start getting started vignette

pkgdown/extra.css

@@ -55,6 +55,11 @@ a.anchor {
   color: var(--nav-bkg) !important;
 }
 
+/* button padding */
+li.nav-item {
+  padding-right: .5em;
+}
+
 /* package name in navbar */
 .navbar-brand {
   color: var(--nav-link) !important;
@@ -224,3 +229,9 @@ h4 {
   background-color: var(--toc-hover);
   color: var(--toc-htext) !important;
 }
+
+/* Vignette tables ---------------------------------------------------------- */
+table.taylor-examples td {
+  width: 33.333%;
+  vertical-align: middle;
+}

vignettes/children/chunk-options.txt

@@ -12,6 +12,7 @@ knitr::opts_chunk$set(
   comment = "#>",
   fig.asp = 0.618,
   fig.width = small_width,
+  fig.align = "center",
   out.width = "90%"
 )
 

vignettes/data/example-uses.csv

@@ -0,0 +1,10 @@
+preview,href,description
+https://juliasilge.com/blog/taylor-swift/index_files/figure-html/unnamed-chunk-10-1.png,https://juliasilge.com/blog/taylor-swift/,Julia Silge topic modeling
+https://cdn.fosstodon.org/media_attachments/files/111/275/600/691/928/622/original/d3cadbb47844dc21.png,https://fosstodon.org/@ryanahart/111275600981010402,Crafting bracelets
+https://cdn.masto.host/vissocial/media_attachments/files/111/268/872/636/513/756/original/438db8d1a9fc47ef.png,https://vis.social/@georgios/111268873077992577,Danceability beeswarm
+https://cdn.fosstodon.org/media_attachments/files/111/263/533/563/532/762/original/2286c64153a24511.png,https://fosstodon.org/@nrennie/111263534136045526,Average energy
+https://cdn.fosstodon.org/media_attachments/files/111/256/276/115/381/437/original/452faf0a9aca766e.png,https://fosstodon.org/@ryanahart/111256276399597870,Swiftly shifting tempos
+https://cdn.fosstodon.org/media_attachments/files/111/250/751/304/784/167/original/89c6862657cac335.png,https://fosstodon.org/@deepali/111250751714226638,Song duration radial
+https://fediscience.org/system/media_attachments/files/111/249/262/791/175/938/original/ecaebe4b66d85c8b.jpg,https://fediscience.org/@c_borstell/111246953936265713,Albums as sheet music
+https://cdn.fosstodon.org/media_attachments/files/111/270/764/662/176/750/original/4986ef0af073cd51.png,https://fosstodon.org/@danoehm/111270774940496937,Eras tour breakdown
+https://cdn.fosstodon.org/media_attachments/files/111/250/191/920/048/768/original/f5dcdfc73d0c6af7.png,https://fosstodon.org/@frankhaenel/111250193319291887,Spotify metrics radial

vignettes/taylor.Rmd

@@ -0,0 +1,136 @@
+---
+title: "Welcome to taylor"
+description: |
+  Learn about the package and what it can do!
+vignette: >
+  %\VignetteIndexEntry{Introduction to taylor}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+---
+
+```{r, child="children/chunk-options.txt"}
+```
+
+taylor is an R package for accessing data
+
+```{r setup}
+library(taylor)
+```
+
+<details><summary>Plot code</summary>
+
+```{r eras-plot, eval = FALSE}
+library(dplyr)
+library(tidyr)
+library(ggplot2)
+
+surprise_song_count <- eras_tour_surprise %>% 
+  nest(dat = -c(leg, date, city, night)) %>% 
+  arrange(date) %>% 
+  mutate(leg = factor(leg, levels = unique(eras_tour_surprise$leg),
+                      labels = c("North America\n(Leg 1)",
+                                 "South\nAmerica",
+                                 "Asia-Pacific"))) %>% 
+  mutate(show_number = 1:n(), .after = night) %>% 
+  unnest(dat) %>% 
+  left_join(distinct(taylor_album_songs, track_name, album_name),
+            join_by(song == track_name),
+            relationship = "many-to-one") %>% 
+  count(leg, date, city, night, show_number, album_name) %>% 
+  complete(nesting(leg, date, city, night, show_number), album_name) %>% 
+  mutate(n = replace_na(n, 0)) %>% 
+  arrange(album_name, date, night) %>% 
+  mutate(surprise_count = cumsum(n), .by = album_name) %>% 
+  mutate(album_name = replace_na(album_name, "Other"),
+         album_name = factor(album_name, c(album_levels, "Other")),
+         album_group = album_name)
+
+ggplot(surprise_song_count) +
+  facet_wrap(~ album_name, ncol = 3) +
+  geom_line(data = ~select(.x, -album_name),
+            aes(x = show_number, y = surprise_count, group = album_group),
+            color = "grey80", na.rm = TRUE) +
+  geom_line(aes(x = show_number, y = surprise_count, color = album_name),
+            show.legend = FALSE, linewidth = 2, na.rm = TRUE) +
+  scale_color_albums(na.value = "grey80") +
+  labs(x = "Show", y = "Songs Played") +
+  theme_minimal() +
+  theme(strip.text.x = element_text(hjust = 0, size = 10),
+        axis.title = element_text(size = 9))
+```
+
+</details>
+
+```{r eras-plot, echo = FALSE, message = FALSE, warning = FALSE}
+#| fig-asp: 1.1
+#| fig-alt: >
+#|   A series of line plots showing the increases in the total number of songs
+#|   from each album that Taylor has played as surprise songs during The Eras
+#|   Tour.
+```
+
+Some test.
+
+```{r, eval = FALSE}
+missing_firsts <- tibble(date = as.Date(c("2023-11-01",
+                                          "2024-02-01")))
+day_ones <- surprise_song_count %>% 
+  slice_min(date, by = c(leg, album_name)) %>% 
+  select(leg, date, album_name) %>% 
+  mutate(date = date - lubridate::ddays(1))
+
+surprise_song_count %>% 
+  bind_rows(missing_firsts) %>% 
+  arrange(date) %>% 
+  fill(leg, .direction = "up") %>% 
+  bind_rows(day_ones) %>% 
+  arrange(album_name, date) %>% 
+  group_by(album_name) %>% 
+  fill(surprise_count, .direction = "down") %>% 
+  ggplot() +
+  facet_grid(cols = vars(leg), scales = "free_x", space = "free_x") +
+  geom_line(aes(x = date, y = surprise_count, group = album_name),
+            color = "grey80", na.rm = TRUE) +
+  geom_line(data = ~filter(.x, album_name == "1989 (Taylor's Version)"),
+            aes(x = date, y = surprise_count, color = album_name),
+            show.legend = FALSE, size = 2, na.rm = TRUE) +
+  scale_color_albums() +
+  scale_x_date(breaks = "month", date_labels = "%b %Y", expand = c(.02, .02)) +
+  theme_minimal() +
+  theme(strip.text.x = element_text(hjust = 0))
+```
+
+
+## I could show you incredible things
+
+There are many ways we can explore the data, but, honestly, baby, who's counting?
+Below is a collection of analyses that use data from taylor that I have found in the wild.
+If you use the data and find it useful, please reach out---I love to see the package used!
+
+```{r examples, echo = FALSE, results = "asis"}
+examples <- read.csv("data/example-uses.csv")
+cells <- paste("<td>",
+               paste0("  <a href=\"", examples$href, "\">"),
+               paste0("    <img src=\"", examples$preview, "\" ",
+                      "alt=\"", examples$description, "\" width=\"100%\"/>"),
+               "  </a>",
+               "</td>",
+               sep = "\n")
+
+needed_rows <- ceiling(length(cells) / 3)
+rows <- vapply(seq_len(needed_rows),
+               function(x) {
+                 paste("<tr>",
+                       paste(cells[((x * 3) - 2):(x * 3)], collapse = "\n"),
+                       "</tr>",
+                       sep = "\n")
+               },
+               character(1))
+
+tab <- paste("<table class=\"taylor-examples\" width=\"100%\">",
+             paste(rows, collapse = "\n"),
+             "</table>",
+             sep = "\n")
+
+cat(tab)
+```