#‘Global Human Day’ featurette

class: inverse, left, bottom
background-image: url(https://images.unsplash.com/photo-1601312378427-822b2b41da35?auto=format&fit=crop&q=80&w=1548&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D)
background-size: cover
# .Large[#'tswift keys' featurette]
## .small[featuring [{ggbarlabs}](https://github.com/everyday_analytics/ggbarlabs) which is experimental]
#### .tiny[Gina Reynolds | 2023-10-26 |Image credit: David Pisnoy, Upsplash]
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Title

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# What keys does Taylor Swift write in the most?

---

**key**: The estimated overall key of the track. Integers map to pitches using standard Pitch Class notation . E.g. 0 = C, 1 = C♯/D♭, 2 = D, and so on. If no key was detected, the value is -1.

---

```r
library(tidyverse)
taylor_album_songs <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2023/2023-10-17/taylor_album_songs.csv')
```

---
class: inverse, middle, center

# featured: ggbarlabs:::geom_barlab_count_percent

---

count: false

.panel1-feature-auto[

```r
*taylor_album_songs
```
]
 
.panel2-feature-auto[

```
## # A tibble: 194 × 29
##    album_name   ep    album_release track_number track_name     artist featuring
##    <chr>        <lgl> <date>               <dbl> <chr>          <chr>  <chr>    
##  1 Taylor Swift FALSE 2006-10-24               1 Tim McGraw     Taylo… <NA>     
##  2 Taylor Swift FALSE 2006-10-24               2 Picture To Bu… Taylo… <NA>     
##  3 Taylor Swift FALSE 2006-10-24               3 Teardrops On … Taylo… <NA>     
##  4 Taylor Swift FALSE 2006-10-24               4 A Place In Th… Taylo… <NA>     
##  5 Taylor Swift FALSE 2006-10-24               5 Cold As You    Taylo… <NA>     
##  6 Taylor Swift FALSE 2006-10-24               6 The Outside    Taylo… <NA>     
##  7 Taylor Swift FALSE 2006-10-24               7 Tied Together… Taylo… <NA>     
##  8 Taylor Swift FALSE 2006-10-24               8 Stay Beautiful Taylo… <NA>     
##  9 Taylor Swift FALSE 2006-10-24               9 Should've Sai… Taylo… <NA>     
## 10 Taylor Swift FALSE 2006-10-24              10 Mary's Song (… Taylo… <NA>     
## # ℹ 184 more rows
## # ℹ 22 more variables: bonus_track <lgl>, promotional_release <date>,
## #   single_release <date>, track_release <date>, danceability <dbl>,
## #   energy <dbl>, key <dbl>, loudness <dbl>, mode <dbl>, speechiness <dbl>,
## #   acousticness <dbl>, instrumentalness <dbl>, liveness <dbl>, valence <dbl>,
## #   tempo <dbl>, time_signature <dbl>, duration_ms <dbl>, explicit <lgl>,
## #   key_name <chr>, mode_name <chr>, key_mode <chr>, lyrics <lgl>
```
]

---
count: false

.panel1-feature-auto[

```r
taylor_album_songs %>%
* mutate(key_name = ifelse(mode, key_name, tolower(key_name)))
```
]
 
.panel2-feature-auto[

---
count: false

.panel1-feature-auto[

```r
taylor_album_songs %>%
  mutate(key_name = ifelse(mode, key_name, tolower(key_name))) %>%
* filter(!is.na(key_mode))
```
]
 
.panel2-feature-auto[

```
## # A tibble: 191 × 29
##    album_name   ep    album_release track_number track_name     artist featuring
##    <chr>        <lgl> <date>               <dbl> <chr>          <chr>  <chr>    
##  1 Taylor Swift FALSE 2006-10-24               1 Tim McGraw     Taylo… <NA>     
##  2 Taylor Swift FALSE 2006-10-24               2 Picture To Bu… Taylo… <NA>     
##  3 Taylor Swift FALSE 2006-10-24               3 Teardrops On … Taylo… <NA>     
##  4 Taylor Swift FALSE 2006-10-24               4 A Place In Th… Taylo… <NA>     
##  5 Taylor Swift FALSE 2006-10-24               5 Cold As You    Taylo… <NA>     
##  6 Taylor Swift FALSE 2006-10-24               6 The Outside    Taylo… <NA>     
##  7 Taylor Swift FALSE 2006-10-24               7 Tied Together… Taylo… <NA>     
##  8 Taylor Swift FALSE 2006-10-24               8 Stay Beautiful Taylo… <NA>     
##  9 Taylor Swift FALSE 2006-10-24               9 Should've Sai… Taylo… <NA>     
## 10 Taylor Swift FALSE 2006-10-24              10 Mary's Song (… Taylo… <NA>     
## # ℹ 181 more rows
## # ℹ 22 more variables: bonus_track <lgl>, promotional_release <date>,
## #   single_release <date>, track_release <date>, danceability <dbl>,
## #   energy <dbl>, key <dbl>, loudness <dbl>, mode <dbl>, speechiness <dbl>,
## #   acousticness <dbl>, instrumentalness <dbl>, liveness <dbl>, valence <dbl>,
## #   tempo <dbl>, time_signature <dbl>, duration_ms <dbl>, explicit <lgl>,
## #   key_name <chr>, mode_name <chr>, key_mode <chr>, lyrics <lgl>
```
]

---
count: false

.panel1-feature-auto[

```r
taylor_album_songs %>%
  mutate(key_name = ifelse(mode, key_name, tolower(key_name))) %>%
  filter(!is.na(key_mode)) %>%
* ggplot()
```
]
 
.panel2-feature-auto[
<img src="tswift-keys_files/figure-html/feature_auto_04_output-1.png" width="80%" />
]

---
count: false

.panel1-feature-auto[

```r
taylor_album_songs %>%
  mutate(key_name = ifelse(mode, key_name, tolower(key_name))) %>%
  filter(!is.na(key_mode)) %>%
  ggplot() +
* aes(x = fct_infreq(key_name))
```
]
 
.panel2-feature-auto[
<img src="tswift-keys_files/figure-html/feature_auto_05_output-1.png" width="80%" />
]

---
count: false

.panel1-feature-auto[

```r
taylor_album_songs %>%
  mutate(key_name = ifelse(mode, key_name, tolower(key_name))) %>%
  filter(!is.na(key_mode)) %>%
  ggplot() +
  aes(x = fct_infreq(key_name)) +
* geom_bar(alpha = .8)
```
]
 
.panel2-feature-auto[
<img src="tswift-keys_files/figure-html/feature_auto_06_output-1.png" width="80%" />
]

---
count: false

.panel1-feature-auto[

```r
taylor_album_songs %>%
  mutate(key_name = ifelse(mode, key_name, tolower(key_name))) %>%
  filter(!is.na(key_mode)) %>%
  ggplot() +
  aes(x = fct_infreq(key_name)) +
  geom_bar(alpha = .8) +
* aes(fill = ifelse(mode, "major", "minor"))
```
]
 
.panel2-feature-auto[
<img src="tswift-keys_files/figure-html/feature_auto_07_output-1.png" width="80%" />
]

---
count: false

.panel1-feature-auto[

---
count: false

.panel1-feature-auto[

---
count: false

.panel1-feature-auto[

```r
taylor_album_songs %>%
  mutate(key_name = ifelse(mode, key_name, tolower(key_name))) %>%
  filter(!is.na(key_mode)) %>%
  ggplot() +
  aes(x = fct_infreq(key_name)) +
  geom_bar(alpha = .8) +
  aes(fill = ifelse(mode, "major", "minor")) +
  scale_fill_manual(values = c("midnightblue", "magenta")) +
  ggbarlabs::geom_barlab_count_percent(size = 3) +
* labs(title = "What Keys are Taylor Swift's Songs in?",
*      caption = "In #tidytuesday's 2023-10-17/taylor_album_songs.csv",
*      subtitle = "Number of Songs in keys from album songs by key")
```
]
 
.panel2-feature-auto[
<img src="tswift-keys_files/figure-html/feature_auto_10_output-1.png" width="80%" />
]

---
count: false

.panel1-feature-auto[

```r
taylor_album_songs %>%
  mutate(key_name = ifelse(mode, key_name, tolower(key_name))) %>%
  filter(!is.na(key_mode)) %>%
  ggplot() +
  aes(x = fct_infreq(key_name)) +
  geom_bar(alpha = .8) +
  aes(fill = ifelse(mode, "major", "minor")) +
  scale_fill_manual(values = c("midnightblue", "magenta")) +
  ggbarlabs::geom_barlab_count_percent(size = 3) +
  labs(title = "What Keys are Taylor Swift's Songs in?",
       caption = "In #tidytuesday's 2023-10-17/taylor_album_songs.csv",
       subtitle = "Number of Songs in keys from album songs by key") +
* ggbarlabs::defaults_ggbarlabs()
```
]
 
.panel2-feature-auto[
<img src="tswift-keys_files/figure-html/feature_auto_11_output-1.png" width="80%" />
]

---
count: false

.panel1-feature-auto[

```r
taylor_album_songs %>%
  mutate(key_name = ifelse(mode, key_name, tolower(key_name))) %>%
  filter(!is.na(key_mode)) %>%
  ggplot() +
  aes(x = fct_infreq(key_name)) +
  geom_bar(alpha = .8) +
  aes(fill = ifelse(mode, "major", "minor")) +
  scale_fill_manual(values = c("midnightblue", "magenta")) +
  ggbarlabs::geom_barlab_count_percent(size = 3) +
  labs(title = "What Keys are Taylor Swift's Songs in?",
       caption = "In #tidytuesday's 2023-10-17/taylor_album_songs.csv",
       subtitle = "Number of Songs in keys from album songs by key") +
  ggbarlabs::defaults_ggbarlabs() +
* labs(x = NULL)
```
]
 
.panel2-feature-auto[
<img src="tswift-keys_files/figure-html/feature_auto_12_output-1.png" width="80%" />
]

---
count: false

.panel1-feature-auto[

```r
taylor_album_songs %>%
  mutate(key_name = ifelse(mode, key_name, tolower(key_name))) %>%
  filter(!is.na(key_mode)) %>%
  ggplot() +
  aes(x = fct_infreq(key_name)) +
  geom_bar(alpha = .8) +
  aes(fill = ifelse(mode, "major", "minor")) +
  scale_fill_manual(values = c("midnightblue", "magenta")) +
  ggbarlabs::geom_barlab_count_percent(size = 3) +
  labs(title = "What Keys are Taylor Swift's Songs in?",
       caption = "In #tidytuesday's 2023-10-17/taylor_album_songs.csv",
       subtitle = "Number of Songs in keys from album songs by key") +
  ggbarlabs::defaults_ggbarlabs() +
  labs(x = NULL) +
* labs(fill = NULL)
```
]
 
.panel2-feature-auto[
<img src="tswift-keys_files/figure-html/feature_auto_13_output-1.png" width="80%" />
]

---

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### Contribute

- https://github.com/everyday-analytics/ggbarlabs

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### Check out flipbookr, used to build this featurette

- https://github.com/EvaMaeRey/flipbookr
- discussion:  https://github.com/EvaMaeRey/flipbookr/blob/master/docs/draft_jasa_submission.pdf

---

### Check out more featurettes

- https://EvaMaeRey.github.io/featurette