covid shiny

library(shiny)
library(tidyverse)

d <- read_csv("https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv")

states <- d %>% 
    pull(state) %>% 
    unique() %>% 
    sort()

ui <- fluidPage(
    
    titlePanel("United States (US) County-level COVID-19 Cases Per Day"),
    
    sidebarLayout(
        sidebarPanel(
            p("Many websites provide great data on the number of COVID-19 cases per day, but not at the county level, as this simple app does"),
            selectInput("state", "US State", choices = states, selected = "Tennessee"),
            uiOutput("counties_input"),
            checkboxInput("p1_log", "Log scale for Plot 1"),
            checkboxInput("p2_log", "Log scale for Plot 2")
        ),
        
        mainPanel(
            h4("Plot 1: Cases Over Time"),
            plotOutput("p1"),
            h4("Plot 2: New Cases Over Time"),
            plotOutput("p2"),
            p("Data source: https://github.com/nytimes/covid-19-data"),
            p("Source code for this app: https://gist.github.com/jrosen48/6a78548013d5764d270db47a61401c25")
        )
    )
)

server <- function(input, output) {
    
    get_counties <- reactive({
        d %>%
            filter(state == input$state) %>%
            pull(county) %>%
            unique() %>%
            sort()
    })
    
    output$counties_input <- renderUI(
        selectInput("county", "County", choices = get_counties())
    )
    
    output$p1 <- renderPlot({
        
        p1 <- d %>% 
            filter(county == input$county & state == input$state) %>% 
            mutate(new_cases = cases - lag(cases)) %>% 
            ggplot(aes(x = date, y = cases)) +
            geom_point() +
            geom_smooth() +
            labs(title = str_c("Total Cases in ", input$county, " County (", input$state, ") Per Day"),
                 x = NULL,
                 y = "") +
            theme_bw() +
            theme(text = element_text(size = 12))
        
        if (input$p1_log) {
            p1 + scale_y_log10() + ylab("log (Cases)")
        } else {
            p1
        }
        
    })
    
    output$p2 <- renderPlot({
        
        p2 <- d %>% 
            filter(county == input$county & state == input$state) %>% 
            mutate(new_cases = cases - lag(cases)) %>% 
            ggplot(aes(x = date, y = new_cases)) +
            geom_col() +
            labs(title = str_c("New Cases in ", input$county, " County (", input$state, ") Per Day"),
                 x = "",
                 y = "") +
            theme_bw() +
            theme(text = element_text(size = 12))
        
        if (input$p2_log) {
            p1 + scale_y_log10() + ylab("log (Cases)")
        } else {
            p2
        }
        
    })
}

shinyApp(ui = ui, server = server)