꽃 종류별 원형그래프 포함 shiny

[11기_정주희]

library(shiny)

library(datasets)

library(data.table)

# Define UI ----

ui <- fluidPage(    

  # Give the page a title

  titlePanel("iris 데이터의 히스토그램, 사분위수, 원형 그래프"),

  # Generate a row with a sidebar

  sidebarLayout(      

    # Define the sidebar with one input

    sidebarPanel(

      selectInput("region", "컬럼:", 

                  choices= colnames(iris[1:4])),

      hr(),

      helpText("iris 컬럼의 히스토그램 그래프와 사분위수, 원형 그래프 ")

    ),

    # Create a spot for the barplot

    mainPanel(

      plotOutput("typePlot")  

    )

  )

)

# Define server logic ----

server <-function(input, output) {

  # Fill in the spot we created for a plot

  output$typePlot <- renderPlot({

    par(mar=c(0.1,0.1,1,0.1))

    par(mfrow=c(2,2))

    # 히스토그램 그래프

    hist( iris[ ,input$region ] , col="green",main='아이리스 Histogram',xlab=input$region)

    par(new=T)

    a = sort(iris[,input$region])

    plot(a,dnorm(a,mean=mean(a),sd=sd(a)),type='l',axes=FALSE,ann=FALSE,col='maroon')

    # 4분위수 그래프

    boxplot( iris[ ,input$region ] , col="medium purple",main='아이리스',xlab=input$region)

    # 원형 그래프

    x2 = iris[iris$Species=="setosa",]

    x3 = iris[iris$Species=="versicolor",]

    x4 = iris[iris$Species=="virginica",]

    cnt = data.table(setosa=sum(x2[ ,input$region ]),versicolor=sum(x3[ ,input$region ]),virginica=sum(x4[ ,input$region ]))

    cnt_labels <- round( cnt/sum(cnt) * 100, 1) 

    cnt_labels2 <-  paste( colnames(cnt_labels) ,cnt_labels ,'%') 

    pie(  t(cnt)  , col=rainbow(7), labels=cnt_labels2,main=c('꽃 종류별',input$region))

  })

}

# Run the app ----

shinyApp(ui = ui, server = server)

iris.Species

x3 = iris[iris$Species=="setosa",]

x3

x4 = iris[iris$Species=="versicolor",]

x5 = iris[iris$Species=="virginica",]

unique(iris$Species)

x3

sum(iris[ ,"Sepal.Length" ])

cnt = data.table(setosa=sum(x3$Sepal.Length),versicolor=sum(x4$Sepal.Length),virginical=sum(x5$Sepal.Length))

cnt

cnt_labels <- round( cnt/sum(cnt) * 100, 1) 

cnt_labels

b = round(x3/sum(x3)*100,1)

paste(colnames(b),b,'%')

pie(t(x3))

iris

cnt_labels2 <-  paste( colnames(cnt_labels) ,cnt_labels ,'%') 

pie(  t(cnt)  , col=rainbow(3), labels=cnt_labels2)

--------------------------------------------------------------------------------------------------

꽃 종류별 컬럼별 평균 크기 비율

library(shiny)

library(datasets)

library(data.table)

# Define UI ----

ui <- fluidPage(    

  # Give the page a title

  titlePanel("iris 데이터의 히스토그램, 사분위수, 원형 그래프"),

  # Generate a row with a sidebar

  sidebarLayout(      

    # Define the sidebar with one input

    sidebarPanel(

      selectInput("region", "컬럼:", 

                  choices= colnames(iris[1:4])),

      hr(),

      helpText("iris 컬럼의 히스토그램 그래프와 사분위수, 원형 그래프 ")

    ),

    # Create a spot for the barplot

    mainPanel(

      plotOutput("typePlot")  

    )

  )

)

# Define server logic ----

server <-function(input, output) {

  # Fill in the spot we created for a plot

  output$typePlot <- renderPlot({

    par(mar=c(0.1,0.1,1,0.1))

    par(mfrow=c(2,2))

    # 히스토그램 그래프

    hist( iris[ ,input$region ] , col="green",main='아이리스 Histogram',xlab=input$region)

    par(new=T)

    a = sort(iris[,input$region])

    plot(a,dnorm(a,mean=mean(a),sd=sd(a)),type='l',axes=FALSE,ann=FALSE,col='maroon')

    # 4분위수 그래프

    boxplot( iris[ ,input$region ] , col="medium purple",main='아이리스',xlab=input$region)

    # 원형 그래프

    x2 = iris[iris$Species=="setosa",]

    x3 = iris[iris$Species=="versicolor",]

    x4 = iris[iris$Species=="virginica",]

    cnt = data.table(setosa=mean(x2[ ,input$region ]),versicolor=mean(x3[ ,input$region ]),virginica=mean(x4[ ,input$region ]))

    cnt_labels <- round( cnt/sum(cnt) * 100, 1) 

    cnt_labels2 <-  paste( colnames(cnt_labels) ,cnt_labels ,'%') 

    pie(  t(cnt)  , col=rainbow(7), labels=cnt_labels2,main=c('꽃 종류별',input$region,'평균 크기 비율'))

  })

}

# Run the app ----

shinyApp(ui = ui, server = server)