Analyzing the Evolution of Linkin Park's Music with Pandas
kvsingh.github.io
kvsingh.github.io
One of the things I like about Linkin Park is that their style evolved so much over the years. Even when they got big they were not afraid to completely change up their style almost completely.
I think the author knows this and tries to point it out in the commentary but I don't know if the graphs tell a compelling story.
One thing I'd like to point out from a data perspective is that a bar graph might not be the best tool for this. An album consists of many songs and there are graphs that can convey more information while maintaining readability. Perhaps a scatter plot or candlestick graph? If you use point size for song duration you can even display duration and energy of all the songs on each album in a scatter plot and I think it would be readable still.
I got some audio features (loudness, energy and valence) for Linkin Park's songs using the Spotify API. In the post, I do an album-wise analysis of these features, and how they vary across and within the albums using the Python Data Analysis Library, Pandas.
I try to articulate the general progression in style through the average change in these features, as well as the change in variation of these features.
If you're a Linkin Park fan, I would love to know how your experience of listening to LP matches with my analysis :)
Using for example a box-plot (https://pandas.pydata.org/pandas-docs/stable/visualization.h...) could show the mean/std in a more comprehensible way by having it in a single plot.
Was hoping for "We put headphones on 7 pandas and analysed their reaction to Linkin Park's best known songs. 5 out of 7 pandas agreed that the 'Living Things' album wasn't very good."