
Analyzing Last.fm Listening History - cobralibre
http://geoffboeing.com/2016/05/analyzing-lastfm-history/
======
jc4p
This is really cool! I love playing with my own Last.fm data. Some
suggestions:

\- Manually (or using your Facebook timeline?) place out big events in your
life and see if you can see what kind of music you listened to before/after
them that you don't normally. I listen to depressing shit post break-ups.

\- Use your Twitter or any other feed to estimate your "mood" over time and
see if you can find any music you listened to while you're angry

\- Use The Echo Nest to get metrics for how happy/sad/energetic the music you
listen to is.

\- Come up with your own definition of albums played! I hate Last.fm's
because, as you mentioned, it heavily biases albums with multiple tracks. In
my personal analysis I always start off with a RLE for tracks played on the
same album, and my metric for "albums I listen to the most" is "which albums
do I listen to at least 3 continuous songs from the most".

I spent a few months this year trying to combine my Last.fm listening history
with my geolocation history (I've mostly just stayed in the same place for the
last 8 years, 3-4 years) and Forecast.io's historical API to be able to answer
the question "am I really only happy when it rains?" \-- Data warehousing is a
hard problem, though.

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maaaats
263,428 plays over 53,632 songs = 5 plays of each song on average. (updated
after comment below)

I haven't "scrobbled" in many years, but checked now that I in 2007 (when I
was 16) had 12,377 plays with only 153 unique songs. An average of playing
each song 78 times. However, most of the songs I only listened to a few times,
so there is basically just ~20+ songs I listened to 250-500 times each that
year.

So I guess I was a typical teenager that got obsessed with some songs/artists
and listened to them non stop, heh.

~~~
pbuzbee
This post says there are 53,632 unique songs. 15,503 refers to the number of
unique artists.

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morsch
Shameless plug of a weekend project from a while back (I'm pleasently
surprised it still works): [http://deja-entendu.zomg.zone](http://deja-
entendu.zomg.zone)

Auto-creates a Spotify playlist from your scrobbles from 6 months, or a year
ago or whenever. For instance, if you want to walk a mile in the article
author's shoes (ears?): [http://deja-entendu.zomg.zone/gboeing](http://deja-
entendu.zomg.zone/gboeing)

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rahoulb
It's kind of stupid, but when I tried out Apple Music, the lack of Last.fm
integration really bugged me and I soon switched back to Spotify. Now I
understand why :-D

~~~
Jgrubb
I just installed the scrobbler and it's working fine with Apple Music. FWIW.

~~~
jc4p
From my experience the scrobbler only work with music I own in Apple Music,
not any music I'm listening to from Beats Radio or any of the recommended
playlists.

~~~
dewey
On the Mac [http://micropixels.pl/neptunes/](http://micropixels.pl/neptunes/)
works just fine also for streamed music from apple music not just the tracks
you download into your local library. Not aware of anything that does it on
iOS though unfortunately :(

~~~
traek
On macOS, [http://bowtieapp.com](http://bowtieapp.com) is a good free
alternative.

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gboeing
Original author here. Thanks everyone for the comments! If you've got any
other feedback or suggestions I am more than happy to hear it!

~~~
djsumdog
This is pretty cool. I still use Last.FM (and also LibreFM) and scrobble from
home, work and my phone.

I'll have to give these python notebooks a try :)

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pgm8705
Very cool. I've always wanted to do something like this as well. I'd be
interested in analyzing my listening habits throughout the year to see if
there is any correlation between months and artists. I feel like I'm pretty
"seasonal" with what I listen to.

~~~
jc4p
I tried doing this with my own Last.fm data, if this slow badly coded Heroku
app is still live you can see mine: [http://lastfm-
seasonally.herokuapp.com/user/pvam](http://lastfm-
seasonally.herokuapp.com/user/pvam)

Basically, I listen to what I like to listen to no matter the season. If you
have last.fm change the last slash in that URL with your username and after a
couple minutes (it's single-threaded pulling API requests) it'll show your
analysis.

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sotojuan
Pretty cool, still sad at the really bad Last.fm redesign but glad useful
things come out of the data.

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askmike
It's pretty awesome what you can do with that dataset. I made a visualization
a few years back for a class that looks at the genres I listened to over time:

[http://lab.askmike.org/d3/songstream/](http://lab.askmike.org/d3/songstream/)

~~~
jojohack
That's pretty awesome, very easy to read. I've been meaning to get into d3
soon, what is this particular style of graph called?

~~~
jrowley
It's a Stack Layout turned 90 degrees.

[https://github.com/d3/d3/wiki/Stack-
Layout](https://github.com/d3/d3/wiki/Stack-Layout)

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pbuzbee
I made something similar with my own data recently. With ~330k plays and 11
years of data, I really enjoyed seeing the long-term changes and trends in my
music habits.

I could see where my tastes would change based on where I was in my life (high
school, college, entering a relationship, etc). These transitions marked huge
changes in my tastes.

It was also cool to see other trends. For example, I found that I have a
"concert bounce" where I listen to an artist much more after seeing them live.

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whatever_dude
This just me realize I haven't been using last.fm for a couple of years, after
obsessing on having it in everything I used to listen to music. I guess my
move to Pandora didn't help.

But what do I know, there's a browser extension that does that!
[http://build.last.fm/item/1000591](http://build.last.fm/item/1000591)

Back to last.fm I go.

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iopq
If you look at my listening history, Untitled is by far my favorite track.
That's because every interlude on one album is untitled so I end up listening
to it like 5 times every time I listen to the album. Never mind the track
number, though, it doesn't look at it.

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h2hn
Cool I have a great collection in lastfm also. So I should check it out...

