Part 2
This dataset is a dataset containing the top songs BY YEAR in the world by Spotify. This dataset has several variables about the songs and is based on Billboard. The second dataset is a dataset of the top movies from 2006-2016. It includes the name, actors, year, runtime, rating, # of votes, revenue, and metascore.
1.) What is the average duration (in seconds) of songs per year?
This bar chart shows “year” on the y-axis and “Average Duration
(seconds)” on the x-axis. We can observe that on average, songs in 2011
were longer than any other year, and songs in 2018-2019 were shorter on
average.
2.) How many songs are in each genre?
From the bar graph that displays the distribution of genres, we can confirm that dance pop clearly is the genre with the most top songs. The second and third highest are also pop genres, “pop” and “candy pop”.
3.) Does it appear that songs with more energy are easier to dance to in certain years? (3+)
There is not a clear relationship between the Energy of a Song and its
dance ability,yet we see a cluster or clump of data points in the upper
right hand of the graph. There appears to be a weak positive
correlation. This suggests that the higher score of dance ability, the
more energy that the song possesses. We are also seeing more light blue
data points than dark, so can conclude that songs in the later end of
the decade have a higher energy and dance rate.
4.) Were the most popular songs in each year likely a live recording of the song or very auto tuned? (3+)
From this visualization, we can determine that a large majority of the most popular songs in each decade were not recorded live. As the years go on, the most popular songs tends to have less of a higher “live” score. This is most likely due to advances in technology and different sounds that can be produced in studio.
5.) Is there a relationship between how loud a song is and the energy that the song gives off based on the projected volume? (3+)
There is a strong positive correlation between energy and loudness.
Though it does not seem as though year is greatly influenced by these
variables, we can determine that the greater value of Loudness, the
higher the Energy gets. The energy level rises in very small increments
with Loudness, but this is still relevant to note. We can see that when
songs are not loud, the song is much less energetic and less willing to
have people’s moods be boosted or create fun. In this case, Loudness of
a song is important to generate an energetic feel among listeners.