Building a Lyrics Profanity Analyzer with R Shiny

A few weeks ago, a family member asked me to make them a Spotify playlist with recent rap hits. To avoid including anything excessively profane, I’d pull up the song lyrics on genius.com and manually search for potentially offensive words or phrases. Looking to streamline this process (and have a bit of fun with Shiny Apps), I built a simple tool that quickly measures profanity in any song, based on lyrics from genius.com.

The app is embedded below, but you can find a full-screen version here. Here are some sample songs to try out:

  • “Rap God”: https://genius.com/Eminem-rap-god-lyrics
  • “The London”: https://genius.com/Young-thug-the-london-lyrics
  • “Money in the Grave”: https://genius.com/Drake-money-in-the-grave-lyrics

Building the App

The first step was to create a list of offensive words to check song lyrics against. The list I used was by developed by Luis von Ahn. As he notes on his resource page, “the list contains some words that many people won’t find offensive, but it’s a good start for anybody wanting to block offensive or profane terms on their site.”

Next, I needed to develop a function to scrape the lyrics from genius.com, tidy the text into a data frame format, and summarize the profanity by count in descending order.

Finally, I needed an interface for users to interact with. Luckily, the shiny package makes this easy. After importing the profanity list, writing the genius.com scrape function, and building the Shiny app interface locally, I was ready to deploy it to shinyapps.io.

Voila! Now I have a basic tool to quickly summarize profanity in any song found on genius.com.

Hopefully this will come in handy next time I need to put together a “family friendly” mix for events, parties, or road trips. You can find the GitHub repo for this project here, and can access the Shiny app directly here.

Feature photo by Matthew Henry from Burst.

Interactive Investment Tool with R Shiny

R Shiny is a fantastic framework to quickly develop and launch interactive data applications. I recently wrote some investing advice and was looking for a way to illustrate two case studies. Building on an RStudio template, I created a tool to visualize the return of an investment over time, allowing the user to modify each parameter and observe its effect:

Click here for the full-page (non-embedded) version.

Find the full code here or below:

library(FinCal)
library(ggplot2)
library(tidyr)
library(shinythemes)
library(scales)

# Define UI for application that draws a histogram
ui <- shinyUI(fluidPage(theme = shinytheme("spacelab"),
  # Application title
  titlePanel("The Potential for Growth: Two Case Studies"),
  p('An interactive tool to accompany the ', a(href = 'http://unboxed-analytics.com/life-hacking/fundamentals-of-investing/', '"Fundamentals of Investing"'), 'post.'),
  
  # Sidebar with a slider input for number of bins
  sidebarLayout(
    sidebarPanel(
      numericInput(
        inputId = "rate",
        label = "Yearly Rate of Return",
        value = .06,
        min = .01,
        max = .15,
        step = .01
      ),
      p("Represented as a decimal."),
      p(".06 = 6%"),
      numericInput(
        inputId = "years",
        label = "Number of Years",
        value = 43,
        min = 3,
        max = 50,
        step = 1
      ),
      numericInput(
        inputId = "pv",
        label = "Initial Outlay",
        value = 2000,
        min = 1000,
        max = 100000,
        step = 1000.
      ),
      numericInput(
        inputId = "pmt",
        label = "Monthly Contribution",
        value = 0,
        min = 0,
        max = 10000,
        step = 100
      ),
      numericInput(
        inputId = "type",
        label = "Payment Type",
        value = 0,
        min = 0,
        max = 1,
        step = 1
      ),
      p("Indicates if payments occur at the end of each period (Payment Type = 0) or if payments occur at the beginning of each period (Payment Type = 1).")
      ),
    
    mainPanel(plotOutput("finPlot"),
              p("The grey line represents PRINCIPAL and the blue line represents PRINCIPAL + INTEREST."),
              p("Case 1: Suppose you have $2,000 to invest. You use that money to purchase a low-cost, tax-efficient, diversified mutual fund offering an approximate yearly return of 6%."),
              p("You purchase the mutual fund on your 22nd birthday and don’t check your account until your 65th birthday on the day of retirement. After 43 years, you would have over $26,200! Your money has doubled four times."),
              p("Case 2: Suppose again you have $2,000 today to invest. You purchase shares of the same mutual and now, in addition to the initial investment, purchase $100 of additional shares each month. [Adjust the 'Monthly Contribution' sidebar parameter]"),
              p("How much would you have at the end of 43 years? Over $268,400! You have passively created wealth through the market."))
  )
))

# Define server logic required to draw a histogram
server <- shinyServer(function(input, output) {
  output$finPlot <- renderPlot({

    # processing
    total <- fv(r = input$rate/12, n = 0:(12*input$years), pv = -input$pv, pmt = -input$pmt, type = input$type)
    principal <- seq(input$pv, input$pv + (input$years*12)*(input$pmt+.000000001), input$pmt + .000000001)
    interest <- total - principal
    df <- data.frame(period = 0:(12*input$years), total, principal)
    
    # plotting
    ggplot(df, aes(x = period)) + 
      geom_line(aes(y = total), col = "blue", size = .85) +
      geom_line(aes(y = principal), col = "black", size = .85) +
      labs(x = "Period",
           y = "") + 
      scale_y_continuous(labels = dollar) +
      theme(legend.position="bottom") +
      theme(legend.title = element_blank()) +
      theme_minimal()
  })
})

# Run the application
shinyApp(ui = ui, server = server)