The data set contains the top 2000 songs from Spotify’s top hits in 2000 - 2019. The data include 18 columns that provide a discription of the song as well as various audio statistics that describe each songs qualities. This includes variables such as danceability, energy, speechiness, and tempo.
The data set can be downloaded here: https://myxavier-my.sharepoint.com/:x:/g/personal/riekenaj_xavier_edu/ETZXqnZtKHJInve0r1nVl4kBOOruz1spOIBeWaLadx4bnw?download=1
The visualizations answer the following questions:
This question is meant to help further understand that different audio statistics in the data. It will help determine if there is any correlation between them.
It can be determined that the higher energy rating a song has, the more danceable it is. In general, most songs featured in the top 2000 have a high danceability rating. Using the key, it can also be determined that the key of the song doesn’t have a lot of impact on the songs energy or danceability.
Music trends change from year to year. This visualization is meant to see if those changes have any impact on the popularity of the songs.
This visualization shows us that the year with the most amount of songs featured in the top 2000 is 2012. There is some variation with 2000, 2009, 2013, & 2019 all having less than 90 featured. Besides these, most feature more than 90 songs with minimal variation. Based off the bar graph, it can be determined that music trends year to year has a minimal effect on the number of songs in the top 2000.
A confidence measure from 0.0 to 1.0 of whether the track is acoustic. 1.0 represents high confidence the track is acoustic. This question is also meant to analyze music trends from year to year.
## $title
## [1] "Relationship Between Acousticness & Popularity by Year"
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## attr(,"class")
## [1] "labels"
When looking at all of the graphs as a whole, songs with a lower acousticness tend to have a higher popularity rating. The change in music prefrences can be seen in years 2007, and 2014-2017, where more songs with high acousticness ratings also had high popularity ratings. 2017 had the most amount of songs with low acousticness ratings and low popularity ratings.
The box plot shows that the distribution of a songs popularity between explicit and non-explicit songs is the same. Non-explicit songs have more outliers that do not have a high popularity rating compared explicit songs.
The “speechiness” rating describes if a song is mainly words, mainly music, or words and music mixed together.
The graph shows that there is minimal correlation between a songs length and its speechiness rating. This can be explained by the fact that most songs in the top 2000 are around the same length (2.5.- 5 minutes). Since this is the case, most songs with high speechiness ratings (no music) are outliers in the plot.