My Data Product presentation - Diamonds

This peer assessed assignment has two parts. First, you will create a Shiny application and deploy it on Rstudio's servers. Second, you will use Slidify or Rstudio Presenter to prepare a reproducible pitch presentation about your application.

Try my app here. See the code in my github page here.

1. Write a shiny application with associated supporting documentation. The documentation should be thought of as whatever a user will

2. need to get started using your application.

3. Deploy the application on Rstudio's shiny server

4. Share the application link by pasting it into the provided text box

5. Share your server.R and ui.R code on github

1. Some form of input (widget: textbox, radio button, checkbox, …)

2. Some operation on the ui input in sever.R

3. Some reactive output displayed as a result of server calculations

4. You must also include enough documentation so that a novice user could use your application.

5. The documentation should be at the Shiny website itself. Do not post to an external link.

This app was create with a classic dataset about diamonds and contains the prices and other attributes of almost 54,000 diamonds.

Content

price - price in US dollars ($326–$18,823)

carat - weight of the diamond (0.2–5.01)

cut - quality of the cut (Fair, Good, Very Good, Premium, Ideal)

color - diamond colour, from J (worst) to D (best)

clarity a measurement of how clear the diamond is (I1 (worst), SI2, SI1, VS2, VS1, VVS2, VVS1, IF (best))

x length in mm (0–10.74)

y width in mm (0–58.9)

z depth in mm (0–31.8)

depth total depth percentage = z / mean(x, y) = 2 * z / (x + y) (43–79)

table width of top of diamond relative to widest point (43–95)

1. Select a sample size: how many samples do you want to analyze?
2. Select the attributes you would like to compare.
3. Select the length, the width and the depth of you plot
4. Enjoy ;)

carat : Carat weight of the diamond

cut : Describe cut quality of the diamond. Quality in increasing order Fair, Good, Very Good, Premium, Ideal

color : Color of the diamond, with D being the best and J the worst

clarity : How obvious inclusions are within the diamond:(in order from best to worst, FL = flawless, I3= level 3 inclusions) FL,IF, VVS1, VVS2, VS1, VS2, SI1, SI2, I1, I2, I3

depthdepth % : The height of a diamond, measured from the culet to the table, divided by its average girdle diameter

tabletable% : The width of the diamond's table expressed as a percentage of its average diameter

price : the price of the diamond

x : length mm

y : width mm

z : depth mm

library(shiny)
library(ggplot2)
library(markdown)

dataset <- diamonds

fluidPage(theme = "bootstrap.css",


          headerPanel("DIAMONDS\n"),
          h2("Analyze diamonds by their cut, color, clarity, price, and other attributes\n"),
          h3("Jéssica Félix, june 2019, Coursera Project\n"),

          sidebarPanel(

              sliderInput('sampleSize', 'Sample Size - instructions in: ', min=1, max=nrow(dataset),
                          value=min(1000, nrow(dataset)), step=500, round=0),

              selectInput('x', 'X', names(dataset)),
              selectInput('y', 'Y', names(dataset), names(dataset)[[2]]),
              selectInput('color', 'Color', c('None', names(dataset))),

              checkboxInput('jitter', 'Jitter'),
              checkboxInput('smooth', 'Smooth'),

              selectInput('facet_row', 'Facet Row', c(None='.', names(dataset))),
              selectInput('facet_col', 'Facet Column', c(None='.', names(dataset)))
          ),

          mainPanel(
              plotOutput('plot')
          )

)

library(shiny)
library(ggplot2)
library(markdown)

function(input, output) {

    dataset <- reactive({
        diamonds[sample(nrow(diamonds), input$sampleSize),]
    })

    output$plot <- renderPlot({

        p <- ggplot(dataset(), aes_string(x=input$x, y=input$y)) + geom_point()

        if (input$color != 'None')
            p <- p + aes_string(color=input$color)

        facets <- paste(input$facet_row, '~', input$facet_col)
        if (facets != '. ~ .')
            p <- p + facet_grid(facets)

        if (input$jitter)
            p <- p + geom_jitter()
        if (input$smooth)
            p <- p + geom_smooth()

        print(p)

    }, height=700)

}