Nothing
Statistics Primer"
In STAT: Interactive Document for Working with Basic Statistical Analysis
knitr::opts_chunk$set(echo = TRUE)
library(psycho)
library(Hmisc)
library(corrgram)
library(dplyr)
library(rpivotTable)
library(psych)
library(datasets)
sidebarPanel(
inputPanel(
checkboxInput("P","Check if you want to use pre-loaded datasets",value = TRUE), selectInput("ds","Choose dataset you wish to explore",choices = c("iris","esoph","anscombe","cars","attitude","chickwts","Orange","ToothGrowth","BOD"))
),
inputPanel(
fileInput("file", "Upload the *.csv file with headers"),
checkboxInput("std","standardize",value = FALSE),
downloadButton("downloadStdData", "Download dataset")
),
inputPanel(
uiOutput("vx"),
uiOutput("vx2"),
uiOutput("vx3")
),
inputPanel(
selectInput("col","Choose Color",choices = c("red","green","blue","yellow"))
),
inputPanel(
downloadButton("downloadPlot2", "Download Histogram"),
downloadButton("downloadPlot3", "Download Pie Chart"),
downloadButton("downloadPlot4", "Download Box Plot"),
downloadButton("downloadPlot5", "Download Association Plot"),
downloadButton("downloadPlot", "Download Correlation Plot"),
downloadButton("downloadCorMat", "Download Correlation Matrix"),
downloadButton("downloadReport", "Download Descriptives Report"),
downloadButton("downloadReport2", "Download Summary Report")
)
)
mainPanel(
tabsetPanel(type = "tab",
tabPanel("Descriptives", verbatimTextOutput("AD")),
tabPanel("Histogram",plotOutput("HG")),
tabPanel("Pie Chart",plotOutput("PC")),
tabPanel("Box Plot",plotOutput("BP")),
tabPanel("Association Plot",plotOutput("AP")),
tabPanel("Correlation Plot",plotOutput("CP")),
tabPanel("Correlation Summary",verbatimTextOutput("SUM")),
tabPanel("Interactive Dashboard",rpivotTableOutput("PT"))
),width = 8
)
output$AD<-renderPrint({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
cat(sprintf("\nThis is about dataset : %s\n", input$ds))
data( input$ds)
data = get(input$ds)
}
cat(sprintf("\nSnapshot of the dataset\n"))
if(input$std == TRUE) {data = data.frame(standardize(data))}
print(head(data,6))
cat(sprintf("\nSummary of the dataset\n\n"))
print(summary(data))
df = select_if(data,is.numeric)
cat(sprintf("\n\n Detailed descriptive statistics of Quantitative Variables are as follows\n\n"))
print(describe(df))
})
output$CP<-renderPlot({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
cat(sprintf("\nThis is about dataset : %s\n", input$ds))
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
corrgram(data,order = TRUE,lower.panel = panel.shade,upper.panel = panel.pie,main ="Corrgram")
})
output$SUM<-renderPrint({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
cat(sprintf("\nThis is about dataset : %s\n", input$ds))
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = select_if(data,is.numeric)
cat(sprintf("\n Correlation Summary of the dataset\n"))
cor = rcorr(as.matrix(df))$r
print(cor)
})
datasetInput1 <- reactive({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data_set = data.frame(standardize(data))}
else {data_set = data}
})
output$downloadStdData <- downloadHandler(
filename = function() {
filetitle = paste("dataset")
paste(filetitle, ".csv", sep = "")
},
content = function(file) {
write.csv(datasetInput1(), file, row.names = FALSE)
}
)
output$downloadPlot<- downloadHandler(
filename = function() {
paste("Correlationplot", ".png", sep = "")
},
content = function(file) {
png(file)
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
cat(sprintf("\nThis is about dataset : %s\n", input$ds))
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
corrgram(data,order = TRUE,lower.panel = panel.shade,upper.panel = panel.pie,main ="Corrgram")
dev.off()
})
datasetInput2 <- reactive({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = select_if(data,is.numeric)
data = data.frame(rcorr(as.matrix(df))$r)
})
output$downloadCorMat <- downloadHandler(
filename = function() {
filetitle = paste("dataset")
paste(filetitle, ".csv", sep = "")
},
content = function(file) {
write.csv(datasetInput2(), file)
}
)
output$PT<-renderRpivotTable({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
rpivotTable(data)
})
output$vx <- renderUI({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = select_if(data,is.numeric)
selectInput("variablex","Select the Quantitative variable for histogram",choices = colnames(df),selected = "" )
})
output$HG<-renderPlot({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = select_if(data,is.numeric)
attach(df)
hist(get(input$variablex),col = input$col,main = "Histogram",xlab = input$variablex)
})
output$downloadPlot2<- downloadHandler(
filename = function() {
paste("Histogram", ".png", sep = "")
},
content = function(file) {
png(file)
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = select_if(data,is.numeric)
attach(df)
hist(get(input$variablex),col = input$col,main = "Histogram",xlab = input$variablex)
dev.off()
})
output$vx2 <- renderUI({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = select_if(data,is.factor)
selectInput("variablex2","Select the Qualitative variable for PieChart",choices = colnames(df),selected = "" )
})
output$vx3 <- renderUI({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = select_if(data,is.factor)
selectInput("variablex3","Select the Second Qualitative variable",choices = colnames(df),selected = "" )
})
output$PC<-renderPlot({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = select_if(data,is.factor)
attach(df)
x = get(input$variablex2)
frequency = table(x)
lbls = paste(names(frequency), "\n", sep="")
pct = round(frequency/sum(frequency)*100)
lbls = paste(lbls, pct) # add percents to labels
lbls = paste(lbls,"%",sep="") # ad % to labels
pie(frequency,labels = lbls, col=rainbow(length(frequency)),main = input$variablex2)
})
output$downloadPlot3<- downloadHandler(
filename = function() {
paste("Pie", ".png", sep = "")
},
content = function(file) {
png(file)
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = select_if(data,is.factor)
attach(df)
x = get(input$variablex2)
frequency = table(x)
lbls = paste(names(frequency), "\n", sep="")
pct = round(frequency/sum(frequency)*100)
lbls = paste(lbls, pct) # add percents to labels
lbls = paste(lbls,"%",sep="") # ad % to labels
pie(frequency,labels = lbls, col=rainbow(length(frequency)),main = input$variablex2)
dev.off()
})
output$BP<-renderPlot({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = data
attach(df)
boxplot(get(input$variablex) ~ get(input$variablex2),col = input$col,main = "Box Plot",xlab = input$variablex2,ylab = input$variablex)
})
output$downloadPlot4<- downloadHandler(
filename = function() {
paste("BoxPlot", ".png", sep = "")
},
content = function(file) {
png(file)
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = data
attach(df)
boxplot(get(input$variablex) ~ get(input$variablex2),col = input$col,main = "Box Plot",xlab = input$variablex2,ylab = input$variablex)
dev.off()
})
output$AP<-renderPlot({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = select_if(data,is.factor)
attach(df)
x = get(input$variablex2)
y = get(input$variablex3)
frequency = table(x,y)
assocplot(frequency,col =c("green","red"),xlab = input$variablex2,ylab = input$variablex3,main = "Association Plot")
})
output$downloadPlot5<- downloadHandler(
filename = function() {
paste("AssociationPlot", ".png", sep = "")
},
content = function(file) {
png(file)
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = data
attach(df)
x = get(input$variablex2)
y = get(input$variablex3)
frequency = table(x,y)
assocplot(frequency,col =c("green","red"),xlab = input$variablex2,ylab = input$variablex3,main = "Association Plot")
dev.off()
})
h6("", tags$img(src ="K.JPG", height= 400, width=400))
datasetInput3 <- reactive({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
if(input$std == TRUE) {data = data.frame(standardize(data))}
df = select_if(data,is.numeric)
datareport = capture.output(print(describe(df)))
})
output$downloadReport <- downloadHandler(
filename = function() {
filetitle = paste("Descriptive_report")
paste(filetitle, ".doc", sep = "")
},
content = function(file) {
write.file(datasetInput3(), file)
}
)
datasetInput4 <- reactive({
if(input$P == FALSE)
{
file1 = input$file
if(is.null(file1)){return()}
data = read.table(file = file1$datapath,sep =",",header = TRUE)
if(is.null(data())){return()}
}
if(input$P == TRUE){
data( input$ds)
data = get(input$ds)
}
if(input$std == TRUE) {data = data.frame(standardize(data))}
if(input$std == TRUE) {data = data.frame(standardize(data))}
datareport = capture.output(print(summary(data)))
})
output$downloadReport2 <- downloadHandler(
filename = function() {
filetitle = paste("Summary_report")
paste(filetitle, ".doc", sep = "")
},
content = function(file) {
write.file(datasetInput4(), file)
}
)
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STAT documentation built on May 2, 2019, 2:18 a.m.
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knitr::opts_chunk$set(echo = TRUE) library(psycho) library(Hmisc) library(corrgram) library(dplyr) library(rpivotTable) library(psych) library(datasets)
sidebarPanel( inputPanel( checkboxInput("P","Check if you want to use pre-loaded datasets",value = TRUE), selectInput("ds","Choose dataset you wish to explore",choices = c("iris","esoph","anscombe","cars","attitude","chickwts","Orange","ToothGrowth","BOD")) ), inputPanel( fileInput("file", "Upload the *.csv file with headers"), checkboxInput("std","standardize",value = FALSE), downloadButton("downloadStdData", "Download dataset") ), inputPanel( uiOutput("vx"), uiOutput("vx2"), uiOutput("vx3") ), inputPanel( selectInput("col","Choose Color",choices = c("red","green","blue","yellow")) ), inputPanel( downloadButton("downloadPlot2", "Download Histogram"), downloadButton("downloadPlot3", "Download Pie Chart"), downloadButton("downloadPlot4", "Download Box Plot"), downloadButton("downloadPlot5", "Download Association Plot"), downloadButton("downloadPlot", "Download Correlation Plot"), downloadButton("downloadCorMat", "Download Correlation Matrix"), downloadButton("downloadReport", "Download Descriptives Report"), downloadButton("downloadReport2", "Download Summary Report") ) ) mainPanel( tabsetPanel(type = "tab", tabPanel("Descriptives", verbatimTextOutput("AD")), tabPanel("Histogram",plotOutput("HG")), tabPanel("Pie Chart",plotOutput("PC")), tabPanel("Box Plot",plotOutput("BP")), tabPanel("Association Plot",plotOutput("AP")), tabPanel("Correlation Plot",plotOutput("CP")), tabPanel("Correlation Summary",verbatimTextOutput("SUM")), tabPanel("Interactive Dashboard",rpivotTableOutput("PT")) ),width = 8 ) output$AD<-renderPrint({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ cat(sprintf("\nThis is about dataset : %s\n", input$ds)) data( input$ds) data = get(input$ds) } cat(sprintf("\nSnapshot of the dataset\n")) if(input$std == TRUE) {data = data.frame(standardize(data))} print(head(data,6)) cat(sprintf("\nSummary of the dataset\n\n")) print(summary(data)) df = select_if(data,is.numeric) cat(sprintf("\n\n Detailed descriptive statistics of Quantitative Variables are as follows\n\n")) print(describe(df)) }) output$CP<-renderPlot({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ cat(sprintf("\nThis is about dataset : %s\n", input$ds)) data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} corrgram(data,order = TRUE,lower.panel = panel.shade,upper.panel = panel.pie,main ="Corrgram") }) output$SUM<-renderPrint({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ cat(sprintf("\nThis is about dataset : %s\n", input$ds)) data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = select_if(data,is.numeric) cat(sprintf("\n Correlation Summary of the dataset\n")) cor = rcorr(as.matrix(df))$r print(cor) }) datasetInput1 <- reactive({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data_set = data.frame(standardize(data))} else {data_set = data} }) output$downloadStdData <- downloadHandler( filename = function() { filetitle = paste("dataset") paste(filetitle, ".csv", sep = "") }, content = function(file) { write.csv(datasetInput1(), file, row.names = FALSE) } ) output$downloadPlot<- downloadHandler( filename = function() { paste("Correlationplot", ".png", sep = "") }, content = function(file) { png(file) if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ cat(sprintf("\nThis is about dataset : %s\n", input$ds)) data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} corrgram(data,order = TRUE,lower.panel = panel.shade,upper.panel = panel.pie,main ="Corrgram") dev.off() }) datasetInput2 <- reactive({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = select_if(data,is.numeric) data = data.frame(rcorr(as.matrix(df))$r) }) output$downloadCorMat <- downloadHandler( filename = function() { filetitle = paste("dataset") paste(filetitle, ".csv", sep = "") }, content = function(file) { write.csv(datasetInput2(), file) } ) output$PT<-renderRpivotTable({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} rpivotTable(data) }) output$vx <- renderUI({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = select_if(data,is.numeric) selectInput("variablex","Select the Quantitative variable for histogram",choices = colnames(df),selected = "" ) }) output$HG<-renderPlot({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = select_if(data,is.numeric) attach(df) hist(get(input$variablex),col = input$col,main = "Histogram",xlab = input$variablex) }) output$downloadPlot2<- downloadHandler( filename = function() { paste("Histogram", ".png", sep = "") }, content = function(file) { png(file) if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = select_if(data,is.numeric) attach(df) hist(get(input$variablex),col = input$col,main = "Histogram",xlab = input$variablex) dev.off() }) output$vx2 <- renderUI({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = select_if(data,is.factor) selectInput("variablex2","Select the Qualitative variable for PieChart",choices = colnames(df),selected = "" ) }) output$vx3 <- renderUI({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = select_if(data,is.factor) selectInput("variablex3","Select the Second Qualitative variable",choices = colnames(df),selected = "" ) }) output$PC<-renderPlot({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = select_if(data,is.factor) attach(df) x = get(input$variablex2) frequency = table(x) lbls = paste(names(frequency), "\n", sep="") pct = round(frequency/sum(frequency)*100) lbls = paste(lbls, pct) # add percents to labels lbls = paste(lbls,"%",sep="") # ad % to labels pie(frequency,labels = lbls, col=rainbow(length(frequency)),main = input$variablex2) }) output$downloadPlot3<- downloadHandler( filename = function() { paste("Pie", ".png", sep = "") }, content = function(file) { png(file) if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = select_if(data,is.factor) attach(df) x = get(input$variablex2) frequency = table(x) lbls = paste(names(frequency), "\n", sep="") pct = round(frequency/sum(frequency)*100) lbls = paste(lbls, pct) # add percents to labels lbls = paste(lbls,"%",sep="") # ad % to labels pie(frequency,labels = lbls, col=rainbow(length(frequency)),main = input$variablex2) dev.off() }) output$BP<-renderPlot({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = data attach(df) boxplot(get(input$variablex) ~ get(input$variablex2),col = input$col,main = "Box Plot",xlab = input$variablex2,ylab = input$variablex) }) output$downloadPlot4<- downloadHandler( filename = function() { paste("BoxPlot", ".png", sep = "") }, content = function(file) { png(file) if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = data attach(df) boxplot(get(input$variablex) ~ get(input$variablex2),col = input$col,main = "Box Plot",xlab = input$variablex2,ylab = input$variablex) dev.off() }) output$AP<-renderPlot({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = select_if(data,is.factor) attach(df) x = get(input$variablex2) y = get(input$variablex3) frequency = table(x,y) assocplot(frequency,col =c("green","red"),xlab = input$variablex2,ylab = input$variablex3,main = "Association Plot") }) output$downloadPlot5<- downloadHandler( filename = function() { paste("AssociationPlot", ".png", sep = "") }, content = function(file) { png(file) if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} df = data attach(df) x = get(input$variablex2) y = get(input$variablex3) frequency = table(x,y) assocplot(frequency,col =c("green","red"),xlab = input$variablex2,ylab = input$variablex3,main = "Association Plot") dev.off() }) h6("", tags$img(src ="K.JPG", height= 400, width=400)) datasetInput3 <- reactive({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} if(input$std == TRUE) {data = data.frame(standardize(data))} df = select_if(data,is.numeric) datareport = capture.output(print(describe(df))) }) output$downloadReport <- downloadHandler( filename = function() { filetitle = paste("Descriptive_report") paste(filetitle, ".doc", sep = "") }, content = function(file) { write.file(datasetInput3(), file) } ) datasetInput4 <- reactive({ if(input$P == FALSE) { file1 = input$file if(is.null(file1)){return()} data = read.table(file = file1$datapath,sep =",",header = TRUE) if(is.null(data())){return()} } if(input$P == TRUE){ data( input$ds) data = get(input$ds) } if(input$std == TRUE) {data = data.frame(standardize(data))} if(input$std == TRUE) {data = data.frame(standardize(data))} datareport = capture.output(print(summary(data))) }) output$downloadReport2 <- downloadHandler( filename = function() { filetitle = paste("Summary_report") paste(filetitle, ".doc", sep = "") }, content = function(file) { write.file(datasetInput4(), file) } )
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