Super Bowl Ads
MGinorio
Super Bowl Analysis
The American Super Bowl is a statement in the Advertisement industry due to the creative nature of their ads. Every year many brands showcase their best pieces of advertisement and see which team did it better
This time we are asking the question - what is behind the creation of the ads? Was it funny? did it use sex to sell the product? did it feature a celebrity?
Problem Statement
The aim of this analysis is to determine which category predominates in the super bowl add arena. Is it sex, comedy, animals or celebrities?
Implementation
The data was scraped and manipulated accordingly for the analysis. The data was then reviewed graphically to determine what is the most used cateogry, how many times have been used over the years.
Results
Overview
Super Bowl
url.show("https://projects.fivethirtyeight.com/super-bowl-ads/")Packages
#Packages used
library(tidytext)
library(DT)
library(tm)## Loading required package: NLPlibrary(tidyverse)## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --## v ggplot2 3.3.3 v purrr 0.3.4
## v tibble 3.0.5 v dplyr 1.0.3
## v tidyr 1.1.2 v stringr 1.4.0
## v readr 1.4.0 v forcats 0.5.1## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x ggplot2::annotate() masks NLP::annotate()
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(stringr)
library(magrittr)##
## Attaching package: 'magrittr'## The following object is masked from 'package:purrr':
##
## set_names## The following object is masked from 'package:tidyr':
##
## extractlibrary(leaflet)
library(ggplot2)
library(dplyr)
library(plotly)##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layoutlibrary(forcats)1.- Data Exploration
1.1 Summary
GITHUB - place the original .csv in a github Repository and have R read from the link.
superbowl_ads <-read.csv("https://raw.githubusercontent.com/mgino11/Super_Bowl_Ads_Analisys/main/HW_1_superbowl-ads.csv")
glimpse(superbowl_ads)## Rows: 244
## Columns: 11
## $ year <int> 2018, 2020, 2006, 2018, 2003, 2020, 2020,...
## $ brand <chr> "Toyota", "Bud Light", "Bud Light", "Hynu...
## $ superbowl_ads_dot_com_url <chr> "https://superbowl-ads.com/good-odds-toyo...
## $ youtube_url <chr> "https://www.youtube.com/watch?v=zeBZvwYQ...
## $ funny <chr> "False", "True", "True", "False", "True",...
## $ show_product_quickly <chr> "False", "True", "False", "True", "True",...
## $ patriotic <chr> "False", "False", "False", "False", "Fals...
## $ celebrity <chr> "False", "True", "False", "False", "False...
## $ danger <chr> "False", "True", "True", "False", "True",...
## $ animals <chr> "False", "False", "True", "False", "True"...
## $ use_sex <chr> "False", "False", "False", "False", "True...1.2 Counting Qualitative Data
Brands - Who has the most adds?
From the information below we are able to determine that the brand with the greatest amount of ads is Budlight, followed by Budweiser and in third place we can Find Doritos.
superbowl_ads %>%
count(brand) %>%
arrange(desc(n))## brand n
## 1 Bud Light 60
## 2 Budweiser 43
## 3 Doritos 25
## 4 Pepsi 25
## 5 Hynudai 22
## 6 Coca-Cola 21
## 7 E-Trade 13
## 8 Kia 13
## 9 NFL 11
## 10 Toyota 11Sex
How many times a brand has used adds associated with sex?
superbowl_ads %>%
count(use_sex) %>%
arrange(desc(n))## use_sex n
## 1 False 181
## 2 True 63Animals
How many times a brand has used adds associated with animals?
superbowl_ads %>%
count(animals) %>%
arrange(desc(n))## animals n
## 1 False 155
## 2 True 89Funny
How many times a brand has used adds associated with comedy?
superbowl_ads %>%
count(funny) %>%
arrange(desc(n))## funny n
## 1 True 168
## 2 False 762.- Data Wrangling
2.1 Subsets
Subset1 - Superbowl_ads_use
We subset data in order to understand it better. Subset_1 allows us to see the a new data frame including variables like
- Year
- Brand
- Use_sex
- Animals
- Funny
- Celebrity
superbowl_ads %>% select(year, brand, funny, celebrity, animals, use_sex)## year brand funny celebrity animals use_sex
## 1 2018 Toyota False False False False
## 2 2020 Bud Light True True False False
## 3 2006 Bud Light True False True False
## 4 2018 Hynudai False False False False
## 5 2003 Bud Light True False True True
## 6 2020 Toyota True True True False
## 7 2020 Coca-Cola True True True False
## 8 2020 Kia False True False False
## 9 2020 Hynudai True True True False
## 10 2020 Budweiser False True False False
## 11 2010 Hynudai False False False False
## 12 2010 Bud Light True False False True
## 13 2007 Budweiser True False True True
## 14 2002 Budweiser False False True False
## 15 2020 NFL False True False False
## 16 2017 NFL False False False False
## 17 2005 Bud Light True False True True
## 18 2009 Pepsi True False False False
## 19 2004 Bud Light True False True True
## 20 2020 Doritos True True True False
## 21 2007 Bud Light True False False False
## 22 2020 Pepsi False True False False
## 23 2019 Hynudai True True False False
## 24 2009 Budweiser False False True False
## 25 2011 Kia True False False True
## 26 2019 Doritos False True False False
## 27 2019 Pepsi True True False True
## 28 2013 Hynudai True False True False
## 29 2019 NFL True True False False
## 30 2011 Coca-Cola False False False False
## 31 2019 Pepsi True True False False
## 32 2016 Hynudai True False True False
## 33 2010 Bud Light True False False False
## 34 2000 E-Trade True False True False
## 35 2001 Bud Light True False True False
## 36 2018 Doritos True True False False
## 37 2001 Budweiser True False False False
## 38 2018 Coca-Cola False True False False
## 39 2013 Hynudai False False True False
## 40 2004 Pepsi True False True False
## 41 2018 Kia False True False False
## 42 2018 Pepsi False True False False
## 43 2018 NFL True True False False
## 44 2010 E-Trade True False False False
## 45 2017 NFL False True False False
## 46 2000 E-Trade True False False False
## 47 2007 E-Trade True False False False
## 48 2000 Budweiser True False False False
## 49 2013 Doritos True False True False
## 50 2013 Budweiser False False False True
## 51 2007 Doritos True False False True
## 52 2009 Budweiser True False True False
## 53 2012 E-Trade True False False False
## 54 2019 Bud Light True False False False
## 55 2017 Kia True True True False
## 56 2007 Bud Light True False False False
## 57 2011 Bud Light True False True False
## 58 2016 Pepsi False True False False
## 59 2009 Hynudai True False False False
## 60 2011 Coca-Cola True False True False
## 61 2016 Hynudai True True True True
## 62 2009 Doritos True False False False
## 63 2010 Doritos True False False False
## 64 2015 Doritos True False False True
## 65 2007 Coca-Cola False False True False
## 66 2019 Toyota False False False False
## 67 2002 Budweiser True False False False
## 68 2014 Coca-Cola True False False False
## 69 2004 Budweiser True False False False
## 70 2016 Coca-Cola True True False False
## 71 2015 Budweiser True False True False
## 72 2016 Hynudai True True False False
## 73 2001 Bud Light True False False True
## 74 2003 Bud Light True False False False
## 75 2000 Bud Light True False False False
## 76 2018 Coca-Cola False False False False
## 77 2001 Pepsi True False False True
## 78 2014 Doritos True False True False
## 79 2016 Budweiser False True False False
## 80 2004 Budweiser False False True False
## 81 2015 Budweiser False False True False
## 82 2016 Kia True True False False
## 83 2017 Budweiser False False False False
## 84 2000 Budweiser True False True False
## 85 2009 Coca-Cola False False True False
## 86 2015 Doritos True False True False
## 87 2004 Toyota True False False False
## 88 2016 NFL False True False False
## 89 2017 Hynudai False False False False
## 90 2012 Bud Light True False True True
## 91 2008 Budweiser False False True False
## 92 2013 Hynudai True False True False
## 93 2010 Doritos True False False False
## 94 2016 Bud Light True True True False
## 95 2019 Toyota False False False False
## 96 2009 Bud Light True False False False
## 97 2019 Budweiser False False True False
## 98 2003 Bud Light True False False True
## 99 2019 Coca-Cola False False True False
## 100 2012 Hynudai True False False False
## 101 2011 Hynudai True False False False
## 102 2015 Kia True True True True
## 103 2014 Budweiser False False True False
## 104 2007 Bud Light True False False False
## 105 2008 Hynudai False False False False
## 106 2010 NFL False False False False
## 107 2005 Pepsi True False False False
## 108 2018 Budweiser False False False False
## 109 2018 Bud Light True False True False
## 110 2004 Bud Light True False True True
## 111 2002 Budweiser True False False False
## 112 2006 Budweiser True False False False
## 113 2014 Bud Light False True True True
## 114 2009 Coca-Cola True False True False
## 115 2014 Bud Light True True False True
## 116 2003 Bud Light True False False True
## 117 2014 Toyota True True True False
## 118 2009 Bud Light True False False True
## 119 2014 Kia False True False False
## 120 2014 Hynudai True True False True
## 121 2013 Bud Light True True True True
## 122 2008 Bud Light True False False False
## 123 2003 Budweiser True False False False
## 124 2013 Bud Light True True False False
## 125 2011 Doritos True False True False
## 126 2005 Bud Light True False False False
## 127 2005 Budweiser True False True False
## 128 2014 Doritos True False True False
## 129 2008 Bud Light True False False False
## 130 2012 Pepsi False True False False
## 131 2012 Doritos True False True False
## 132 2012 Toyota True False True True
## 133 2016 Doritos True False False False
## 134 2002 Bud Light True False True True
## 135 2002 Bud Light True False False False
## 136 2013 E-Trade True False True False
## 137 2008 Bud Light True False True False
## 138 2012 Coca-Cola False False True False
## 139 2004 Pepsi True False False False
## 140 2010 Doritos True False True False
## 141 2012 Kia True True False True
## 142 2012 NFL False True False False
## 143 2005 Bud Light True False False True
## 144 2010 Hynudai False True False False
## 145 2004 Bud Light True False False False
## 146 2008 Bud Light True False False True
## 147 2016 Toyota True False False False
## 148 2006 Bud Light True False False False
## 149 2007 Coca-Cola False False True False
## 150 2007 Budweiser False False True False
## 151 2013 Doritos True False False False
## 152 2010 Bud Light True True False False
## 153 2009 Doritos True False True True
## 154 2009 Coca-Cola True True False False
## 155 2009 Pepsi False True False False
## 156 2001 E-Trade False False True False
## 157 2018 Bud Light True False True False
## 158 2015 Doritos True False False True
## 159 2010 Kia True False True True
## 160 2008 Doritos True False False False
## 161 2012 Coca-Cola False False True False
## 162 2011 Hynudai False False True False
## 163 2008 Coca-Cola True True False False
## 164 2000 Bud Light True False True True
## 165 2019 Kia False False True False
## 166 2002 Bud Light True False False True
## 167 2013 Kia True False True True
## 168 2008 Pepsi True True False True
## 169 2019 Bud Light True False False False
## 170 2011 Hynudai False False False False
## 171 2008 Bud Light True True False True
## 172 2008 Bud Light True True False True
## 173 2010 E-Trade True False False True
## 174 2013 Budweiser False False False True
## 175 2001 Pepsi True False False True
## 176 2018 Coca-Cola False False False True
## 177 2003 Bud Light True False False False
## 178 2011 Pepsi True False False True
## 179 2018 E-Trade True False False True
## 180 2016 Budweiser False False True False
## 181 2008 Coca-Cola True True True False
## 182 2013 Kia True False False True
## 183 2014 Coca-Cola False False True False
## 184 2012 Budweiser False False True False
## 185 2004 Bud Light True False True False
## 186 2007 Bud Light True True False False
## 187 2007 Budweiser False True False False
## 188 2019 Kia False False False False
## 189 2002 Budweiser True False False True
## 190 2010 E-Trade True False False False
## 191 2003 Bud Light True False False False
## 192 2018 Toyota True False False False
## 193 2003 Budweiser True False True False
## 194 2013 Budweiser False False True False
## 195 2010 Budweiser True False True False
## 196 2003 Bud Light True False True False
## 197 2002 E-Trade True False True True
## 198 2006 Budweiser True False False False
## 199 2012 Coca-Cola False False True False
## 200 2019 Bud Light True False False False
## 201 2007 Toyota False False False False
## 202 2014 Hynudai True False False True
## 203 2006 Pepsi True True False False
## 204 2006 Pepsi True True False True
## 205 2015 Pepsi False False True False
## 206 2012 Bud Light False False False False
## 207 2009 Doritos True False False False
## 208 2006 Budweiser True False True True
## 209 2014 Bud Light False False False False
## 210 2005 Pepsi True True False True
## 211 2005 Bud Light True True True True
## 212 2007 Bud Light True False True False
## 213 2005 Pepsi True True False True
## 214 2015 Budweiser False False True False
## 215 2019 Bud Light True False True False
## 216 2004 Bud Light True True False True
## 217 2003 Budweiser True False False True
## 218 2009 E-Trade True False False False
## 219 2013 Pepsi True False False True
## 220 2004 Budweiser True True True True
## 221 2009 Hynudai False False False False
## 222 2014 Budweiser False False True False
## 223 2003 Pepsi True True False False
## 224 2015 Coca-Cola False False False False
## 225 2003 NFL False True False False
## 226 2012 Doritos True False False False
## 227 2002 Pepsi False True False True
## 228 2002 Bud Light True True False True
## 229 2000 Budweiser True False False False
## 230 2001 Bud Light True True False True
## 231 2013 Hynudai False False False False
## 232 2015 Toyota False False False False
## 233 2000 Budweiser True False True False
## 234 2001 Doritos True True False True
## 235 2016 Doritos True False True False
## 236 2008 Bud Light True False False False
## 237 2007 Doritos True False False True
## 238 2001 NFL False True False False
## 239 2001 Pepsi True True True True
## 240 2014 NFL False False False False
## 241 2012 Budweiser False False True True
## 242 2001 Pepsi True True False False
## 243 2001 E-Trade True False False False
## 244 2001 Budweiser False True False Falsehead(superbowl_ads)## year brand
## 1 2018 Toyota
## 2 2020 Bud Light
## 3 2006 Bud Light
## 4 2018 Hynudai
## 5 2003 Bud Light
## 6 2020 Toyota
## superbowl_ads_dot_com_url
## 1 https://superbowl-ads.com/good-odds-toyota/
## 2 https://superbowl-ads.com/2020-bud-light-seltzer-inside-posts-brain/
## 3 https://superbowl-ads.com/2006-bud-light-bear-attack/
## 4 https://superbowl-ads.com/hope-detector-nfl-super-bowl-lii-hyundai/
## 5 https://superbowl-ads.com/2003-bud-light-hermit-crab/
## 6 https://superbowl-ads.com/2020-toyota-go-places-with-cobie-smulders/
## youtube_url funny show_product_quickly
## 1 https://www.youtube.com/watch?v=zeBZvwYQ-hA False False
## 2 https://www.youtube.com/watch?v=nbbp0VW7z8w True True
## 3 https://www.youtube.com/watch?v=yk0MQD5YgV8 True False
## 4 https://www.youtube.com/watch?v=lNPccrGk77A False True
## 5 https://www.youtube.com/watch?v=ovQYgnXHooY True True
## 6 https://www.youtube.com/watch?v=f34Ji70u3nk True True
## patriotic celebrity danger animals use_sex
## 1 False False False False False
## 2 False True True False False
## 3 False False True True False
## 4 False False False False False
## 5 False False True True True
## 6 False True True True Falsecreate data frame using Tibble
superbowl_ads2 <- as_tibble(superbowl_ads)
colnames(superbowl_ads2)## [1] "year" "brand"
## [3] "superbowl_ads_dot_com_url" "youtube_url"
## [5] "funny" "show_product_quickly"
## [7] "patriotic" "celebrity"
## [9] "danger" "animals"
## [11] "use_sex"Factor $ Levels
Subset_1 = superbowl_ads2
In order to understand Categorical Data we need to use Levels and factors. The package used for this task is forcats
glimpse(superbowl_ads2)## Rows: 244
## Columns: 11
## $ year <int> 2018, 2020, 2006, 2018, 2003, 2020, 2020,...
## $ brand <chr> "Toyota", "Bud Light", "Bud Light", "Hynu...
## $ superbowl_ads_dot_com_url <chr> "https://superbowl-ads.com/good-odds-toyo...
## $ youtube_url <chr> "https://www.youtube.com/watch?v=zeBZvwYQ...
## $ funny <chr> "False", "True", "True", "False", "True",...
## $ show_product_quickly <chr> "False", "True", "False", "True", "True",...
## $ patriotic <chr> "False", "False", "False", "False", "Fals...
## $ celebrity <chr> "False", "True", "False", "False", "False...
## $ danger <chr> "False", "True", "True", "False", "True",...
## $ animals <chr> "False", "False", "True", "False", "True"...
## $ use_sex <chr> "False", "False", "False", "False", "True...superbowl_ads2 %>%
mutate(funny = fct_lump(funny, n = 50)) %>%
count(funny)## # A tibble: 2 x 2
## funny n
## * <fct> <int>
## 1 False 76
## 2 True 168Subset_2
superbowl_ads2 %>%
count(use_sex, celebrity)## # A tibble: 4 x 3
## use_sex celebrity n
## <chr> <chr> <int>
## 1 False False 135
## 2 False True 46
## 3 True False 41
## 4 True True 223.- Graphs
subset_1
We want to interpret graphically the frequency of ads that use sex
ggplot(superbowl_ads2, aes(x = use_sex)) +
geom_bar() +
coord_flip()
We want to interpret graphically the frequency of funny ads
ggplot(superbowl_ads2, aes(x = funny)) +
geom_bar() +
coord_flip()
We want to compare the use of sex in ads vs. the use of comedy. We can clearly see that comedy has been used more than sex.
ggplot(superbowl_ads2, aes(x = funny, fill = use_sex)) +
geom_density(col = NA, alpha = 0.55)
4.- Conclusion
Super Bowl Ads
SEX VS. COMEDY
Thanks to the Data Wrangling and Graphs we can now understand that most of ads we see have more inclination for the use of sex than comedy. And since we determined earlier - Budlight + Budweiser + Doritos are the brands with the most amunt of ads over the years.
ggplot(superbowl_ads2, aes(x = funny)) +
geom_bar() +
coord_flip()
ggplot(superbowl_ads2, aes(x = use_sex)) +
geom_bar() +
coord_flip()
SEX vs. funny (different view)
Brands seem to be more interested in pursuing the use of sex in ads instead of comedy.
ggplot(superbowl_ads2, aes(x = funny, fill = use_sex)) +
geom_density(col = NA, alpha = 0.55)