Analyzing Spotify Stream History

Your_Spotify is absolutely fantastic for doing this<p><a href="https:&#x2F;&#x2F;github.com&#x2F;Yooooomi&#x2F;your_spotify">https:&#x2F;&#x2F;github.com&#x2F;Yooooomi&#x2F;your_spotify</a>

I have been using last.fm[1] for this for years (just checked, from 2008!). They now do a rolling weekly and annual interactive chart which is fun to look at, here&#x27;s mine for 2023[2].<p>They have a Spotify integration and I use PanoScrobbler on mobile.<p>[1]: <a href="https:&#x2F;&#x2F;www.last.fm&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.last.fm&#x2F;</a><p>[2]: <a href="https:&#x2F;&#x2F;www.last.fm&#x2F;user&#x2F;GripFx&#x2F;listening-report&#x2F;year" rel="nofollow">https:&#x2F;&#x2F;www.last.fm&#x2F;user&#x2F;GripFx&#x2F;listening-report&#x2F;year</a>

I wish YouTube Music did this :(<p>Ideas for other analysis;<p>Songs that over or under index when sliced by some other dimension. Weather? Morning vs evening? Weekday vs weekend? Summer vs winter?<p>Songs you never finish vs songs you always finish.<p>Songs you don&#x27;t like from albums you do.<p>One hit wonders (within your personal taste)<p>Songs you&#x27;ve played 10+ times but haven&#x27;t heard in over three years<p>If you had this data at scale: favourite songs from people who enjoy similar niches to you (it&#x27;s me! Listen to Televators by TMV).

I collected 10 years worth of my complete listening habits via a lastfm plugin, in the past for Winamp, then for iPhone&#x2F;Android Media players and finally within Spotify. Now lastfm has shut down their free API access and visualization tools stopped working. I printed a 2x1m large poster of my over 10 years of data as a beautiful LastGraph visualization.

This made me remember how much I used to love exploring my last.fm data with stream graphs from <a href="https:&#x2F;&#x2F;lastgraph.aeracode.org&#x2F;" rel="nofollow">https:&#x2F;&#x2F;lastgraph.aeracode.org&#x2F;</a> (before it died)<p>I&#x27;ll have to have a go at making something similar with my Spotify data. Thanks for the inspiration.

Can this data tell you if the song was played from the local cache or actually streamed? Would like to know if the smart shuffle has a preference for locally cached songs so Spotify can save on data charges.

This is cool. I also requested my data as I wanted to find out the artists I&#x27;d missed out listening to. The ones I had heard previously but didn&#x27;t get hooked initially... As in I should have been listening to Phoebe Bridgers all this time <a href="https:&#x2F;&#x2F;www.darrenshaw.org&#x2F;blog&#x2F;2023&#x2F;01&#x2F;05&#x2F;should-have-been-listening-to-phoebe-bridgers.html" rel="nofollow">https:&#x2F;&#x2F;www.darrenshaw.org&#x2F;blog&#x2F;2023&#x2F;01&#x2F;05&#x2F;should-have-been-...</a>

For me, this is easily one of best pros of using Spotify. The post did not mention but it may take up to a month to get data files from spotify (took 28 days for me) but it is worth it. One example use case for data science is the Stats.fm project that neatly aggregates you listening history with graphs and such.

I wrote a website to do exactly this with your own data and Python in the browser using pyodide und plotly.js for visualizations: <a href="https:&#x2F;&#x2F;github.com&#x2F;piebro&#x2F;spotify-statistics&#x2F;">https:&#x2F;&#x2F;github.com&#x2F;piebro&#x2F;spotify-statistics&#x2F;</a>

I&#x27;ll do a proper Show HN very soon, but for anyone who&#x27;s interested in viewing their detailed Spotify stats, you can use <a href="https:&#x2F;&#x2F;volt.fm" rel="nofollow">https:&#x2F;&#x2F;volt.fm</a>