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library(shiny)
source("irisCluster_with_output.R")
source("subset_rows.R")
UI <- fluidPage(
# add a level 1 header
h1("Master App"),
# each module will have its own tab
tabsetPanel(
#k-means clustering tab
tabPanel(
title = "K-means clustering",
irisClusterUI("hello")
),
#subset rows tab
tabPanel(
title = "Subset Rows",
subset_rows_ui("subset")
)
)
) # end of fluidPage
# create the R server function
SF <- function(input, output, session, ...){
# store the output from the irisCluster module that has hello as its namespace
dataset <- irisClusterServer("hello")
# call the server function, setting the reactive return as the input
subset_rows_server("subset", dataframe = dataset$returndf)
} # end of server function
# Run the application
shinyApp(ui = UI, server = SF)
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