data visualisation spotify tracks
This is the data visualization of Spotify track data focused on musical attributes.
Questions:
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What are the co-relations of each musical attribute?
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Which musical attributes make tracks popular?
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What are the distributions of each musical attribute?
1. What are the co-relations of each musical attribute?
According to this heat map, the highest correlation you can see is between loudness and energy (0.82). Also, popularity has high correlations with loudness (0.36), danceability (0.26), and energy (0.25). That is similar to valence, which has high correlations with danceability (0.55), energy (0.44), and loudness (0.4). To the contrary, it has the least correlation with acousticness.
This suggests that songs favored on Spotify are danceable, loud, and energetic, for example, Hip-Hop, Electronic, or Dance.
2. Which musical attributes make tracks popular?
This plot above shows correlations between popularity and musical attributes.
Positive correlations can be found in loudness, danceability, and energy.
3. What are the distributions of each musical attribute?
This plot above shows distributions of each musical attribute.
Categories of popularity and danceability are closer to the normal distribution than others. Acousticness is clearly bimodal, liveness is right-skewed, and loudness is left-skewed.
Souces:
