diff --git a/app.R b/app.R
index d9a0b84..89ba4eb 100644
--- a/app.R
+++ b/app.R
@@ -122,4 +122,4 @@ server <- function(input, output, session) {
 }
 
 # Run app
-shinyApp(ui, server)
\ No newline at end of file
+shinyApp(ui, server)
diff --git a/combined.R b/combined.R
new file mode 100644
index 0000000..5393f7c
--- /dev/null
+++ b/combined.R
@@ -0,0 +1,241 @@
+library(shiny)
+library(ggplot2)
+library(dplyr)
+library(plotly)
+library(leaflet)
+library(geosphere)
+library(leaflet.extras)
+library(sf)
+
+
+# Load dataset
+weather <- read.csv("data/processed/weather_pro.csv")
+cities <- read.csv("data/processed/cities.csv")
+
+
+# Change numeric month from number to name only for bar plots
+weather_bar <- weather
+weather_bar$month <- month.name[weather_bar$month]
+
+
+
+# Define UI
+ui <- navbarPage(
+  "Citytemp Weather Dashboard",
+  
+  # -----Create tab for Temperature or Precipitation Trends-----
+  tabPanel(
+    'Temperature or Precipitation Trends',
+    titlePanel("Temperature or Precipitation Trends"),
+    
+    # Add sidebar layout
+    sidebarLayout(
+      # Add sidebar panel with inputs
+      sidebarPanel(
+        # Add slider input for selecting range of months
+        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(weather$state)),
+        
+        # Add dropdown menu input for selecting city
+        selectInput("city", "Select City:",
+                    choices = NULL),
+        
+        # Add radio button input for selecting temperature or precipitation
+        radioButtons(
+          "data_type",
+          "Select Data Type:",
+          choices = c("Temperature", "Precipitation"),
+          selected = "Temperature"
+        ),
+      ),
+      
+      # Add main panel with plot output
+      mainPanel(plotOutput("line_plot"),
+                leafletOutput("map"))
+    )
+  ),
+  
+  
+  # -----Create tab for City Ranking by Temperature/Precipitation-----
+  
+  tabPanel(
+    'City Ranking by Temperature/Precipitation',
+    titlePanel(
+      "City Ranking by average monthly Temperature and Precipitation in 2021"
+    ),
+    sidebarLayout(
+      sidebarPanel(
+        selectInput("statename", "Select a state:", choices = unique(weather_bar$state)),
+        selectInput(
+          "highlow",
+          "Select highest or lowest temperature:",
+          choices = c("Highest" = "high", "Lowest" = "low")
+        ),
+        selectInput("month", "Select a month:", choices = unique(weather_bar$month))
+      ),
+      mainPanel(plotOutput("temp_barplot"),
+                plotOutput("rain_barplot"))
+    )
+  )
+  
+  
+  
+  
+)
+
+server <- function(input, output, session) {
+  
+  
+  # Update city and state input based on map clicks
+  observeEvent(input$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
+  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({
+    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$city,
+        color = "navy",
+        radius = 5,
+        stroke = FALSE,
+        fillOpacity = 0.4
+      ) |>
+      setView(-100, 40, zoom = 3.3)
+  })
+  
+
+  
+  # --------------------------------------City Ranking Tab start here------------------------------------
+  
+  
+  # Filter data based on user input, and calculate avg temp and rain
+  bar_data <- reactive({
+    weather_bar %>% filter(state == input$statename &
+                             high_or_low == input$highlow &
+                             month == input$month) %>%
+      group_by(city) %>% summarize(
+        avg_temp = mean(observed_temp, na.rm =TRUE),
+        avg_rain = mean(observed_precip, na.rm =TRUE)
+      )
+  })
+  
+  
+  
+  # Create bar chart of cities by temperature
+  output$temp_barplot <- renderPlot({
+    ggplot(bar_data(), aes(x = avg_temp, y = reorder(city, avg_temp))) +
+      geom_bar(stat = "identity") +
+      labs(
+        x = "Average Temperature",
+        y = "City",
+        title = paste0(
+          "Cities in ",
+          input$statename,
+          " by average ",
+          input$highlow,
+          "est temperature in ",
+          input$month,
+          " 2021"
+        )
+      )
+  })
+  
+  
+  # Create bar chart of cities by precipitation
+  output$rain_barplot <- renderPlot({
+    ggplot(bar_data(), aes(x = avg_rain, y = reorder(city, avg_rain))) +
+      geom_bar(stat = "identity") +
+      labs(
+        x = "Average Precipitation",
+        y = "City",
+        title = paste0(
+          "Cities in ",
+          input$state,
+          " by average precipitation in ",
+          input$month,
+          " 2021"
+        )
+      )
+  })
+}
+
+# Run app
+shinyApp(ui, server)
+