The best hip-hop songs of all time, visualized

Hi, this is Simon, I am a software engineer at Datawrapper. For this edition of the weekly chart, I visualized the greatest hip-hop songs of all time, a list originally assembled by BBC Music.

Earlier this year, BBC Music asked more than 100 critics, artists, and other music industry folks from 15 countries for their five favorite hip-hop tracks. Then they broke down the results of the poll into one definitive list. But BBC Music didn’t just publish a best-of list, they also published the complete poll results and a description of the simple algorithm they ranked the songs with. Using that data and algorithm, I recreated a searchable data table of more than 300 hip-hop songs.

Juicy by The Notorious B.I.G. is ranked first by a wide margin. The rest of the list is a grand tour through four decades of US rap music. It has old school block party sound, 90s boom-bap beats, and West Coast gangsta rap. Going through the list, the first thing you may notice is that the highest-ranking songs are from the period between the mid-eighties and the mid-nineties – what’s often called hip-hop’s ‘golden era’. Only two songs from the past decade made it into the top 25: Alright by Kendrick Lamar and Runaway by Kanye West. But there’s something else that stands out: The absence of women.

Where the ladies at?

The top 10 doesn’t include any female rappers at all. The highest-ranking song by a female artist is Queen Latifah’s 1993 feminist rap anthem U.N.I.T.Y., ranked 19th. In fact, the BBC’s 25 greatest hip-hop songs of all time include more songs that feature the band OutKast (three) than songs by women rappers (two).

To get a better understanding of the data, I plotted publishing years, ratings, and artist gender in a chart. Out of 311 entries, there are just 23 songs by women rappers and 19 songs that are by mixed bands or collaborations between female and male artists. For comparison: Even though JAY-Z did not make it into the top 25, he alone has 20 songs on the list. If you wonder why this is the case, you should read J’na Jamerson’s analysis of why there are so few women in hip-hop best-of lists. Spoiler: It’s probably a mix of the prevailing misogyny in hip-hop and the fact that the hip-hop business is largely run by men, who decide who receives attention and who doesn’t.

In spite of all this, hip-hop has so many amazing female voices. To celebrate women in hip-hop and to make it easier for you to find great music by female rappers, I’ve filtered the data set for an alternative best-of list containing only songs that feature women artists. Make sure to also listen to the Spotify playlist.

How I analyzed the data

The BBC published a list of all responses to their poll, which has a total of 311 songs. They also included a detailed description of their ranking algorithm, which I used to recreate the ranking through grouping and sorting the data in R. Here’s how the ranking works:

We awarded 10 points for first ranked track, eight points for second ranked track, and so on down to two points for fifth place. The song with the most points won. We split ties by the total number of votes: songs with more votes ranked higher. Any ties remaining after this were split by first place votes, followed by second place votes and so on: songs with more critics placing them at higher up the lists up ranked higher.

To add more context, I categorized artists by gender and added cover artwork that I got via the Spotify API. I then used Benedict Witzenberger’s R package to create Datawrapper charts directly from my R scripts. If you’d like to learn how I prepared the data in more detail, see my data analysis repo on GitHub.

To find out more about the data visualization tools and techniques I used in this article, have a look at the following articles:

• How to create scatter plots using Datawrapper
• How to create custom tables using Datawrapper
• How to use the DatawrappR R package

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That’s it from me for this week. As always, do let me know if you have feedback, suggestions or questions. I am looking forward to hearing from you at simon@datawrapper.de, Mastodon, or Twitter.