_auth")),
-    
+  titlePanel("Hampshire local authority ghg emission visualisation"),
   
-    mainPanel(leafletOutput("authmap", width = "100%", height = "600px")),
+  fluidRow(
     
+    column(6,
+      wellPanel("Click map to select local authority"),
+      leafletOutput("authmap",height = "500px")),
     
-    plotOutput("plot", width = "100%", height = "600px")
+    column(6,
+           wellPanel(textOutput("selected_auth")),
+           plotOutput("plot", height = "500px"))
     
   )
   
@@ -117,7 +142,6 @@ server <- function(input, output, session) {
     
     observeEvent(
       
-      ## the sgmap2 needs to match the name of the map you're outputting above
       input$authmap_shape_click, {
         
         click <- input$authmap_shape_click
@@ -134,8 +158,20 @@ server <- function(input, output, session) {
     
     output$plot <- renderPlot({
       
-      ggplot(ghg_emissions_sub, aes(x = Year, y = value)) +
-        geom_col(aes(fill = variable), position = "stack")
+      plotCaption = paste0("Emissions data: Department for Business, Energy & Industrial Strategy",
+                           "\nLocal authority boundary data (2018): ONS Open Geography Portal",
+                           "\nVisualisation: rushby.shinyapps.io/LAemissions")
+      
+      plotTitle = paste0("Greenhouse gas emissions by sector for ",input$authmap_shape_click$id)
+      
+      ggplot(ghg_subset(auth_area = input$authmap_shape_click$id), aes(x = Year, y = value)) +
+        geom_col(aes(fill = variable), position = "stack") +
+        labs(x = "Year",
+             y = expression("tCO"[2]),
+             fill = "Sector",
+             title = plotTitle,
+             caption = plotCaption) +
+        theme(legend.position = "bottom")
       
     })