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app.R
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app.R
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# library(shiny)
# library(argonDash)
# library(argonR)
# library(shinyWidgets)
# library(dplyr)
# library(flextable)
# library(report)
# library(reactable)
# library(skimr)
# library(dlookr)
# library(performance)
# library(see)
# library(car)
# library(dplyr)
# library(tidyr)
# library(pastecs)
# library(broom)
# library(ggplot2)
# library(ggfortify)
# library(plotly)
# library(ggpubr)
# library(GGally)
# library(modelbased)
# library(DataExplorer)
# template
source("header.R")
source("sidebar.R")
source("intro/intro_tab.R")
source("dataexp/dataexp_tab.R")
source("body/body.R")
# App
shiny::shinyApp(
ui = argonDashPage(
title = "Ismet Thesis",
author = "Ismet Ozer",
description = "Interactive visualization of Ismet's Thesis Data",
sidebar = Isidebar,
header = argonHeader,
body = argonBody
),
server = function(input, output) {
# Skim table
output$skimTable <- renderTable({
if (input$skim == "Factor")
return(tez %>% skim() %>% yank("factor"))
else
return(tez %>% dlookr::diagnose_numeric())
})
# Participant distribution
output$plot_bar_output <- renderPlot({
if (input$plot_bar == "All")
return(tez %>% dplyr::ungroup() %>% dplyr::select(-intuRelig_code,
-okRelig_code) %>%
plot_bar(by_position = "stack",
ggtheme = theme_minimal()))
else
return(tez %>% dplyr::select(-intuRelig_code, -okRelig_code) %>%
plot_bar(by = input$plot_bar,
ggtheme = theme_minimal()))
})
input_mapper <- list("IGT" = tez$IGT,
"IGT_1" = tez$IGT_1,
"IGT_2" = tez$IGT_2,
"IGT_3" = tez$IGT_3,
"IGT_4" = tez$IGT_4,
"IGT_5" = tez$IGT_5)
#IGT stat.desc
output$IGTstat <- DT::renderDT({
IGT_desc_table <- by(input_mapper[input$IGTstat_input], tez$group,
stat.desc, basic = F, norm = T)
as.data.frame(IGT_desc_table[input$IGTstat_group_input]) %>%
DT::datatable() %>% DT::formatRound(columns = 1,
digits = 2)
})
#Outliers Table
output$outliersTable <- DT::renderDT({
tez %>% ungroup() %>% dplyr::select(-id) %>%
diagnose_outlier() %>%
DT::datatable() %>% DT::formatRound(columns = 3:6,
digits = 2)
})
}
)