arbys <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - Arbys.csv")
blimpie <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - blimpie (1).csv")
buffaloWildWings <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - buffalowildwings (1).csv")
burgerKing <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - burgerking.csv")
carlsJr <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - carsljr (1).csv")
chickFilA <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - chickfila.csv")
chilis <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - chilis (1).csv")
delTaco <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - deltaco (1).csv")
inNOut <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - innout (1).csv")
## Warning in read.table(file = file, header = header, sep = sep, quote = quote, :
## incomplete final line found by readTableHeader on
## '/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - innout
## (1).csv'
jackInTheBox <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - JackintheBox.csv")
KFC <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - KFC.csv")
mcdonalds <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - mcdonalds.csv")
popeyes <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - Popeyes.csv")
raisingCanes <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - raisingcanes (1).csv")
sonic <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - Sonic Drive-In.csv")
tacoBell <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - tacobell.csv")
wendys <- read.csv("/Users/alainaliu/Downloads/sdsw-project-main/sdsw restaurants - wendys.csv")
arbys <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - Arbys.csv")
blimpie <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - blimpie (1).csv")
buffaloWildWings <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - buffalowildwings (1).csv")
burgerKing <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - burgerking.csv")
carlsJr <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - carsljr (1).csv")
chickFilA <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - chickfila.csv")
chilis <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - chilis (1).csv")
delTaco <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - deltaco (1).csv")
inNOut <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - innout (1).csv")
jackInTheBox <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - JackintheBox.csv")
KFC <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - KFC.csv")
mcdonalds <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - mcdonalds.csv")
popeyes <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - Popeyes.csv")
raisingCanes <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - raisingcanes (1).csv")
sonic <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - Sonic Drive-In.csv")
tacoBell <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - tacobell.csv")
wendys <- read.csv("/Users/brend/OneDrive/Documents/Calorie Data/sdsw-project-main/sdsw restaurants - wendys.csv")
# combine everything into one dataset
alldata1 <- bind_rows(arbys, blimpie, buffaloWildWings, burgerKing, carlsJr, chickFilA, chilis, delTaco, inNOut, jackInTheBox, KFC, mcdonalds, popeyes, raisingCanes, sonic, tacoBell, wendys)
alldata <- alldata1[complete.cases(alldata1$Price),]
# replacing restaurant names
alldata[alldata == "BurgerKing"] <- "Burger King"
alldata[alldata == "Chick-fil-a"] <- "Chick-Fil-A"
alldata[alldata == "In n Out"] <- "In-N-Out Burger"
alldata[alldata == "JackInTheBox"] <- "Jack in the Box"
alldata[alldata == "McDonalds"] <- "McDonald's"
alldata[alldata == "SonicDrive-In"] <- "Sonic Drive-In"
alldata[alldata == "TacoBell"] <- "Taco Bell"
# for graphs
colors <- c("Arby's"="#990000", "Blimpie"="#FF3333", "Buffalo Wild Wings"="#FF6600", "Burger King"="#FF9900", "Carl's Jr."="#FFCC00", "Chick-Fil-A"="#FFFF00", "Chili's"="#99FF33", "Del Taco"="#66CC00", "In-N-Out Burger"="#339900", "Jack in the Box"="#006600", "KFC"="#339966", "McDonald's"="#009999", "Popeyes"="#0099CC", "Raising Cane's"="#3399FF", "Sonic Drive-In"="#0066CC", "Taco Bell"="#0000CC", "Wendy's"="#6600CC")
# graph all restaurants price to calories
checkboxInput("color",
label="Color by Restaurant?",
value=FALSE)
fluidRow(
column(6,
renderPlot({
price_cal <- ggplot(data=alldata, aes(x=Calories, y=Price))
if (input$color==TRUE){
price_cal + geom_point(aes(color=Restaurant)) + scale_color_manual(values=colors)
} else {
price_cal + geom_point()
}
})),
column(6,
renderPlot({
ss_cal <- ggplot(data=alldata, aes(x=Calories, y=ServingSize))
if (input$color==TRUE){
ss_cal + geom_point(aes(color=Restaurant)) + scale_color_manual(values=colors)
} else {
ss_cal + geom_point()
}
}))
)
# graph individual restaurants price to calories
checkboxGroupInput("restaurant",
label="Show:",
c("Arby's", "Blimpie", "Buffalo Wild Wings", "Burger King", "Carl's Jr.", "Chick-Fil-A", "Chili's", "Del Taco", "In-N-Out", "Jack in the Box", "KFC", "McDonald's", "Popeyes", "Raising Cane's", "Sonic Drive-In", "Taco Bell", "Wendy's"),
inline=TRUE
)
fluidRow(
column(6,
renderPlot({
new_alldata <- alldata[alldata$Restaurant==input$restaurant,]
ggplot(data=new_alldata, aes(x=Calories, y=Price)) +
geom_point(aes(color=Restaurant), size=1, alpha=0.5) +
scale_color_manual(values=colors) +
xlim(0, 2000) + ylim(0, 30)
})),
column(6,
renderPlot({
new_alldata <- alldata[alldata$Restaurant==input$restaurant,]
ggplot(data=new_alldata, aes(x=ServingSize, y=Price)) +
geom_point(aes(color=Restaurant), size=1, alpha=0.5) +
scale_color_manual(values=colors) +
xlim(0, 2000) + ylim(0, 30)
}))
)
# Calories to Price ratio (The amount paid per 100 calories)
alldata$Calories_to_Price <- c(((alldata$Price)*100)/(alldata$Calories))
# Serving Size to Price ratio (The amount paid per 10 grams)
alldata$ServSize_to_Price <- c(((alldata$Price)*10)/(alldata$ServingSize))
# Protein to Calories ratio (The amount of Protein in grams per 10 calories)
alldata$Protein_to_Calories <- c(((alldata$Protein)*10)/(alldata$Calories))
# Carbohydrates to Calories ratio (The amount of Carbohydrates in grams per 10 calories)
alldata$Carbohydrates_to_Calories <- c(((alldata$Carbohydrates)*10)/(alldata$Calories))
# Sodium to Calories ratio (The amount of sodium in milligrams per 10 calories)
alldata$Sodium_to_Calories <- c(((alldata$Sodium)*10)/(alldata$Calories))
# Saturated Fat to Calories ratio (The amount of saturated fat in grams per 10 calories)
alldata$SaturatedFat_to_Calories <- c(((alldata$SaturatedFat)*10)/(alldata$Calories))
# Dietary Fiber to Calories ratio (The amount of Dietary Fiber in grams per 100 calories)
alldata$DietaryFiber_to_Calories <- c(((alldata$DietaryFiber)*100)/(alldata$Calories))
CtoPdata <- alldata %>%
dplyr::select(Restaurant, Item, Price, Calories, Calories_to_Price)
DT::datatable(CtoPdata, filter="bottom")
Graphs
# top 10 Calories to Price ratio
ggplot(data=arrange(alldata, Calories_to_Price)[1:10,], aes(x=reorder(Item, Calories_to_Price), y=Calories_to_Price, fill=Restaurant)) +
geom_bar(stat='identity') +
scale_fill_manual(values=colors) +
theme(axis.text.x=element_text(angle=45, hjust=1, size=8)) +
labs(y='Price per 100 Cal', x='Menu Items')
# bottom 10 Calories to Price ratio
ggplot(data=arrange(alldata, -Calories_to_Price)[1:10,], aes(x=reorder(Item, -Calories_to_Price), y=Calories_to_Price, fill=Restaurant)) +
geom_bar(stat='identity') +
scale_fill_manual(values=colors) +
theme(axis.text.x=element_text(angle=45, hjust=1, size=8)) +
labs(y='Price per 100 Cal', x='Menu Items')
# top 10 Serving Size to Price ratio
ggplot(data=arrange(alldata, ServSize_to_Price)[1:10,], aes(x=reorder(Item, ServSize_to_Price), y=ServSize_to_Price, fill=Restaurant)) +
geom_bar(stat='identity') +
scale_fill_manual(values=colors) +
theme(axis.text.x=element_text(angle=45, hjust=1, size=8)) +
labs(y='Price per 10 grams', x='Menu Items')
# bottom 10 Serving Size to Price ratio
ggplot(data=arrange(alldata, -ServSize_to_Price)[1:10,], aes(x=reorder(Item, -ServSize_to_Price), y=ServSize_to_Price, fill=Restaurant)) +
geom_bar(stat='identity') +
scale_fill_manual(values=colors) +
theme(axis.text.x=element_text(angle=45, hjust=1, size=8)) +
labs(y='Price per 10 grams', x='Menu Items')
# creating a dataframe of averages
alldata_avg <- alldata %>%
group_by(Restaurant) %>%
summarize(AvgServingSize = mean(ServingSize),
AvgPrice = mean(Price),
AvgCalories = mean(Calories),
AvgCaloriesFroMFat = mean(CaloriesFromFat),
AvgTotalFat = mean(TotalFat),
AvgSaturatedFat = mean(SaturatedFat),
AvgTransFat = mean(TransFat),
AvgCholesterol = mean(Cholesterol),
AvgSodium = mean(Sodium),
AvgCarbohydrates = mean(Carbohydrates),
AvgDietaryFiber = mean(DietaryFiber),
AvgSugars = mean(Sugars),
AvgProtein = mean(Protein),
AvgCalories_to_Price = mean(Calories_to_Price),
AvgServSize_to_Price = mean(ServSize_to_Price),
AvgProtein_to_Calories = mean(Protein_to_Calories),
AvgCarbohydrates_to_Calories = mean(Carbohydrates_to_Calories),
AvgSodium_to_Calories = mean(Sodium_to_Calories),
AvgSaturatedFat_to_Calories = mean(SaturatedFat_to_Calories),
AvgDietaryFiber_to_Calories = mean(DietaryFiber_to_Calories))
par(mfrow = c(1, 2))
# Average Calories to Price ratio for each restaurant
ggplot(alldata_avg, aes(x=AvgCalories_to_Price, y=reorder(Restaurant, -AvgCalories_to_Price))) +
geom_bar(stat='identity') +
theme(axis.text.x=element_text(angle=50, hjust=1, size=7)) +
labs(x='Price per 100 Calories', y='Restaurants')
# Average Serving Size to Price ratio for each restaurant
ggplot(alldata_avg[complete.cases(alldata_avg$AvgServSize_to_Price),], aes(x=AvgServSize_to_Price, y=reorder(Restaurant, -AvgServSize_to_Price))) +
geom_bar(stat='identity') +
theme(axis.text.x=element_text(angle=50, hjust=1, size=7)) +
labs(x='Price per 10 grams', y='Restaurants')
par(mfrow = c(3, 2))
# Average Protein to Calories ratio for each restaurant
ggplot(alldata_avg, aes(x=AvgProtein_to_Calories, y=reorder(Restaurant, -AvgProtein_to_Calories))) +
geom_bar(stat='identity') +
theme(axis.text.x=element_text(angle=50, hjust=1, size=7)) +
labs(x='Avg Protein (g) per 10 Calories', y='Restaurants')
# Average Carbohydrates to Calories ratio for each restaurant
ggplot(alldata_avg, aes(x=AvgCarbohydrates_to_Calories, y=reorder(Restaurant, -AvgCarbohydrates_to_Calories))) +
geom_bar(stat='identity') +
theme(axis.text.x=element_text(angle=50, hjust=1, size=7)) +
labs(x='Avg Carbohydrates (g) per 10 Calories', y='Restaurants')
# Average Sodium to Calories ratio for each restaurant
ggplot(alldata_avg, aes(x=AvgSodium_to_Calories, y=reorder(Restaurant, -AvgSodium_to_Calories))) +
geom_bar(stat='identity') +
theme(axis.text.x=element_text(angle=50, hjust=1, size=7)) +
labs(x='Avg Sodium (mg) per 10 Calories', y='Restaurants')
# Average Saturated Fat to Calories ratio for each restaurant
ggplot(alldata_avg, aes(x=AvgSaturatedFat_to_Calories, y=reorder(Restaurant, -AvgSaturatedFat_to_Calories))) +
geom_bar(stat='identity') +
theme(axis.text.x=element_text(angle=50, hjust=1, size=7)) +
labs(x='Avg Saturated Fat (g) per 10 Calories', y='Restaurants')
# Average Dietary Fiber to Calories ratio for each restaurant
ggplot(alldata_avg, aes(x=AvgDietaryFiber_to_Calories, y=reorder(Restaurant, -AvgDietaryFiber_to_Calories))) +
geom_bar(stat='identity') +
theme(axis.text.x=element_text(angle=50, hjust=1, size=7)) +
labs(x='Avg Dietary Fiber (g) per 10 Calories', y='Restaurants')
# Average Protein for each restaurant
ggplot(alldata_avg, aes(x=AvgProtein, y=reorder(Restaurant, -AvgProtein))) +
geom_bar(stat='identity') +
theme(axis.text.x=element_text(angle=50, hjust=1, size=7)) +
labs(x='Protein in grams', y='Restaurants')
