“How Notre Dame’s fight song stacks up” from Our Guide To The Exuberant Nonsense Of College Fight Songs

Link to the original article containing the graphic recreated: https://projects.fivethirtyeight.com/college-fight-song-lyrics/ - Using the fight_songs data set from the fivethirtyeight package

This figure is a graphical representation of the college fight songs from 65 schools in the Power Five conferences (the ACC, Big Ten, Big 12, Pac-12 and SEC), specifically highlighting Notre Dame. These songs are sung with great pride at sporting events or played by the marching band in support of the college team towards victory. Each college’s fight song is unique bringing all the students together on special occasions. For the version of each song available on Spotify, the tempo and duration was analyzed and plotted.

Data wrangling-visualization statements creating the figure

1. load data set

#install.packages("fivethirtyeight")
library(fivethirtyeight)
## Some larger datasets need to be installed separately, like senators and
## house_district_forecast. To install these, we recommend you install the
## fivethirtyeightdata package by running:
## install.packages('fivethirtyeightdata', repos =
## 'https://fivethirtyeightdata.github.io/drat/', type = 'source')
data(fight_songs)
library(ggplot2)
fightsongs <- fight_songs

#install.packages("dplyr") 
library(dplyr)
## Warning: package 'dplyr' was built under R version 4.1.2
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(extrafont)
## Registering fonts with R

2. Initial scatterplot of bpm vs sec_duration

## does accuracy of colors matter
ggplot(fightsongs, aes(x=sec_duration, y = bpm, color = school)) +
  geom_point(size = 4, alpha = 0.2, show.legend = FALSE) +
  ggtitle("How Notre Dame's fight song stacks up") +
  theme(plot.title = element_text(hjust=0.5)) +
  xlab("Duration") +
  ylab("Beats per minute")

3. Finding the mean of Duration and Beats per minute to add vertical and horizontal dotted lines

secDurmean = fightsongs %>%
  summarize(mean_sec_duration = mean(sec_duration, na.rm = TRUE))

BPMmean = fightsongs %>%
  summarize(mean_BPM = mean(bpm, na.rm = TRUE))

secDurmean <- secDurmean[[1]]
BPMmean <- BPMmean[[1]]

4. Labeling Notre Dame and filling the point black

fight_songs_plot <- ggplot(fightsongs, aes(x=sec_duration, y = bpm, color = school)) +
  geom_point(size = 4, alpha = 0.2, show.legend = FALSE) +
  ggtitle("How Notre Dame's fight song stacks up") +
  xlab("Duration") +
  ylab("Beats per minute") +
  geom_point(data = fightsongs %>% filter(school == "Notre Dame"), color = "black", size = 4, alpha = 1) + 
  geom_text(data = fightsongs %>% filter(school == "Notre Dame"), label= "Notre Dame", color = "black", vjust = -1.5, fontface = "bold", size = 3) 
  
  
fight_songs_plot

5. Adding x axis and y axis tick marks and horizontal line for Beats per minute and Duration averages

fight_songs_plot <- ggplot(fightsongs, aes(x=sec_duration, y = bpm, color = school)) +
  geom_point(size = 4, alpha = 0.2, show.legend = FALSE) +
  ggtitle("How Notre Dame's fight song stacks up") +
  xlab("Duration") +
  ylab("Beats per minute") +
  geom_point(data = fightsongs %>% filter(school == "Notre Dame"), color = "black", size = 4, alpha = 1) + 
  geom_text(data = fightsongs %>% filter(school == "Notre Dame"), label= "Notre Dame", color = "black", vjust = -1.5, fontface = "bold", size = 3) +
  
  scale_x_continuous(breaks = seq(0, 180, by = 20), expand = c(0, 0), limits = c(-5, 185), labels=c("0 sec", "20", "40", "60", "80", "100", "120", "140", "160", "180")) +
  scale_y_continuous(breaks = seq(60, 200, by = 20), limits = c(55,205), labels=c("60", "80", "100", "120", "140", "160", "180", "200bpm")) + 
  
  geom_segment(aes(x = secDurmean, y = 55, xend = secDurmean, yend = 97), color = "black", linetype = "dotted") +
  annotate("text", x=71.90769, y=107, label="AVERAGE", angle=90, size = 2) +
  geom_segment(aes(x = secDurmean, y = 117, xend = secDurmean, yend = 205), linetype = "dotted", color = "black") +
  
   geom_segment(aes(x = 0, y = BPMmean, xend = 138, yend = BPMmean), color = "black", linetype = "dotted") +
  annotate("text", x=145, y=128.8, label="AVERAGE", size = 2) +
  geom_segment(aes(x = 154, y = BPMmean, xend = 185, yend = BPMmean), linetype = "dotted", color = "black")

fight_songs_plot

6. Adding labels for the four quadrants on the graph for how fast the song is played and how long it lasts

fight_songs_plot <- ggplot(fightsongs, aes(x=sec_duration, y = bpm, color = school)) +
  geom_point(size = 4, alpha = 0.2, show.legend = FALSE) +
  ggtitle("How Notre Dame's fight song stacks up") +
  xlab("Duration") +
  ylab("Beats per minute") +
  geom_point(data = fightsongs %>% filter(school == "Notre Dame"), color = "black", size = 4, alpha = 1) + 
  geom_text(data = fightsongs %>% filter(school == "Notre Dame"), label= "Notre Dame", color = "black", vjust = -1.5, fontface = "bold", size = 3) +
  
  scale_x_continuous(breaks = seq(0, 180, by = 20), expand = c(0, 0), limits = c(-5, 185), labels=c("0 sec", "20", "40", "60", "80", "100", "120", "140", "160", "180")) +
  scale_y_continuous(breaks = seq(60, 200, by = 20), limits = c(55,205), labels=c("60", "80", "100", "120", "140", "160", "180", "200bpm")) + 
  
  geom_segment(aes(x = secDurmean, y = 55, xend = secDurmean, yend = 97), color = "black", linetype = "dotted") +
  annotate("text", x=71.90769, y=107, label="AVERAGE", angle=90, size = 2) +
  geom_segment(aes(x = secDurmean, y = 117, xend = secDurmean, yend = 205), linetype = "dotted", color = "black") +
  
   geom_segment(aes(x = 0, y = BPMmean, xend = 138, yend = BPMmean), color = "black", linetype = "dotted") +
  annotate("text", x=145, y=128.8, label="AVERAGE", size = 2) +
  geom_segment(aes(x = 154, y = BPMmean, xend = 185, yend = BPMmean), linetype = "dotted", color = "black") +

  annotate("text", x=33, y=192, label= "Fast and short", family = "mono", size = 3.5) + 
  annotate("text", x = 33, y=58, label = "Slow but short", family = "mono", size = 3.5) +
  annotate("text", x=147, y=192, label= "Fast but long", family = "mono", size = 3.5) + 
  annotate("text", x = 147, y=58, label = "Slow and long", family = "mono", size = 3.5) 

fight_songs_plot

7. Visual customization for graph

fight_songs_plot <- ggplot(fightsongs, aes(x=sec_duration, y = bpm, color = school)) +
  geom_point(size = 4, alpha = 0.2, show.legend = FALSE) +
  ggtitle("How Notre Dame's fight song stacks up") +
  xlab("Duration") +
  ylab("Beats per minute") +
  geom_point(data = fightsongs %>% filter(school == "Notre Dame"), color = "black", size = 4, alpha = 1) + 
  geom_text(data = fightsongs %>% filter(school == "Notre Dame"), label= "Notre Dame", color = "black", vjust = -1.5, fontface = "bold", size = 3) +
  
  
  annotate("text", x=33, y=192, label= "Fast and short", family = "mono", size = 3.5) + 
  annotate("text", x = 33, y=58, label = "Slow but short", family = "mono", size = 3.5) +
  annotate("text", x=147, y=192, label= "Fast but long", family = "mono", size = 3.5) + 
  annotate("text", x = 147, y=58, label = "Slow and long", family = "mono", size = 3.5) +
  
  
  scale_x_continuous(breaks = seq(0, 180, by = 20), expand = c(0, 0), limits = c(-5, 185), labels=c("0 sec", "20", "40", "60", "80", "100", "120", "140", "160", "180")) +
  scale_y_continuous(breaks = seq(60, 200, by = 20), limits = c(55,205), labels=c("60", "80", "100", "120", "140", "160", "180", "200bpm")) + 
  
  geom_segment(aes(x = secDurmean, y = 55, xend = secDurmean, yend = 97), color = "black", linetype = "dotted") +
  annotate("text", x=71.90769, y=107, label="AVERAGE", angle=90, size = 2) +
  geom_segment(aes(x = secDurmean, y = 117, xend = secDurmean, yend = 205), linetype = "dotted", color = "black") +
  
   geom_segment(aes(x = 0, y = BPMmean, xend = 138, yend = BPMmean), color = "black", linetype = "dotted") +
  annotate("text", x=145, y=128.8, label="AVERAGE", size = 2) +
  geom_segment(aes(x = 154, y = BPMmean, xend = 185, yend = BPMmean), linetype = "dotted", color = "black") +
  
  theme_bw() +
  theme(plot.title = element_text(hjust=0.5, face = "bold"), legend.position='none',  axis.text = element_text(face = "plain", family = "Courier New"), aspect.ratio = .8, panel.grid.minor = element_blank(),axis.title = element_text(face= "bold"), panel.border = element_blank(), axis.ticks = element_blank(), panel.grid = element_line(color = "grey")) +
  geom_vline(xintercept = 0, size = .2)
  
fight_songs_plot