Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

add combined script #26

Merged
merged 1 commit into from
Feb 26, 2023
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion app.R
Original file line number Diff line number Diff line change
@@ -122,4 +122,4 @@ server <- function(input, output, session) {
}

# Run app
shinyApp(ui, server)
shinyApp(ui, server)
241 changes: 241 additions & 0 deletions combined.R
Original file line number Diff line number Diff line change
@@ -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)