Well, this time, I’ll go for the tidyverse.
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.4 ✔ readr 2.1.4
✔ forcats 1.0.0 ✔ stringr 1.5.1
✔ ggplot2 3.4.4 ✔ tibble 3.2.1
✔ lubridate 1.9.3 ✔ tidyr 1.3.0
✔ purrr 1.0.2
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
[1] "album_name" "ep" "album_release"
[4] "track_number" "track_name" "artist"
[7] "featuring" "bonus_track" "promotional_release"
[10] "single_release" "track_release" "danceability"
[13] "energy" "key" "loudness"
[16] "mode" "speechiness" "acousticness"
[19] "instrumentalness" "liveness" "valence"
[22] "tempo" "time_signature" "duration_ms"
[25] "explicit" "key_name" "mode_name"
[28] "key_mode" "lyrics"
Make a lollyplot with song durations
durations <- taylor_album_songs %>%
group_by(album_name) %>%
summarise(duration_ms = sum(duration_ms)) %>%
select(album_name, duration_ms) %>%
mutate(duration_min = duration_ms / 60000) %>%
arrange(desc(duration_min))
durations %>% ggplot(aes(x = reorder(album_name, duration_min), y = duration_min)) +
geom_segment(aes(xend = album_name, yend = 0), color = "grey50") +
geom_point(size = 4, color = "red") +
labs(title = "Taylor Swift: song durations",
subtitle = "Sorted by duration",
x = "Song",
y = "Duration (min)",
caption = "Data: Spotify API") +
theme_minimal() +
coord_flip() +
theme(plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
plot.caption = element_text(hjust = 0.5))
Warning: Removed 2 rows containing missing values (`geom_segment()`).
Warning: Removed 2 rows containing missing values (`geom_point()`).
