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Dr Bénédicte Wenden Jan 23
I found time to do a bit of coding on the enjoyable Spotify dataset. I tried to find the words in the track and album names associated with high and low popularity. It would be nice to run this for each genre.
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Ian Bell Jan 21
Spotify Song Data Got to use pivot_longer for the first time! In the last 30 years, the average song length has decreased by over a minute!🤖 Code:
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Georgios Karamanis Jan 18
A more artistic take on the password data for this week's code:
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Cal Webb Jan 22
Finished my Spotify related project! "Perfect pairings" of popular tracks? More style over substance this time, but a dendrogram showing year of release adjusted popularity pairings by audio features. Details, high res pictures, code:
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Cal Webb Jan 21
Progress for this : A dendrogram from a hierarchical cluster model of the 200-ish most popular EDM tracks in the data. Songs are clustered on danceability, energy, loudness, mode, speechiness, acousticness, instrumentalness, liveness, valence, and tempo.
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Mike Mahoney Jan 21
For this , I decided to play around a little more with heddlr (, coming soon to a CRAN near you) to make a modular dashboard -- and made 84 graphs in the process😅 See the dashboard: Code:
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Kyla McConnell Jan 21
My wasn't super successful... but after a lot of reducing the data to try to get my laptop to cope I ended up with one converging neural network.... with 33-50% accuracy😂 But the support of the community makes it worth it!
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Jared Braggins Jan 21
For this week's I decided to try and create a chart with a retro graphic equalizer aesthetic. This was very much inspired by one of 's charts, which can be found here: Code:
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Cédric Scherer Jan 24
2020/04 🎶 Spotify Songs As I said before, too many options, so I came up with this monster about: THE G🟡LDEN AGE OF HIP HOP 🎤 💯%
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Philippe Massicotte Jan 19
My little contribution to week #⃣3⃣. Made with
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Uwe Hadler Jan 23
My first : how music changes over time. Notice how songs of the 90s are very danceable and the spike in loudness after 2000. Code is available here:
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Georgios Karamanis 21h
Made some audio waves for this . Not very satisfied with the result but that should do it 😐
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Amit Levinson Jan 20
Had some free time to enjoy a nice with data from 🎼🎧 Learned how to unnest_words and use the get_sentiments function; didn't know 'feat' was so popular 😂 code:
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Paul Nice Jan 23
Quick & simple effort at for the first time in a while with just a few lines of code. Looks like there's a lot more interesting things to find in the data. Wonder what's up with Rock music?!
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Marisa L. Henry Jan 22
this weeks comparing the distribution of song characteristics between K-pop songs and pop songs from Billboard's 2019 top 10 pop artists
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João Paulo Nogueira 19h
The top 5 track artist by playlist genre.
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Indrajeet Patil 22h
Holy cow this is a fantastic collection of beautiful visualizations (contributions to ) by ! 🤯📊📈😍 Thanks for making all the data and the code available! 🙌
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Mike Jeziorski Jan 22
A heads-up for anyone using this week's Spotify dataset to examine genres: ~4500 lines are duplicate listings of songs under different genres. I don't see an easy way to assign such songs to an appropriate genre/subgenre, and I also don't see how "Royals" is R&B.
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Ronald Delgado Jan 22
Wow! One of the best plots I've seen ever! Great work!
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Dr. Torsten Sprenger 3h
My 04|2020 contribution: Spotify Audio Features per Genre & Subgenre🎶inspired by petal charts from and Code:
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