Class Activity 19

# List of required packages
library(tidyverse)
library(shiny)
library(dplyr)
library(babynames)

Question 1

We are utilizing the babynames dataset to explore and visualize how the popularity of specific names has evolved over time.

(a) Create a user interface (UI) by using textInput for the baby name input, selectInput for gender selection, and adding an actionButton to initiate the search.

ui <- fluidPage(
  titlePanel("Baby Names Trend"),
  sidebarLayout(
    sidebarPanel(
      textInput("name", "Enter a Baby Name:", "Emma"),
      selectInput("gender", "Select Gender:", choices = c("Male" = "M", "Female" = "F")),
      actionButton("goButton", "Show Trend")
    ),
    mainPanel(plotOutput("nameTrend"))
  )
)

(b) Filter the babynames dataset based on user inputs for name and gender by utilizing eventReactive to respond to the action button press, and apply filter within this reactive context, using isolate to access the inputs without establishing reactive dependencies.

server <- function(input, output) {
  # Use eventReactive to execute code in response to a specific action (button press)
  nameData <- eventReactive(input$goButton, {
    req(input$name) # Ensure the name input is not empty
    babynames %>% 
      filter(name == isolate(input$name), 
             sex == isolate(input$gender)) # Use isolate to prevent reactivity except on button press
  })
}

(c) Create a line plot to visualize the trend of a selected baby name over the years by using renderPlot, showing the number of occurrences (n) of the name across different years (year).

server <- function(input, output) {
   # Use eventReactive to execute code in response to a specific action (button press)
  nameData <- eventReactive(input$goButton, {
    req(input$name) # Ensure the name input is not empty
    babynames %>% 
      filter(name == isolate(input$name), 
             sex == isolate(input$gender)) # Use isolate to prevent reactivity except on button press
  })
  
  output$nameTrend <- renderPlot({
   # req(nameData())  # Ensure data is available before plotting
    ggplot(nameData(), aes(x = year, y = n)) +
      geom_line() +  
      labs(title = paste("Trend for name", isolate(input$name)),  # Use isolate to get name input without triggering reactivity
           x = "Year", y = "Number of Babies") +
      theme_minimal()  
  })
}

Remember, without isolate, any change to the inputs (input$name and input$gender) would immediately trigger the reactive expressions (nameData and the plotting logic within renderPlot) to re-execute. This means the plot would update every time the user types a letter in the name input field or changes the gender, rather than waiting for the user to press the goButton.

(d) Run the Shiny app by combining the UI and server components using shinyApp.

shinyApp(ui, server, options = list(height = 800))

(e). Deploying a Shiny App to shinyapps.io

Open an account on shinyapps.io and follow the steps to deploy one of the apps to shinyapps.io.

Step 1: Create Your Shiny App

Create a file named app.R in a new folder. This folder will contain all the necessary files for your app.

Step 2: Organize Your App Folder

Ensure your app.R file is saved in a dedicated folder for your app. This folder can also include any additional data files, data folder for data, or other resources your app needs.

Step 3: Deploy Your App to shinyapps.io

Before deploying, you’ll need to set up an account on shinyapps.io. Use the rsconnect package to authenticate your R session with your shinyapps.io account. You will need the API key from your shinyapps.io account dashboard.

library(rsconnect)
rsconnect::setAccountInfo(name='<account-name>',
                          token='<api-token>',
                          secret='<api-secret>')

Replace <account-name>, <api-token>, and <api-secret> with your actual account name and API key details. Navigate to your app folder in RStudio, or set the working directory to your app folder in R:

setwd("/path/to/your/app")

Deploy your app using the deployApp function:

rsconnect::deployApp()

Follow the prompts in the R console. Once the deployment process completes, you will receive a URL to access your app hosted on shinyapps.io.