Justin Duke did an exceptional job with his analysis of Pitchfork using Pandas. I was inspired to take a different look at this Pitchfork data using R and some plot.ly. My main focus was looking at music that is categorized as “Best New Music” on the site. I was curious if any record labels were more likely to get the honor, and wanted just a general look at artists with the honor and any other general trends.

I used the same dataset Justin did and loaded it into R. Top priority was getting a dataset that that was only “Best New Music.” This can be done with the which function in R (see code). Once there I just had two questions to answer (1) which record labels had the most artist with “Best New Music” and (2) which artists had been granted the honor the most times in the set.

Creating subsets of data was a little tricky because of the weird spacing in the dataset but I was able to get it done. Once subsets were created for both artists and labels, plotting was straightforward with plot.ly.

Best New Music Over Time

I wanted to plot all of the “Best New Music” based on publishing date. One thing I found surprising is that Kanye West is the only artist who got a perfect score in this data set for My Beautiful Dark and Twisted Fantasy.

Best New Music By Label

      

I choose labels that had at least 3 albums with the honor. It became clear that a handful of labels (4AD, Domino and Sub Pop) owned when it came to getting this honor. Looking closer at 4AD, they have some of more interesting indie musicians including Grimes, Tune-yards and Purity Ring.  

Best New Music By Artist

I choose artists who had the honor at least 3 times. Animal Collective, Deer Hunter and Kanye West have been granted the honor the most times (5). Many of the other artists in this set are to be expected, the “darlings” on indie music like Arcade Fire, GrizzlyBear and Vampire Weekend.

I use Pitchfork as a music discovery tool and I tend to agree with their reviews. This was a fun exercise in better understanding albums that get honored on the site.

Code: