<- spotify_data %>%
spotify_data mutate(streams = as.numeric(streams))
%>%
spotify_data mutate(streams = as.numeric(streams)) %>%
ggplot(aes(y = `energy_%`, x = streams)) +
geom_point(color = "blue", alpha = 0.6) +
scale_x_log10(labels = scales::comma) +
labs(title = "Energy Percentage vs. Number of Streams",
y = "Energy Percentage",
x = "Number of Streams")
Energy In Music
and how it Effects Streams
Intoroduction
I’m going to perform an analyis on spotify data and determine if Songs with a higher energy percentage will have a higher number of streams.
Method
I’m going to perform an analyis on spotify data and determine if Songs with a higher energy percentage will have a higher number of streams
Interpretation
Based on the available data, there is no clear evidence of a correlation between the number of streams and the energy percentage of a song. This suggests that a song’s energy level does not significantly impact its streaming performance, or if there is an effect, it may be influenced by other factors