I've been tracking the music I listen to on Spotify since
early November. There is an IFTTT recipe that
automatically updates a Google Spreadsheet every time I listen to a song with
the song name, artist name, album title, and timestamp.
While other people might be interested in the type of music
and how much of it I listen to, I am likely the main audience for this
visualization. No matter if the audience is just me, or family members,
friends, classmates, or others, some might generate assumptions about what
types of music I listen to on a regular bases. People who know I have a
daughter would understand the kids songs in the treemap, those who don't know
about my daughter might find the kids songs strange. The audience also probably
has some assumptions about how they listen to music throughout the day, and may
compare my listening habits to theirs. Someone who needs silence while working
will not understand how I listen to so much music. People may also judge the
types of music I listen to, and think better or worse of me.
My questions are: Which artists do I listen to the most, and
do I like a lot of those artists' songs or are they one-hit wonders to me? What
day of the week do I listen to the most music? What time of day do I listen to
the most music?
There are several other questions I have, but don't have the
proper data currently. Those questions are: Do I listen to certain genres of
music on specific days? I'm guessing that music on Mondays is different than
music on Fridays. How do the number of meetings I have during the day affect
how many songs, and what types of songs, I listen to? Again, guessing that more
meetings might mean fewer songs, but that the genres would change (since many
meetings tend to put me in a bad mood, especially when they are poorly run). To
make these analyses work, I would need to manually input genres for each song,
and would need to go through my calendar and manually update the number of
meetings I have each day.
I'm using R for the data preparation and analysis, and
Illustrator to fine tune the images.
For the treemap I used the R package 'portfolio'. Flowingdata.com
helped with the steps I needed to take to make this work. For the bar graph, I
used barplot. For the line graph, I used ggplot.
I'm also including my initial sketches of how I wanted the
visualization to look. This helped a lot for planning my attack, especially
with regard to the data cleanup.
Visualizations are below, all code is on GitHub.
Sketch of what I wanted:
Treemap of artists I listen to most:
Treemap of artists I listen to most:
Songs listened to per hour:
Songs listened to by day:
