We could see using album and artist alone, could predict track popularity to some extent. We could easily find recent tracks, album and artists are favored by today's listeners. Spotify Music Data Analysis MSBX-5415 Final Project Write-up Jason Engel Sydney Bookstaver Soumya Panda Upasana Rangaraju Introduction Spotify is one of the leading music streaming apps with more than 96 million paid subscribers. If nothing happens, download GitHub Desktop and try again. Here's the insight we've learned about music trend based on big data analysis: 1.Recent music is still largely favored, indicating customers' music "psychology" leaning towards trying novel tracks. Very useful for house parties, you can have all the music info on the TV. We care about the distributions as it provides us insights on the frequencies of the various styles of music, as well as the shape of the frequencies as if they were on Spotify. Also, track number has been lower, indicating smaller album in music industry nowadays. GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together. So, you open up Spotify, ... We learned through data analysis that although we have tens of thousands of datasets on BigQuery, the majority of consumption occurred on a relatively small share of top datasets. We use essential cookies to perform essential website functions, e.g. Clearly we could see house is brandnew genre, not exploading until 2010; followed by indie, which started to expand around 2005. they're used to log you in. Ensemble methods are extremely good for analyzing multi-feature data with non-linear relationship, plus XGBoost has recently dominated data science field with extreme superiority, so we choose XGBClassifier to train our data, and achieved very excellent accuracy score for both cross-validated and test data. Analyze a playlist You can use our free playlist analyzer to quickly find some helpful statistics and information about any Spotify playlist. Found an issue? The best predictive feature is album popularity. Let’s see what kind of information we can extract and use with SpotifyR: Your favorite songs/artists. ⋅⋅⋅Music has generally been louder than before? It'll be interesting to see if such small trend will continue. Music Analytics Driven By Data Science. In this project, we conducted data mining for 200000 tracks extracted by Spotify API, in order to analyze the trend of music industry development, and produce a predictive model for track popularity. For rock, the whole market has dramatically shrinked; while latin and metal shrinked much slowly. 3.Pop music undoubtedly dominates the music market, in both production quantity and popularity quantity; while some other genres like soul and classical have almost zero percentage of being top 20% popular, most probably because they are minority music favored by a small population. Which numeric features are associated with track popularity? 8 Data Exploration; 9 Spotify Audio Analysis. This free app specifically developed to analyse spotify playlist (yours or not) and presents the data with a beautiful design of the musical structure to give you a detailed insight on any Spotify playlist. So they appeared recently, or suddently became popular? When were these popular tracks of different genres released? uwgabrielxu.github.io/spotify-music-data-analysis/, download the GitHub extension for Visual Studio. Also a slight association for track number, artist popularity and loudness. First, we define "popular songs" as those with track popularity score ranking at top 20% of all tracks. Spotify is the world’s biggest music streaming platform by number of subscribers. For example. Association between track popularity and each numeric feature by scatterplot. genres, album name, artist name). These genres are produced in large quantity with certain proportion at top 20%. Spotify sites. We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. Various machine learning algorithms have been tried and gradient boosting classifier by XGBoost show the best accuracy score. Learn more about the audio properties of your favourite tracks, including detailed rhythmic information. Spotilyze uses the Spotify API to gather information about your playlists and displays the result in a beautiful manner. While playing around with the Spotify web API, and building a login flow in the app, it was pretty easy to get an access token for my account with all kinds of permissions for access to my data. Scatterplot for relationship among album, artist and track popularity, in which color indicating track popularity. The music industry is one of them. We could see strong association for year and album popularity, which is not surprising. For indie, house and mexican, almost all come from recent five years. As we know Spotify is one of the most popular audio streaming platforms around the globe. So such music have been on decline? Scope. The remaining physical features are not associated at all. Connect with Spotify and analyse your listening. We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. 8.Unfortunately, Spotify API does NOT provide location information for users; otherwise it'll be good idea to analyze music taste difference for different states as well as across the globe. The upper panel is for only popular tracks; while lower for total tracks. What genres of tracks are prefered by listeners today? ⋅⋅⋅What novel types of music have evolved popular in the past five years? We could see album popularity dominates all other features, followed by track number, year and duration. View real-time stats and see how new releases are performing as soon as a track goes online. 2.Some physical features of music with high popularity have slightly changed, including energy/loudness slightly increased, and valence slightly decreased. Spotify Statistics: Stats of your playlists and most favourite artists, songs and genres, all in nice designe complete with charts. Track number has been lower in recent 10 years, indicating album is smaller nowadays. If nothing happens, download Xcode and try again. This project aims to manipulate the Spotify music data with Python, having a twofold scope: Time-series boxplot for 16 different numeric features. Learn more, We use analytics cookies to understand how you use our websites so we can make them better, e.g. Learn how to get your personal listening data from Last.fm or Spotify, then kickstart your analysis with some guiding questions. Free Spotify access comes with lower sound quality, and advertisements, and requires an internet connection. Music Streaming’s Real Value for Most Artists Is Data, Not Money Apple Music for Artists comes out of beta, as rival companies like Spotify and Pandora beef up data analytics for artists as well An interactive visualisation of the musical structure of a song on Spotify. One of the most prominent ways Spotify uses the data generated by their customers is to help generate content that each user will consider in-line with their specific tastes. All information is precise to the audio sample. It operates on a freemium model. Function get_my_top_artists_or_tracks is one the best of the package. General numeric features (e.g. We could see some strong pair correlations, such as loudness and energy, loudness and acousticness, speechiness and explicit. In this article, we will learn how to scrape data from Spotify which is a popular music streaming and podcast platform. In general, we've analyzed Spotify API data, and have discovered some very interesting trends for today's music market, and also provide a high-quality model for track popularity prediction. 4.Important change: indie and house are brandnew genres and novel trend! Let’s say you’re having a rough day and you want to listen to some music to lift your spirit. This scraping will be done by using a Web API of Spotify, known as Spotipy. It’s a strategy that doesn’t just please users, it saves the distributors lots of money that once would have been spent on marketing. Music Trends Team Features Pricing Careers Blog Log In Sign Up. And understanding what makes streaming music popular could hugely impact decision-making for music business. Among others, it’s good for everything needed to analyze the heck out of your whole music library - information about songs and albums in particular. loudness, duration), ⋅⋅⋅3. Analyze the trend of music development over past 20 years. It also lets you create new custom made playlists based on your favourite tracks. 5.There's basically NO correlation between track popularity and numeric physical features; yet, there's strong correlation among track, album and artist popularity, which is not suprising; and there's also slight correlation between track popularity and track number, which is also not surprising, as most popular songs are usually the first in the album. by Ingrid Fadelli , Tech Xplore Model Results on the validation and test sets. Hey Guys, Yesterday a friend told me, that he got a pretty long email with his personal stats for 2016, including most heard songs (with numbers) and genres. Millions of developers and companies build, ship, and maintain their software on GitHub — the largest and most advanced development platform in the world. release time, track popularity, artist popularity), ⋅⋅⋅2. The Audio Analysis endpoint provides low-level audio analysis for all of the tracks in the Spotify catalog. Spotilyze does not store information about you nor your playlists. Extend your knowledge about the music you listen to. To simplify things as much as possible, I’ve prepared an overview of how much data … ⋅⋅⋅1. (Purple lines reflect mean). It reflects "hotness" by today's music listeners, calculated by total number of plays. While rock, which used to be prosperous, has now shrinked dramatically. 9.1 Creating Large Dataset; 10 Conclusion; Introduction. Then merge into Pandas Dataframe and start feature engineering. Establish models to predict track popularity by machine learning algorithms. Let us know. Comparison between album and artist popularity, we could see track popularity affected stronger by album, indicating popular artist's work could be popular or unpopular. It’s quite likely that get_spotify_uris function returns less information than input data.