add Map and popup

.gitignore

@@ -0,0 +1,4 @@
+processed.R
+rsconnect/
+
+.Rhistory

app.R

@@ -1,9 +1,16 @@
 library(shiny)
 library(ggplot2)
 library(dplyr)
+library(plotly)
+library(leaflet)
+library(geosphere)
+library(leaflet.extras)
+library(sf)
+
 
 # Load dataset
-data <- read.csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-12-20/weather_forecasts.csv")
+weather <- read.csv("data/processed/weather_pro.csv")
+cities <- read.csv("data/processed/cities.csv")
 
 # Define UI
 ui <- fluidPage(
@@ -19,44 +26,100 @@ ui <- fluidPage(
       sliderInput("month_range", "Select Month Range:",
                   min = 1, max = 12, value = c(1, 12)),
 
-
+      
       # Add dropdown menu input for selecting state
       selectInput("state", "Select State:",
-                  choices = unique(data$state)),
+                  choices = unique(weather$state)),
 
       # Add dropdown menu input for selecting city
       selectInput("city", "Select City:",
-                  choices = unique(data$city)),
+                  choices = NULL),
 
       # Add radio button input for selecting temperature or precipitation
       radioButtons("data_type", "Select Data Type:",
                    choices = c("Temperature", "Precipitation"),
-                   selected = "Temperature")
+                   selected = "Temperature"),
     ),
 
     # Add main panel with plot output
     mainPanel(
-      plotOutput("line_plot")
+      plotOutput("line_plot"),
+      leafletOutput("map")
     )
   )
 )
 
 # Define server
-server <- function(input, output) {
+server <- function(input, output, session) {
+
+  # Update city and state input based on map clicks
+  observeEvent(input$map_marker_click, {
+    updateSelectInput(session, "city", selected = input$map_marker_click$id)
+    updateSelectInput(session, "state", selected = cities$state[cities$city == input$map_marker_click$id])
+  })
+
+  # Update city input possible values based on selected state
+  observe({
+    updateSelectInput(session, "city", 
+                      choices = unique(weather$city[weather$state == input$state]))
+
+  })
+  # observe({
+  #   updateSelectInput(session, "state", 
+  #                     choices = unique(weather$state[weather$city == input$city]))
+  # })
+
+
+
   # Filter data based on user inputs
-  filtered_data <- reactive({
-    data %>%
-      filter(month >= input$month_range[1], month <= input$month_range[2]) %>%
-      filter(state == input$state, city == input$city)
+  line_data <- reactive({
+    weather %>%
+      filter(month >= input$month_range[1], month <= input$month_range[length(input$month_range)]) %>%
+      filter(state == input$state, city == input$city) %>%
+      group_by(month, high_or_low) %>%
+      summarise(observed_temp = mean(observed_temp, na.rm=TRUE),
+                observed_precip = mean(observed_precip, na.rm=TRUE))
   })
 
   # Create line plot based on filtered data and user data type input
   output$line_plot <- renderPlot({
-    ggplot(filtered_data(), aes(x = month, y = ifelse(input$data_type == "Temperature", observed_temp, observed_precip))) +
-      geom_line() +
-      labs(x = "Month", y = input$data_type)
+    if (input$data_type == "Temperature"){
+      ggplot(line_data(), aes(x = month, y = observed_temp, col=high_or_low)) +
+        geom_point() +
+        geom_line() +
+        scale_x_continuous(breaks = seq(1, 12, by = 1)) +
+        labs(x = "Month", y = "Temperature (°F)", color="High/Low")
+    }
+    else{
+      ggplot(line_data(), aes(x = month, y = observed_precip)) +
+        geom_point(color="violetred") +
+        geom_line(color="lightblue") +
+        scale_x_continuous(breaks = seq(1, 12, by = 1)) +
+        labs(x = "Month", y = "Precipitation")
+    }
   })
+
+  # Create leaflet map
+  output$map <- renderLeaflet({
+    leaflet(cities) |>
+      addTiles() |>
+      addCircleMarkers(~lon,
+                       ~lat,
+                       popup = paste0("City: ", cities$city, "<br>",
+                                      "State: ", cities$state, "<br>",
+                                      "Elevation: ", cities$elevation, " m<br>",
+                                      "Distance to Coast: ", cities$distance_to_coast, " mi<br>",
+                                      "Average Annual Precipitation: ", cities$avg_annual_precip, " in"),
+                       layerId = cities$city,
+                       label = cities$city,
+                       color = "navy",
+                       radius = 5,
+                       stroke = FALSE,
+                       fillOpacity = 0.4) |> 
+      setView(-100, 40, zoom = 3.3)
+  })
+
 }
 
 # Run app
-shinyApp(ui, server)
+shinyApp(ui, server)