Assignment 1

Author

Emma Whipkey

BAN 350 Assignment 1

Comparing Categories Using Gestalt Principles in Music Data

Rolling Stone’s 500 Greatest Albums of All Time attempts to rank the world’s best music albums based on the votes of music critics, artists, and industry figures. Originally published in 2003, the list has undergone several revisions, with the most recent update occurring in 2023. A look at the dataset summary reveals that this is the 2012 revised edition, as the most recent album release year is 2011.

Code
library(tidyverse)
top_albums <- read_csv(
  "https://jsuleiman.com/datasets/Rolling_Stones_Top_500_Albums.csv",
    locale = locale(encoding = "ISO-8859-2", asciify = TRUE))
summary(top_albums)
     Number           Year         Album              Artist         
 Min.   :  1.0   Min.   :1955   Length:500         Length:500        
 1st Qu.:125.8   1st Qu.:1970   Class :character   Class :character  
 Median :250.5   Median :1976   Mode  :character   Mode  :character  
 Mean   :250.5   Mean   :1979                                        
 3rd Qu.:375.2   3rd Qu.:1988                                        
 Max.   :500.0   Max.   :2011                                        
    Genre             Subgenre        
 Length:500         Length:500        
 Class :character   Class :character  
 Mode  :character   Mode  :character  
                                      
                                      
                                      

I chose to analyze two aspects of the dataset: count of artists with albums classified as Hip-Hop, and the rankings trend of The Rolling Stones albums over time.

Hip-Hop Artists with the Most Albums in the Top 500

Filtering the Genre column for albums classified as Hip-Hop returned 29 rows.

# A tibble: 29 × 6
   Number  Year Album                                      Artist Genre Subgenre
    <dbl> <dbl> <chr>                                      <chr>  <chr> <chr>   
 1     48  1988 It Takes a Nation of Millions to Hold Us … Publi… Hip … Conscio…
 2    118  2005 Late Registration                          Kanye… Hip … None    
 3    123  1986 Raising Hell                               Run D… Hip … None    
 4    134  1994 Ready to Die                               The N… Hip … Thug Rap
 5    138  1992 The Chronic                                Dr. D… Hip … Gangsta 
 6    144  1988 Straight Outta Compton                     N.W.A  Hip … Gangsta 
 7    153  1991 The Low End Theory                         A Tri… Hip … Conscio…
 8    219  1986 Licensed to Ill                            Beast… Hip … None    
 9    228  1987 Paid in Full                               Eric … Hip … None    
10    242  1984 Run D.M.C.                                 Run D… Hip … None    
# ℹ 19 more rows

Sorting by Artist count revealed that Kanye West and Jay-Z were tied for the most Hip-Hop albums in the Top 500, with 3 each. I chose is a standard horizontal bar chart to visualize the data, with artist name labels on the Y axis for better legibility. I also added a default fill aesthetic for the 21 discrete artists in the set.

Genre labels for each album in the dataset can be combined (eg, the Beastie Boys’ Paul’s Boutique is labeled as Hip Hop, Rock, Funk/Soul, therefore not included in the table), so an improved visualization could include any combined genres in the dataset that include Hip-Hop.

My visualization includes minor gridlines and a light grey background, but it isn’t possible for artists to have half of an album on the Top 500. A better visualization could keep the grey background, but remove the minor gridlines for less visual noise.

The Rolling Stones Album Rankings in the Top 500

Filtering the Artist column for albums by The Rolling Stones, (a partial namesake of Rolling Stone itself) returned 10 rows. The Rolling Stones are tied with with the Beatles for the second most albums in the Top 500.

# A tibble: 10 × 6
   Number  Year Album                    Artist             Genre       Subgenre
    <dbl> <dbl> <chr>                    <chr>              <chr>       <chr>   
 1      7  1972 Exile on Main St.        The Rolling Stones Rock        Blues R…
 2     32  1969 Let It Bleed             The Rolling Stones Rock        Blues R…
 3     58  1968 Beggars Banquet          The Rolling Stones Rock, Funk… Blues R…
 4     64  1971 Sticky Fingers           The Rolling Stones Rock        Classic…
 5    109  1966 Aftermath                The Rolling Stones Rock        Blues R…
 6    116  1965 Out of Our Heads         The Rolling Stones Rock        Blues R…
 7    180  1965 The Rolling Stones, Now! The Rolling Stones Rock, Blue… Pop Roc…
 8    213  1981 Tattoo You               The Rolling Stones Rock        Classic…
 9    270  1978 Some Girls               The Rolling Stones Rock        Blues R…
10    357  1967 Between the Buttons      The Rolling Stones Rock        Blues R…

My goal for this visualization is to see if The Rolling Stones’ album rankings on the Top 500 increased or decreased over time.By adding a trendline over a scatter plot of the table data, I can see that there is a slight decline overall from their earliest ranked album, 1965’s The Rolling Stones, Now!, to their latest ranked album, 1981’s Tattoo You. This might indicate a creative decline in the band’s output since 1972’s Exile on Main St., their highest ranked album. As the Y axis limit is large (0 to 500), I labeled the points with the numeric album ranking for better legibility. I also reversed the Y scale, so the higher ranked albums would appear closer to the top of the scatterplot.

Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.
`geom_smooth()` using formula = 'y ~ x'

As noted in Better Data Visualizations, scatterplots can be difficult for readers to fully understand, even with a trendline showing the general direction of the relationship between the points.

The visualization is also missing album titles; I had a difficult time labeling the points with the entire album names in a way that was readable, so I left the ranking labels only.

Conclusion

I chose two aspects of the Top 500 that are unrelated to each other for the most part - a variety of hip-hop artists, and a single rock band with ranked albums in three different decades. However, the wealth of information in the dataset could show how the waxing and waning popularity of the two genres over the decades affects rankings. Does the Rock genre, which dominates the list with 249 entries, start to disappear by the time hip-hop’s popularity starts increasing in the 1980s? Comparing the differences between the original 2003 list and its subsequent revisions could also reveal trends in music criticism over time.