library(shiny)
grapevine <- read.csv("data/bronze.csv")
gold <- read.csv("data/gold.csv")
goldPlus <- read.csv("data/goldPlusElim.csv")
platinum <- read.csv("data/danieldf.csv")
shinyServer(function(input, output, session) {
dataInput <- reactive({
switch(input$dataset,
"Grapevine" = grapevine,
"Gold" = gold,
"Gold Plus" = goldPlus,
"Platinum" = platinum,
)
})
#Creates variables for the columns selected
observe({
updateSelectInput(session, "inSelect", choices = names(dataInput()), selected = names(dataInput())[1])
updateSelectInput(session, "inSelect2", choices = names(dataInput()), selected = names(dataInput())[2])
})
#This creates the "Create" button
plot1 <- eventReactive(input$createg, {
splitData1()
splitData2()
})
#We create smaller dataframes here
splitData1 <- reactive({
#We check to see if a dataframe was submitted, otherwise ERROR
if(is.null(input$dataset)) return(NULL)
#We make dat our dataframe
dat <- dataInput()
#We create a smaller dataframe with only the two columns selected
dat1 <- dat[,c(input$inSelect2, input$inSelect), drop = FALSE]
#We create an even smaller datafram that takes when the grouping variable's numeric value is equal to the first instance
#eg if the grouping variable is gender and the other variable is seed
#This would make the gender variable numeric and just take which variable is equal to 1
#Following our example, this would create a new dataframe with seed and when gender == 1
dat1 <- subset(dat1, as.numeric(dat1[[1]]) == 1)
dat1 <- droplevels(dat1)
#This is the dataframe we return
#This return the column that the user wanted to see with the grouping variable
#eg if the grouping variable is gender and the other variable is seed
#This would just return seed column
dat1 <- dat1[,c(input$inSelect), drop = FALSE]
})
#Second function that creates smaller dataframes
splitData2 <- reactive({
if(is.null(input$dataset)) return(NULL)
dat <- dataInput()
dat1 <- dat[,c(input$inSelect2, input$inSelect), drop = FALSE]
#This is the only line that has changed from SplitData2
dat1 <- subset(dat1, as.numeric(dat1[[1]]) == 2)
dat1 <- droplevels(dat1)
dat1 <- dat1[,c(input$inSelect), drop = FALSE]
})
#This creates our plots
output$plot1 <- renderPlot({
plot1() #displays the graph after the create button
#density graphs are not working
#error: argument 'x' must be numeric
#dens <- density(splitData1())
#plot(dens, col = "red")
#dens2 <- density(splitData2())
#plot(dens, col = "blue")
#only histograms and lines seem to be working
plot(splitData1(), col = "red") #creates histograms of the first grouping variable
lines(splitData2(), col = "blue") #creates histograms of the second grouping variable
})
})
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