2020-02-10_wearerladies_beeswarm

library(tidyverse)
library(ggbeeswarm)
library(viridis)

spotify_songs <- 
  readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-01-21/spotify_songs.csv') 

spotify_songs %>% 
  filter(playlist_genre == "pop" & track_popularity > 50) %>% 
  ggplot(aes(x = playlist_subgenre, y = danceability, group = playlist_subgenre, color = playlist_subgenre)) +
  geom_quasirandom(alpha = 0.4) +
  ggtitle("Is Dance Pop More Danceable?", 
          subtitle = "Track Popularity of 50+") +
  scale_color_viridis(discrete = T) +
  theme_minimal() +
  theme(axis.title.x = element_blank(),
        legend.position = "none")

spotify_songs %>% 
  filter(playlist_genre == "pop" & track_popularity > 50) %>% 
  ggplot(aes(x = playlist_subgenre, y = danceability, group = playlist_subgenre, fill = playlist_subgenre)) +
  geom_boxplot() +
  ggtitle("Is Dance Pop More Danceable?", 
          subtitle = "Track Popularity of 50+") +
  scale_fill_viridis(discrete = T) +
  theme_minimal() +
  theme(axis.title.x = element_blank(),
        legend.position = "none")

spotify_songs %>% 
  filter(playlist_genre == "pop" & track_popularity > 50) %>% 
  ggplot(aes(x = playlist_subgenre, y = danceability, group = playlist_subgenre, fill = playlist_subgenre)) +
  geom_boxplot() +
  ggtitle("Is Dance Pop More Danceable?", 
          subtitle = "Track Popularity of 50+") +
  scale_fill_viridis(discrete = T) +
  theme_minimal() +
  theme(axis.title.x = element_blank(),
        legend.position = "none")

spotify_songs %>% 
  filter(playlist_genre == "pop" & track_popularity > 50) %>% 
  ggplot(aes(x = playlist_subgenre, y = danceability, group = playlist_subgenre, fill = playlist_subgenre)) +
  geom_violin() +
  geom_boxplot(width = 0.1, fill = "white") +
  ggtitle("Is Dance Pop More Danceable?", 
          subtitle = "Track Popularity of 50+") +
  scale_fill_viridis(discrete = T) +
  theme_minimal() +
  theme(axis.title.x = element_blank(),
        legend.position = "none")