library(dplyr)
library(shiny)
library(ggplot2)
library(readxl)
master<-read_excel("~/Domaca Naloga/selected-trend-table-from-health-united-states-2011.-leading-causes-of-death-and-numbers-of-deaths-by-sex-race-and-hispanic-origin-united-states-1980-and-2009.xlsx")
uni <- unique(as.factor(master$Cause_of_death))



# Define UI for application that draws a histogram
ui <- fluidPage(

  # Application title
  titlePanel("Leading Causes of Death and Numbers of Deaths "),
  HTML("<p>In the table belowe we have data on the number of deaths, throughout the years starting since 1980 to 2009, for a number of differnet causes.
       Including various diseases, suicide and homicide. This is a dataset hosted by the Centers for Disease Control and Prevention.
       Based on this dataset I will try to find out things like: what was the leading couse of death at the begining, end and throughout this period,
       have more people died at the end of the period or at the begining, are there diseases that affect a certan race/ethnic group (or Geographycal location) more thean others.</p>"),
  conditionalPanel(condition = "input.show_data == true", h3("Data table")),
  DT::dataTableOutput(outputId = "deathtable"),
  # Sidebar with a slider input for number of bins
  sidebarLayout(
    sidebarPanel(
      selectInput(inputId = "Disease",
                  label = "Select Disease:",
                  choices = uni,
                  selected = "All causes",
                  selectize = TRUE),


      wellPanel(
        # Show data table
        checkboxInput(inputId = "show_data",
                      label = "Show data table",
                      value = TRUE)
      ),

      HTML("<h3>Data interpretation</h3>
           <p>From the dropdown menu above we can choose between different causes of death.
           On the right we get a chart showing us if the the number of deaths is growing or not for different races/ethnic groups.
           From the data we can conclude that while some diseases are occuring less the other that have grown in time. We can also see that there are diseases
           that appear to affect more certan races/ethnic groups. That can be caused by Geographycal or Biologycal predispositions.
           Overall when we select all causes we can see that the number of deaths has grown from 200 000 to 250 000.</p>")


      ), #closing sidebarPanel
    # Show a plot of the generated distribution

    mainPanel(
      plotOutput(outputId = "scatterplot"),
      width = 7

    )

    ), #closing sidebarLayout

  plotOutput(outputId = "barchart"),
  HTML("<h3>Data interpretation</h3>
        <p>From the bar char above we can see the number of deaths for groups throughout the years,
       and from the chart below we can see the number of deaths by diseases.</p>"),
  plotOutput(outputId = "barchart2")
  )#closing fluidPage

# Define server logic required to draw a histogram
server <- function(input, output) {

  output$deathtable <- DT::renderDataTable(
    if(input$show_data){
      DT::datatable(data = master[, 1:4],
                    options = list(pageLength = 10),
                    rownames = FALSE)
    }
  )

  output$scatterplot <- renderPlot({
    #req(input$category)
    req(input$Disease)
    filter(master, Cause_of_death==input$Disease) %>%
      ggplot(., aes(x= Year, y=Deaths, group=Group, color=Group)) +
      geom_line(size=1.5) + geom_point(shape=4, size=2.5)+
      scale_color_brewer(palette="Set2")+
      theme_dark()
  })

  output$barchart <- renderPlot({
    #req(input$category)
    #req(input$Disease)
    ggplot(master, aes(x= Year, y= Deaths, fill=Group)) +
      geom_bar(stat="identity", width = 9, colour="black", lwd=0.1) +
      geom_text(aes(label= ifelse(Deaths>300000,Deaths,"")), position=position_stack(vjust=0.5), colour = "white") + coord_flip() + labs(y="", x="")
  })

  output$barchart2 <- renderPlot({
    #req(input$category)
    #req(input$Disease)
    ggplot(master, aes(x= Year, y= Deaths, fill=Cause_of_death)) +
      geom_bar(stat="identity", width = 9, colour="black", lwd=0.1) +
      geom_text(aes(label= ifelse(Deaths>500000,Deaths,"")), position=position_stack(vjust=0.5), colour = "white") + coord_flip() + labs(y="", x="")
  })
}

# Run the application
shinyApp(ui = ui, server = server)