Shiny Application Layouts solutions part 5

####################
#                  #
#    Exercise 1    #
#                  #
####################

#ui.R
fluidPage()
#server.R
function(input, output) {}

####################
#                  #
#    Exercise 2    #
#                  #
####################

#ui.R
fluidPage(
  verticalLayout()
)
#server.R
function(input, output) {}

####################
#                  #
#    Exercise 3    #
#                  #
####################

#ui.R
fluidPage(
  verticalLayout(
    titlePanel("Vertical Cars")
  )
)
#server.R
function(input, output) {}

####################
#                  #
#    Exercise 4    #
#                  #
####################

#ui.R
fluidPage(
  verticalLayout(
    titlePanel("Vertical Iris"),
    plotOutput('plot1')


  )
)
#server.R
function(input, output) {
}

####################
#                  #
#    Exercise 5    #
#                  #
####################

#ui.R
fluidPage(
  verticalLayout(
    titlePanel("Vertical Iris"),
    plotOutput('plot1'),
    wellPanel(selectInput('x', 'X Variable', names(iris)))

  )
)
#server.R
function(input, output) {
}


####################
#                  #
#    Exercise 6    #
#                  #
####################

#ui.R
fluidPage(
  verticalLayout(
    titlePanel("Vertical Iris"),
    plotOutput('plot1'),
    wellPanel(selectInput('x', 'X Variable', names(iris))),
    wellPanel(selectInput('y', 'Y Variable', names(iris),
                          selected=names(iris)[[2]])),
    wellPanel(
              numericInput('clusters', 'Cluster count', 3,
                           min = 1, max = 9)))

  )
#server.R
function(input, output) {
}

####################
#                  #
#    Exercise 7    #
#                  #
####################

#ui.R
fluidPage(
  verticalLayout(
    titlePanel("Vertical Iris"),
    plotOutput('plot1'),
    wellPanel(selectInput('x', 'X Variable', names(iris))),
    wellPanel(selectInput('y', 'Y Variable', names(iris),
                          selected=names(iris)[[2]])),
    wellPanel(
              numericInput('clusters', 'Cluster count', 3,
                           min = 1, max = 9)))

  )
#server.R
function(input, output) {
  Data <- reactive({
    iris[, c(input$x, input$y)]
  })
}

####################
#                  #
#    Exercise 8    #
#                  #
####################

#ui.R
fluidPage(
  verticalLayout(
    titlePanel("Vertical Iris"),
    plotOutput('plot1'),
    wellPanel(selectInput('x', 'X Variable', names(iris))),
    wellPanel(selectInput('y', 'Y Variable', names(iris),
                          selected=names(iris)[[2]])),
    wellPanel(
              numericInput('clusters', 'Cluster count', 3,
                           min = 1, max = 9)))

  )
#server.R
function(input, output) {
  Data <- reactive({
    iris[, c(input$x, input$y)]
  })
  clusters <- reactive({
    kmeans(Data(), input$clusters)
  })

}

####################
#                  #
#    Exercise 9    #
#                  #
####################

#ui.R
fluidPage(
  verticalLayout(
    titlePanel("Vertical Iris"),
    plotOutput('plot1'),
    wellPanel(selectInput('x', 'X Variable', names(iris))),
    wellPanel(selectInput('y', 'Y Variable', names(iris),
                          selected=names(iris)[[2]])),
    wellPanel(
              numericInput('clusters', 'Cluster count', 3,
                           min = 1, max = 9)))

  )
#server.R
function(input, output) {
  Data <- reactive({
    iris[, c(input$x, input$y)]
  })
  clusters <- reactive({
    kmeans(Data(), input$clusters)
  })
  output$plot1 <- renderPlot({
    plot(Data())
  })
}

####################
#                  #
#    Exercise 10   #
#                  #
####################

#ui.R
fluidPage(
  verticalLayout(
    titlePanel("Vertical Iris"),
    plotOutput('plot1'),
    wellPanel(selectInput('x', 'X Variable', names(iris))),
    wellPanel(selectInput('y', 'Y Variable', names(iris),
                          selected=names(iris)[[2]])),
    wellPanel(
              numericInput('clusters', 'Cluster count', 3,
                           min = 1, max = 9)))

  )
#server.R
function(input, output) {
  Data <- reactive({
    iris[, c(input$x, input$y)]
  })
  clusters <- reactive({
    kmeans(Data(), input$clusters)
  })
  output$plot1 <- renderPlot({
    plot(Data(),
         col = clusters()$cluster,
         pch = 20, cex = 3)
    points(clusters()$centers, pch = 4, cex = 4, lwd = 4)
  })
}