docs: 📝 split exercises so they aren't so big (#229)

## Description

This PR splits up some exercises that were multi-part, which
participants found confusing last time.

Closes #139

<!-- Please delete as appropriate: -->
No review needed.

## Checklist

- [x] Ran spell-check
- [x] Formatted Markdown
- [x] Rendered website locally

.vscode/json.code-snippets

@@ -33,9 +33,9 @@
     "scope": "quarto,markdown",
     "prefix": "exercise",
     "body": [
-      "## :technologist: Exercise: ~${0:Title}",
+      "## :technologist: Exercise: ${0:Title}",
       "",
-      "**Time: ~${1:Minutes}**",
+      "> Time: ~${1:Minutes} minutes.",
       "",
       "${2:Text}",
     ],
@@ -61,7 +61,7 @@
       "## :book: Reading task: ~${0:Minutes}",
       "",
       "${1:Text body}",
-			"",
+      "",
       "{{< include ../includes/_sticky_up.qmd >}}",
       ":::",
     ],

appendix/model-variability.qmd

@@ -288,7 +288,7 @@ run.
 metabolites_with_bootstrap_results <- lipidomics |>
   split_by_metabolite() |>
   map(generate_model_variation) |>
-  map(tidy_bootstrap_output) |> 
+  map(tidy_bootstrap_output) |>
   list_rbind()
 metabolites_with_bootstrap_results
 ```
@@ -298,21 +298,12 @@ metabolites_with_bootstrap_results
 metabolites_with_bootstrap_results
 ```
 
-## :technologist: Exercise: Convert to function and add as a target in the pipeline
+## :technologist: Exercise: Convert variation calculation into a function
 
-> Time: \~15 minutes.
-
-Continue the workflow we've applied throughout the course:
-
-1.  Move the code into a function structure (use the scaffold below as a
-    guide).
-2.  Include one argument in the `function()` called `data`.
-3.  Replace `lipidomics` in the code with `data`.
-4.  Add the Roxygen documentation with {{< var keybind.roxgyen >}}.
-5.  Cut and paste the function over into the `R/functions.R` file.
-6.  Style using {{< var keybind.styler >}}.
-7.  Commit the changes to the Git history with {{< var keybind.git >}}.
+> Time: \~8 minutes.
 
+Continue the workflow we've applied throughout the course, convert the
+code to calculate the variation of the model estimates into a function.
 Use this code as a guide for the function.
 
 ``` r
@@ -323,6 +314,15 @@ calculate_variation <- function(___) {
 }
 ```
 
+1.  Move the code we made right before this exercise into a function
+    structure (use the scaffold below as a guide).
+2.  Include one argument in the `function()` called `data`.
+3.  Replace `lipidomics` in the code with `data`.
+4.  Add the Roxygen documentation with {{< var keybind.roxgyen >}}.
+5.  Cut and paste the function over into the `R/functions.R` file.
+6.  Style using {{< var keybind.styler >}}.
+7.  Commit the changes to the Git history with {{< var keybind.git >}}.
+
 ```{r solution-new-function-calculate-variation}
 #| eval: false
 #| code-fold: true
@@ -337,12 +337,27 @@ calculate_variation <- function(data) {
   data |>
     split_by_metabolite() |>
     purrr::map(generate_model_variation) |>
-    purrr::map(tidy_bootstrap_output) |> 
+    purrr::map(tidy_bootstrap_output) |>
     purrr::list_rbind()
 }
 ```
 
-Next, add the function to `_targets.R`.
+## :technologist: Exercise: Add the new function as a target in the pipeline
+
+> Time: \~8 minutes.
+
+Continuing from the previous exercise, add the `calculate_variation()`
+function to `_targets.R`. Use this code as a scaffold:
+
+``` r
+list(
+  ...,
+  tar_target(
+    name = ___,
+    command = ___
+  )
+)
+```
 
 1.  Create another `tar_target()` item in the `list()` at the bottom of
     the file.
@@ -354,14 +369,15 @@ Next, add the function to `_targets.R`.
     {{< var keybind.targets-make >}}.
 4.  Commit the changes to the Git history with {{< var keybind.git >}}.
 
-Use this code as a scaffold:
-
-``` r
+```{r solution-calculate-variation-to-pipeline}
+#| eval: false
+#| code-fold: true
+#| code-summary: "**Click for the solution**. Only click if you are struggling or are out of time."
 list(
-  ...,
+  # ...,
   tar_target(
-    name = ___,
-    command = ___
+    name = df_model_variation,
+    command = calculate_variation(lipidomics)
   )
 )
 ```
@@ -370,14 +386,14 @@ list(
 #| eval: false
 #| echo: false
 #| purl: true
-variation_targets_code <- '
+variation_targets_code <- "
   ),
   tar_target(
     name = df_model_variation,
     command = calculate_variation(lipidomics)
   )
 )
-'
+"
 # print_lines("_targets.R")
 revise_by_line_num(
   path = "_targets.R",
@@ -391,19 +407,6 @@ targets::tar_make()
 git_ci("_targets.R", "Update targets with model variation")
 ```
 
-```{r solution-calculate-variation-to-pipeline}
-#| eval: false
-#| code-fold: true
-#| code-summary: "**Click for the solution**. Only click if you are struggling or are out of time."
-list(
-  # ...,
-  tar_target(
-    name = df_model_variation,
-    command = calculate_variation(lipidomics)
-  )
-)
-```
-
 ## Visualizing the variability of results
 
 ::: {.callout-note collapse="true"}

justfile

@@ -20,6 +20,6 @@ style:
   #!/usr/bin/Rscript
   styler::style_dir(here::here())
 
-# Build pkgdown website
+# Build website
 build-site: 
   quarto render

sessions/pipelines.qmd

@@ -376,7 +376,7 @@ git_ci("DESCRIPTION", "Add tidyverse and targets to deps")
 c(
   "\n## Basic statistics\n\n```{r setup}\nlibrary(tidyverse)",
   "source(here::here('R/functions.R'))",
-  "lipidomics <- read_csv(here::here('data/lipidomics.csv'))\n```\n\n"  
+  "lipidomics <- read_csv(here::here('data/lipidomics.csv'))\n```\n\n"
 ) |>
   paste0(collapse = "\n") |>
   write_to_file("doc/learning.qmd")
@@ -410,7 +410,7 @@ Let's write out the code!
 lipidomics |>
   group_by(metabolite) |>
   summarise(across(value, list(mean = mean, sd = sd))) |>
-  mutate(across(where(is.numeric), ~round(.x, digits = 1)))
+  mutate(across(where(is.numeric), ~ round(.x, digits = 1)))
 ```
 
 After that, style the file using {{< var keybind.styler >}} on the file.
@@ -485,7 +485,7 @@ descriptive_stats <- function(data) {
   data |>
     dplyr::group_by(metabolite) |>
     dplyr::summarise(dplyr::across(value, list(mean = mean, sd = sd))) |>
-    dplyr::mutate(dplyr::across(tidyselect::where(is.numeric), ~round(.x, digits = 1)))
+    dplyr::mutate(dplyr::across(tidyselect::where(is.numeric), ~ round(.x, digits = 1)))
 }
 ```
 
@@ -537,19 +537,19 @@ Lets do that now.
 #| eval: false
 #| filename: "targets.R"
 list(
-    tar_target(
-        name = file,
-        command = "data/lipidomics.csv",
-        format = "file"
-    ),
-    tar_target(
-        name = lipidomics,
-        command = readr::read_csv(file, show_col_types = FALSE)
-    ),
-    tar_target(
-        name = df_stats_by_metabolite,
-        command = descriptive_stats(lipidomics)
-    )
+  tar_target(
+    name = file,
+    command = "data/lipidomics.csv",
+    format = "file"
+  ),
+  tar_target(
+    name = lipidomics,
+    command = readr::read_csv(file, show_col_types = FALSE)
+  ),
+  tar_target(
+    name = df_stats_by_metabolite,
+    command = descriptive_stats(lipidomics)
+  )
 )
 ```
 
@@ -618,8 +618,10 @@ Before continuing, let's commit the changes (including the files in the
 #| eval: false
 #| echo: false
 #| purl: true
-git_ci(c("_targets", "_targets.R", "DESCRIPTION"), 
-       "Tell targets about packages, add _targets")
+git_ci(
+  c("_targets", "_targets.R", "DESCRIPTION"),
+  "Tell targets about packages, add _targets"
+)
 ```
 
 ## Creating figure outputs
@@ -710,7 +712,7 @@ tasks:
 #' @return A ggplot2 graph.
 #'
 plot_distributions <- function(data) {
-  data |> 
+  data |>
     ggplot2::ggplot(ggplot2::aes(x = value)) +
     ggplot2::geom_histogram() +
     ggplot2::facet_wrap(ggplot2::vars(metabolite), scales = "free")
@@ -746,13 +748,13 @@ works, than **commit the changes to the Git history** with
 #| eval: false
 #| echo: false
 #| purl: true
-update_targets_plots <- '
+update_targets_plots <- "
 ),
 tar_target(
   name = fig_metabolite_distribution,
   command = plot_distributions(lipidomics)
 )
-'
+"
 # print_lines("_targets.R")
 # -20 to remove the previous `)`
 revise_by_line_num(
@@ -851,7 +853,8 @@ tar_read(fig_metabolites_distribution)
 #| eval: false
 #| echo: false
 #| purl: true
-basic_stats_md_text <- c("```{r setup}",
+basic_stats_md_text <- c(
+  "```{r setup}",
   "library(tidyverse)",
   "library(targets)",
   "lipidomics <- tar_read(lipidomics)",
@@ -865,7 +868,8 @@ basic_stats_md_text <- c("```{r setup}",
   "",
   "```{r}",
   "tar_read(fig_metabolites_distribution)",
-  "```")
+  "```"
+)
 print_file("doc/learning.qmd")
 revise_by_line_num(
   "doc/learning.qmd",
@@ -887,7 +891,7 @@ let's add it to ignore file by using:
 
 ```{r}
 #| filename: Console
-use_git_ignore("doc/_targets.yaml") 
+use_git_ignore("doc/_targets.yaml")
 ```
 
 Before continuing, let's commit these changes to the Git history with
@@ -905,7 +909,7 @@ can use it to format the final table text to be `mean value (SD value)`:
 
 ```{r stats-to-table}
 #| filename: "doc/learning.qmd"
-targets::tar_read(df_stats_by_metabolite) |> 
+targets::tar_read(df_stats_by_metabolite) |>
   mutate(MeanSD = glue::glue("{value_mean} ({value_sd})")) |>
   select(Metabolite = metabolite, `Mean SD` = MeanSD) |>
   knitr::kable(caption = "Descriptive statistics of the metabolites.")
@@ -916,7 +920,7 @@ targets::tar_read(df_stats_by_metabolite) |>
 #| echo: false
 #| purl: true
 pretty_basic_stats_code <- '
-targets::tar_read(df_stats_by_metabolite) |> 
+targets::tar_read(df_stats_by_metabolite) |>
   mutate(MeanSD = glue::glue("{value_mean} ({value_sd})")) |>
   select(Metabolite = metabolite, `Mean SD` = MeanSD) |>
   knitr::kable(caption = "Descriptive statistics of the metabolites.")
@@ -933,8 +937,8 @@ git_ci("doc/learning.qmd", "Basic stats as a pretty table.")
 ```{r execute-only-table-basic-stats}
 #| eval: true
 #| echo: false
-lipidomics |> 
-  descriptive_stats() |> 
+lipidomics |>
+  descriptive_stats() |>
   mutate(MeanSD = glue::glue("{value_mean} ({value_sd})")) |>
   select(Metabolite = metabolite, `Mean (SD)` = MeanSD) |>
   knitr::kable(caption = "The mean and standard deviation of metabolites in the lipidomics dataset.")