source("Rcode.R")
# Define UI for application that draws a histogram
ui <- fluidPage(
# Application title
titlePanel("DDT data set"),
# Sidebar with a slider input for number of bins
sidebarLayout(
sidebarPanel(
sliderInput("bins",
"Number of bins:",
min = 1,
max = 50,
value = 30),
varSelectInput("condvar",
"Categorical fill Variable:",
ddt[,c("SPECIES","RIVER")],
selected = "SPECIES"),
varSelectInput("var",
"Quantitative Variable:",
ddt[,c("MILE","LENGTH", "WEIGHT","DDT")],
selected = "LENGTH"
),
# varSelectInput("Zout",
# "Extreme Quant. values?:",
# ddt[,c("zLo","zWo", "zDo")],
# selected = "zLo"),
),
# Show a plot of the generated distribution
mainPanel(
plotOutput("histPlot"),
plotOutput("dotPlot")
)
)
)
# Define server logic required to draw a histogram
server <- function(input, output) {
output$histPlot <- renderPlot({
# generate bins based on input$bins from ui.R
g <- ggplot(ddt, aes(x = !!input$var, fill = !!input$condvar ))
g <- g + geom_histogram(bins = input$bins)
# draw the histogram with the specified number of bins
g
})
output$dotPlot <- renderPlot({
# generate bins based on input$bins from ui.R
ifelse(input$var == "LENGTH", ZZ <- "zLo",
ifelse(input$var == "WEIGHT", ZZ <-"zWo",
ifelse(input$var == "DDT", ZZ <- "zDo", ZZ <-"zMo")))
g <- ggplot(ddt, aes(x = !!input$var))
g <- g + geom_dotplot(aes(color = !!input$condvar,stroke = 5, fill = ddt[,ZZ]))
g <- g + geom_density(aes(y = ..count..))
# draw the histogram with the specified number of bins
g
})
}
# Run the application
shinyApp(ui = ui, server = server)
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