What do you look for in a candy?
This interactive app was created with the Candy Power Ranking data from FiveThirtyEight.
##### Candies in bubbles:

Please select your desired ingredients, sugar percentile, and price percentile in a candy in the left sidebar. Sugar percentile is the percentile of sugar it falls under within the data set. Price percentile is the unit price percentile compared to the rest of the set.

Please also select whether you would like the bubbles to be sized according to the sugar percentile or the price percentile. A larger bubble corresponds to a higher percentile on the 0-100% scale. We'll find the perfect candy for you.

Note that if no ingredients are selected, all the candies will be displayed. The colors in the bubble are only for asthetics; their shades and saturation do not indicate any categorization or ordering.

##### Notes on the dataset:

For binary variables, 1 means yes, 0 means no. SugarPer is the percentile of sugar it falls under within the data set. PricePer is the unit price percentile compared to the rest of the set.

This interactive app was created with the Candy Power Ranking data from FiveThirtyEight.
##### Notes on the dataset:

In October of 2017, FiveThirtyEight ran an experiment where they had users on their site fill out a brief survey. Each user who took the survey was faced with two candies and asked to choose which they would prefer. In total, there were over 259,000 matchups. The winning percentage corresponds to the percent of matchups that a particular candy won. You can use the visual on the other tab to explore a potential relationship between price or sugar content and winning percentage. The full FiveThirtyEight article can be found here.

#### The Hunt For The Perfect Candy by Chase Williamson, Haochen Wang

``````#Load libraries
library(shiny)
library(dplyr)
library(bubbles)
library(ggplot2)
library(shinythemes)
library(colorspace)
library(plotly)

#Import dataset

#Basic data cleaning
candy_data <- candy_data %>%
mutate(competitorname = gsub("Õ", "'", candy_data\$competitorname)) %>%
mutate(sugarpercent = 100*sugarpercent, pricepercent = 100*pricepercent) %>%
rename("Brand" = competitorname,
"Chocolate" = chocolate,
"Fruity" = fruity,
"Nuts" = peanutyalmondy,
"Nougat" = nougat,
"Wafer" = crispedricewafer,
"Hard" = hard,
"Bar" = bar,
"Caramel" = caramel,
"Pluribus" = pluribus,
"SugarPer" = sugarpercent,
"PricePer" = pricepercent,
"WinPer" = winpercent) %>%
select(-Pluribus)

#Nice Labels
x_label <- data.frame(var = c("SugarPer", "PricePer", "WinPer"),
names = c("Sugar Percentile", "Price Percentile", "Win Percentage"))
y_label <- data.frame(var = c("SugarPer", "PricePer", "WinPer"),
names = c("Sugar Percentile", "Price Percentile", "Win Percentage"))

##### UI Side ######

# Use taglist layout - this allows us to have multiple navigation tabs
ui = tagList(
navbarPage(
theme = shinytheme("paper"),  # <--- To use a theme, uncomment this
"shinythemes",

tabPanel("Find the perfect candy for you!",

#Define sidebar
sidebarPanel(
helpText("What do you look for in a candy?"),

#Create checkbox inputs
checkboxInput(inputId = "choc", label = "Chocolate?", value = FALSE),
checkboxInput(inputId = "frui", label = "Fruity?", value = FALSE),
checkboxInput(inputId = "pean", label = "Peanuts & Almonds?", value = TRUE),
checkboxInput(inputId = "noug", label = "Nougat?", value = FALSE),
checkboxInput(inputId = "cris", label = "Crisped Rice Wafer?", value = FALSE),
checkboxInput(inputId = "hard", label = "Hard?", value = FALSE),
checkboxInput(inputId = "bar", label = "A bar?", value = FALSE),
checkboxInput(inputId = "car", label = "Caramel?", value = FALSE),

#Create radio button input for size
c("Sugar (Percentile)" = "SugarPer",
"Price (Percentile)" = "PricePer")),

#Create slider input for filtering based on sugar percentile
sliderInput("SugarPer",
"Sugar Percentile:",
min = 0,
max = 100,
value = c(0, 100)),

#Create slider input for filtering based on price percentile
sliderInput("PricePer",
"Price Percentile:",
min = 0,
max = 100,
value = c(0, 100)),

helpText("This interactive app was created with the", a("Candy Power Ranking data",
href="https://github.com/fivethirtyeight/data/tree/master/candy-power-ranking"),
"from", a("FiveThirtyEight.", href="http://fivethirtyeight.com/")),

#Create main panel with two tabs: one for visual and one for data
mainPanel(
tabsetPanel(type = "tabs",
tabPanel("Visual",
h5("Candies in bubbles:"),
p("Please select your desired ingredients, sugar percentile, and price percentile in a candy
in the left sidebar. Sugar percentile is the percentile of sugar
it falls under within the data set. Price percentile is the unit price percentile compared to
the rest of the set."),
p("Please also select whether you would like the bubbles to be sized according
to the sugar percentile or the price percentile. A larger bubble corresponds to a
higher percentile on the 0-100% scale. We'll find the perfect candy for you."),
p("Note that if no ingredients are selected, all the candies will be displayed. The colors
in the bubble are only for asthetics; their shades and saturation do not indicate any
categorization or ordering."),
bubbles::bubblesOutput(outputId = "bubble")),
tabPanel("Data",
h5("Notes on the dataset:"),
p("For binary variables, 1 means yes, 0 means no. SugarPer is the percentile of sugar
it falls under within the data set. PricePer is the unit price percentile compared to
the rest of the set."),
DT::dataTableOutput(outputId = "table")))
)
),

tabPanel("Explore different candies in a plot!",

#Define sidebar
sidebarPanel(

#Create radio buttons for selecting x axis variable
c("Sugar (Percentile)" = "SugarPer",
"Price (Percentile)" = "PricePer",
"Win Percentage" = "WinPer")),

#Create radio buttons for selecting y axis variable
c("Sugar (Percentile)" = "SugarPer",
"Price (Percentile)" = "PricePer",
"Win Percentage" = "WinPer")),

helpText("This interactive app was created with the", a("Candy Power Ranking data",
href="https://github.com/fivethirtyeight/data/tree/master/candy-power-ranking"),
"from", a("FiveThirtyEight.", href="http://fivethirtyeight.com/"))
),

#Put output graphic and description of text in second main panel
mainPanel(
tabsetPanel(type = "tabs",
tabPanel("Visual",
plotlyOutput(outputId = "plot")),
tabPanel("Description",
h5("Notes on the dataset:"),
p("In October of 2017, FiveThirtyEight ran an experiment where they had users on their site fill out a brief survey.
Each user who took the survey was faced with two candies and asked to choose which they would prefer. In total, there were over 259,000
matchups. The winning percentage corresponds to the percent of matchups that a particular candy won. You can use the visual on the other tab
to explore a potential relationship between price or sugar content and winning percentage. The full FiveThirtyEight article can be found",
a("here.", href="http://fivethirtyeight.com/features/the-ultimate-halloween-candy-power-ranking/"))
)
)
)
)
)
)

##### Server Side #####
server<-function(input, output){

#Label names
xlab_var_name <- reactive({
filter(x_label, var == input\$xaxis) %>%
select(names) #.\$names
})

ylab_var_name <- reactive({
y_label %>%
filter(var == input\$yaxis) %>%
select(names) #.\$names
})

#Create reactive dataset
data_react <- reactive({
candy_data %>%
filter(if(input\$choc == TRUE){Chocolate == 1}else{Chocolate %in% 0:1}) %>%
filter(if(input\$frui == TRUE){Fruity == 1}else{Fruity %in% 0:1}) %>%
filter(if(input\$pean == TRUE){Nuts == 1}else{Nuts %in% 0:1}) %>%
filter(if(input\$noug == TRUE){Nougat == 1}else{Nougat %in% 0:1}) %>%
filter(if(input\$cris == TRUE){Wafer == 1}else{Wafer %in% 0:1}) %>%
filter(if(input\$hard == TRUE){Hard == 1}else{Hard %in% 0:1}) %>%
filter(if(input\$bar == TRUE){Bar == 1}else{Bar %in% 0:1}) %>%
filter(if(input\$car == TRUE){Caramel == 1}else{Caramel %in% 0:1}) %>%
filter(PricePer >= input\$PricePer, PricePer <= input\$PricePer) %>%
filter(SugarPer >= input\$SugarPer, SugarPer <= input\$SugarPer) %>%
mutate(Size = get(input\$size)) %>%
select(-WinPer)
})

#Print data table
output\$table <- DT::renderDataTable({
if (nrow(data_react()) == 0)
return()
DT::datatable(data = data_react(), rownames = FALSE)
})

#Make bubbles
output\$bubble <- bubbles::renderBubbles({
if (nrow(data_react()) == 0)
return()
bubbles(value = data_react()\$Size,
label = data_react()\$Brand,
color = rainbow_hcl(nrow(data_react())))
})

#Create plotly output for second visual
output\$plot <- renderPlotly({
ggplot(data = candy_data, mapping = aes_string(x = input\$xaxis, y = input\$yaxis, color = "Brand")) +
geom_point() +
scale_color_manual(values = rainbow_hcl(nrow(candy_data))) +
theme(legend.position = "none") +
labs(x = as.character(xlab_var_name()[1,1]), y = as.character(ylab_var_name()[1,1]))

})

if(!is.null(data_react())) {