last.fm is one of my very favorite services. It's rough around the edges in some parts, but I've gotten incredible value from it. A couple of websites built on it that I check out from time to time:
- https://lastfmviz.netlify.app/ - shows what you've been listening to as a grid of album covers. You can scroll down as long as you want. It's cool to look back and remember where I was when listening to specific music.
- https://lastfmstats.com/ - generates tons of rankings, line charts, racing bar charts, etc. A couple I like: "Artist streaks" (I listened to Pavement tracks 122 times in a row in August 2023), "Unique artists in a single month" (225 in July 2025) and "Unique weeks per artist/album/track" (good to identify what you're always listening to vs. what you listened to heavily in a specific time)
- https://pmcdonough8133.github.io/last.timer/ - shows your listening rankings by hours, minutes instead of just scrobble count. This really should be a default feature in the site, as some artists have average track length 2-3x times of others.
The middle one is fascinating. The first track I ever scrobbled is by an artist I have yet to listen to again in 22 years. Much of the longest gaps is taken up by bands I found or started to like due to Rock Band which came out around that time. Man I miss that too, we had 30 or 40 people over right after it came out and turned the house into a karaoke dive, right down to having to kick them off the couch the next morning.
If you're a Spotify user, you can get even more precise data by downloading your listening data. The website I linked gets data from MusicBrainz and tries to fill in the gaps with an average, but even then it gets some things wrong.
E.g. Fishmans - Long Season is a 40 minute song, but the website's considers it as divided into 4-5 parts. And you don't have to listen to the full song to get a scrobble.
In the Spotify data you get the exact number of seconds you listened to it. And it is surprisingly complete and easy to use too. With LLMs I bet you can load it into pandas and construct queries for any insight you want in seconds.
Just this weekend I generated a really detailed breakdown from my Spotify dump, it's unfortunate they hide so much of the interesting stuff in a dump that takes a week+ to get access to: https://6fce3ff2.spotifyguy94-dashboard.pages.dev
The advertising profile was especially interesting since a) I don't think the brands expected anyone outside of their marketing teams to see some of these names b) I've had premium for most of the time I've used Spotify, but they're still putting in full effort on generating an ad profile in case that ever changes
- https://lastfmviz.netlify.app/ - shows what you've been listening to as a grid of album covers. You can scroll down as long as you want. It's cool to look back and remember where I was when listening to specific music.
- https://lastfmstats.com/ - generates tons of rankings, line charts, racing bar charts, etc. A couple I like: "Artist streaks" (I listened to Pavement tracks 122 times in a row in August 2023), "Unique artists in a single month" (225 in July 2025) and "Unique weeks per artist/album/track" (good to identify what you're always listening to vs. what you listened to heavily in a specific time)
- https://pmcdonough8133.github.io/last.timer/ - shows your listening rankings by hours, minutes instead of just scrobble count. This really should be a default feature in the site, as some artists have average track length 2-3x times of others.
If you use Spotify, another site I've had loads of fun with is https://explorify.link/.