Positivity In Music

and how it effects danceability

Author

Ethan Leamer

Question

I will be performing an analysis on how the positivity of a song correlates to how easy it is to dance to it. Each row in the data is a song and it’s characteristics from Spotify.

Method

Firstly I plan to make a scatter plot using ggplot and geom_point. The # x-axis for this graph will be the valence as that is the explanatory # variable and the y-axis will be the “danceablilty” as it is the response # variable. This will show how the “danceablilty of a song changes as the # valence, or positiveness, increases.

songs %>% 
  ggplot(aes(x = valence, y = danceability)) +
  geom_point() +
  labs(x = "Positiveness",
       y = "Danceability",
       title = "Song Positivity vs. Danceablilty")

Interpretation

This graph shows a slight positive linear relationship between “Positiveness” # and “Danceability”. However, we can see that songs that are very positive # can all be danced to, but some songs that are not very positive have # a very low danceability score. One more key takeaway is that songs can be # very easy to dance to no matter how positive they are. This is seen as there # are “Danceability” scores close to 1 at all levels of positiveness.

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title: "Positivity In Music"    # Name of your HTML output
subtitle: "and how it effects danceability"
author: "Ethan Leamer"    # Author name
toc: true                 # Generates an automatic table of contents.
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### Question

I will be performing an analysis on how the positivity of a song correlates to how easy it is to dance to it. Each row in the data is a song and it's characteristics from Spotify.

```{r}
#| echo: FALSE            # Hide the code in this chunk in the output
library(tidyverse)
songs <- read_csv("https://myxavier-my.sharepoint.com/:x:/g/personal/leamere_xavier_edu/EQzAanNPpIpJnt-zrJshQKcBVQs02WeSpU0MzwRyo1haqg?download=1")

```

### Method

Firstly I plan to make a scatter plot using ggplot and geom_point. The \# x-axis for this graph will be the valence as that is the explanatory \# variable and the y-axis will be the "danceablilty" as it is the response \# variable. This will show how the "danceablilty of a song changes as the \# valence, or positiveness, increases.

```{r}
songs %>% 
  ggplot(aes(x = valence, y = danceability)) +
  geom_point() +
  labs(x = "Positiveness",
       y = "Danceability",
       title = "Song Positivity vs. Danceablilty")
```

### Interpretation

This graph shows a slight positive linear relationship between "Positiveness" \# and "Danceability". However, we can see that songs that are very positive \# can all be danced to, but some songs that are not very positive have \# a very low danceability score. One more key takeaway is that songs can be \# very easy to dance to no matter how positive they are. This is seen as there \# are "Danceability" scores close to 1 at all levels of positiveness.