DATA 607: Assignment 1
Farhana Akther
2023-01-26
Overview
The Ultimate Halloween Candy Power Ranking (https://fivethirtyeight.com/videos/the-ultimate-halloween-candy-power-ranking/) by Walt Hickey is an analysis about the most popular Halloween candies. Data was collected by creating a website (http://walthickey.com/2017/10/18/whats-the-best-halloween-candy/), where participants were shown presenting two fun-sized candies and asked to click on the one they would prefer to receive. In total, more than 269 thousand votes were collected from 8,371 different IP addresses. For our purposes, we will be focusing on the sugar content of top ten popular candies.
Load Libraries.
library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.4.0 ✔ purrr 1.0.1
## ✔ tibble 3.1.8 ✔ dplyr 1.0.10
## ✔ tidyr 1.3.0 ✔ stringr 1.5.0
## ✔ readr 2.1.3 ✔ forcats 0.5.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()Import file as CSV.
In this code we are uploading the data set from github account.
Candy <- read.csv("https://raw.githubusercontent.com/FarhanaAkther23/DATA607/main/Assignment%201/candy-data.csv") We are exploring our data in the following steps:
dim(Candy)## [1] 85 13There are 85 different candies and 13 different variables resulted from data dimension
head(Candy, 15)## competitorname chocolate fruity caramel peanutyalmondy nougat
## 1 100 Grand 1 0 1 0 0
## 2 3 Musketeers 1 0 0 0 1
## 3 One dime 0 0 0 0 0
## 4 One quarter 0 0 0 0 0
## 5 Air Heads 0 1 0 0 0
## 6 Almond Joy 1 0 0 1 0
## 7 Baby Ruth 1 0 1 1 1
## 8 Boston Baked Beans 0 0 0 1 0
## 9 Candy Corn 0 0 0 0 0
## 10 Caramel Apple Pops 0 1 1 0 0
## 11 Charleston Chew 1 0 0 0 1
## 12 Chewey Lemonhead Fruit Mix 0 1 0 0 0
## 13 Chiclets 0 1 0 0 0
## 14 Dots 0 1 0 0 0
## 15 Dum Dums 0 1 0 0 0
## crispedricewafer hard bar pluribus sugarpercent pricepercent winpercent
## 1 1 0 1 0 0.732 0.860 66.97173
## 2 0 0 1 0 0.604 0.511 67.60294
## 3 0 0 0 0 0.011 0.116 32.26109
## 4 0 0 0 0 0.011 0.511 46.11650
## 5 0 0 0 0 0.906 0.511 52.34146
## 6 0 0 1 0 0.465 0.767 50.34755
## 7 0 0 1 0 0.604 0.767 56.91455
## 8 0 0 0 1 0.313 0.511 23.41782
## 9 0 0 0 1 0.906 0.325 38.01096
## 10 0 0 0 0 0.604 0.325 34.51768
## 11 0 0 1 0 0.604 0.511 38.97504
## 12 0 0 0 1 0.732 0.511 36.01763
## 13 0 0 0 1 0.046 0.325 24.52499
## 14 0 0 0 1 0.732 0.511 42.27208
## 15 0 1 0 0 0.732 0.034 39.46056Head brought first 15 rows from data set.
tail(Candy, 15)## competitorname chocolate fruity caramel peanutyalmondy nougat
## 71 Sugar Babies 0 0 1 0 0
## 72 Sugar Daddy 0 0 1 0 0
## 73 Super Bubble 0 1 0 0 0
## 74 Swedish Fish 0 1 0 0 0
## 75 Tootsie Pop 1 1 0 0 0
## 76 Tootsie Roll Juniors 1 0 0 0 0
## 77 Tootsie Roll Midgies 1 0 0 0 0
## 78 Tootsie Roll Snack Bars 1 0 0 0 0
## 79 Trolli Sour Bites 0 1 0 0 0
## 80 Twix 1 0 1 0 0
## 81 Twizzlers 0 1 0 0 0
## 82 Warheads 0 1 0 0 0
## 83 Welch's Fruit Snacks 0 1 0 0 0
## 84 Werther's Original Caramel 0 0 1 0 0
## 85 Whoppers 1 0 0 0 0
## crispedricewafer hard bar pluribus sugarpercent pricepercent winpercent
## 71 0 0 0 1 0.965 0.767 33.43755
## 72 0 0 0 0 0.418 0.325 32.23100
## 73 0 0 0 0 0.162 0.116 27.30386
## 74 0 0 0 1 0.604 0.755 54.86111
## 75 0 1 0 0 0.604 0.325 48.98265
## 76 0 0 0 0 0.313 0.511 43.06890
## 77 0 0 0 1 0.174 0.011 45.73675
## 78 0 0 1 0 0.465 0.325 49.65350
## 79 0 0 0 1 0.313 0.255 47.17323
## 80 1 0 1 0 0.546 0.906 81.64291
## 81 0 0 0 0 0.220 0.116 45.46628
## 82 0 1 0 0 0.093 0.116 39.01190
## 83 0 0 0 1 0.313 0.313 44.37552
## 84 0 1 0 0 0.186 0.267 41.90431
## 85 1 0 0 1 0.872 0.848 49.52411Tail brought last 15 rows from data set.
Rename column headers
Candy2 <- rename(Candy,c("CandyName"="competitorname", "Sugarpercent"="sugarpercent", "Popularity"="winpercent"))in the code above we changed the name of the column
Select a Subset
How many candies have popularity over 70%?
pop_70<-subset(Candy2, Popularity > 70, select=c(CandyName,Sugarpercent,Popularity))
pop_70## CandyName Sugarpercent Popularity
## 29 Kit Kat 0.313 76.76860
## 33 Peanut butter M&M's 0.825 71.46505
## 37 Milky Way 0.604 73.09956
## 43 Nestle Butterfinger 0.604 70.73564
## 52 Reese's Miniatures 0.034 81.86626
## 53 Reese's Peanut Butter cup 0.720 84.18029
## 54 Reese's pieces 0.406 73.43499
## 55 Reese's stuffed with pieces 0.988 72.88790
## 65 Snickers 0.546 76.67378
## 80 Twix 0.546 81.64291In the code above, we created a subset pop_70 and we can see there are 10 different candies with popularity over 70%.
Bar Plots
Which of the popular top 10 candies has less sugar?
barplot(height = pop_70$Sugarpercent, names = pop_70$CandyName, las = 3, cex.axis = 1, main = "Sugar Percentage by Fun Size Candy")
in the code above we have created graph using barplot to compare top 10 popular candy with sugar content.
Conclusion
Based on the analyses and visualizations, we can see that although Reese’s Miniatures are one of the most popular top 10 fun size cadies, it contains 0.95 percent sugar than Reese’s stuffed with pieces. Therefore, the preliminary results suggest that Reese’s Miniatures can be a preferable choice for those who want to control their sugar intake.