Shiny App Project

R Markdown

This is an R Markdown document for my coding of shiny. For complete product, please visit the shiny-io site. < https://wo4yq3-stanley-cheng.shinyapps.io/ibm_project/>.

Trend in Demographics and Income Explore the difference between people who earn less than 50K and more than 50K. You can filter the data by country, then explore various demographic information.

# Load libraries
library(shiny)
library(tidyverse)
library(rio)
library(ggthemes)
library(rsconnect)

# Load dataset 
adult=import("adult.csv")
# Convert column names to lowercase for convenience 
names(adult)=tolower(names(adult))



# Application Layout
ui=shinyUI(fluidPage(
    br(),
    # TASK 1: Application title
    titlePanel("Trend in Demographics and Income"),
    p("Explore the difference between people who earn less than 50K and more than 50K. You can filter the data by country, then explore various demogrphic information."),
    
    # TASK 2: Add first fluidRow to select input for country
    fluidRow(
        column(12, 
               wellPanel(selectInput("country","Select Country",choices=c("United-States","Canada","Mexico","Germany","Philippines")))
        )  # add select input 
    ),
    
    # TASK 3: Add second fluidRow to control how to plot the continuous variables
    fluidRow(
        column(3, 
               wellPanel(
                   p("Select a continuous variable and graph type (histogram or boxplot) to view on the right."),
                   radioButtons("continuous_variable","Continuous",choices=c("age","hours_per_week")),   # add radio buttons for continuous variables
                   radioButtons("graph_type","Graph",choices=c("histogram","boxplot"))    # add radio buttons for chart type
               )
        ),column(9, plotOutput("p1"))  # add plot output
    ),
    
    # TASK 4: Add third fluidRow to control how to plot the categorical variables
    fluidRow(
        column(3, 
               wellPanel(
                   p("Select a categorical variable to view bar chart on the right. Use the check box to view a stacked bar chart to combine the income levels into one graph. "),
                   radioButtons("categorical_variable","Category",choices=c("education","workclass","sex")),    # add radio buttons for categorical variables
                   checkboxInput("is_stacked","Stack Bar",value=FALSE)     # add check box input for stacked bar chart option
               )
        ),
        column(9, plotOutput("p2"))  # add plot output
    )
)
)





# Define server logic
server=shinyServer(function(input, output) {
    adult=import("adult.csv")               # Read in data
    names(adult)=tolower(names(adult))      # Convert column names to lowercase for convenience 
    
    df_country <- reactive({
        adult %>% filter(native_country == input$country)
    })
    
    # TASK 5: Create logic to plot histogram or boxplot
    output$p1 <- renderPlot({
        if (input$graph_type == "histogram") {
            # Histogram
            ggplot(df_country(), aes_string(x =input$continuous_variable)) +
                geom_histogram(color="blue",fill="deepskyblue") +  # histogram geom
                labs(y="Number of People", title=paste("Trend of ",input$continuous_variable)) +  # labels
                facet_wrap(~prediction)+ # facet by prediction
                theme_light()
        }
        else {
            # Boxplot
            ggplot(df_country(), aes_string(y = input$continuous_variable)) +
                geom_boxplot(color="chocolate",fill="darkgoldenrod1") +  # boxplot geom
                coord_flip() +  # flip coordinates
                labs(x="Number of People", title=paste("Boxplot of",input$continuous_variable)) +  # labels
                facet_wrap(~prediction)+    # facet by prediction
                theme_light()
        }
        
    })
    
    # TASK 6: Create logic to plot faceted bar chart or stacked bar chart
    output$p2 <- renderPlot({
        # Bar chart
        p <- ggplot(df_country(), aes_string(x =input$categorical_variable)) +
            labs(y="Number of People",title=(paste("Trend of",input$categorical_variable))) +  # labels
            theme_light()+
            theme(axis.text.x=element_text(angle=45),legend.position="bottom")    # modify theme to change text angle and legend position
        
            
        if (input$is_stacked) {
            p + geom_bar(aes(fill=prediction))  # add bar geom and use prediction as fill
        }
        else{
            p + 
                geom_bar(aes_string(fill=input$categorical_variable)) + # add bar geom and use input$categorical_variables as fill 
                facet_wrap(~prediction)   # facet by prediction
        }
    })
    
})


shinyApp(ui,server)