---
title: "A penguin story"
date: "2024-07-08"
format: 
  html:
    toc: true
    theme: litera
code-annotations: hover
---

## Data

For this analysis, we'll use the penguin dataset in the R package `palmerpenguins` (<https://allisonhorst.github.io/palmerpenguins>).

```{r}
#| label: load-packages
#| message: false
library(tidyverse)
library(palmerpenguins)
library(gt)
```

The `penguins` dataset contains the following elements:

```{r}
glimpse(penguins)
```

## Species

We have `r length(unique(penguins$species))` species in this dataset: `r knitr::combine_words(unique(penguins$species))` that are not evenly distributed.

```{r}
#| column: margin
penguins |>
  count(species) %>%
  knitr::kable()
```

```{r}
#| label: fig-culmen
#| echo: false
#| fig-align: center
#| fig-alt: Illustration of penguin culmen length and depth
#| fig-cap: Illustration of penguin culmen length and depth
#| column: page
knitr::include_graphics("https://allisonhorst.github.io/palmerpenguins/reference/figures/culmen_depth.png")
```

The @fig-species shows the differences in culmen by species.

```{r}
#| label: fig-species
#| warning: false
#| fig-with: 5.0
#| fig-cap: Categorizing species by culmen size
#| fig-cap-location: margin
ggplot(
  penguins,
  aes(
    x = bill_length_mm, y = bill_depth_mm,
    color = species, shape = species
  )
) +
  geom_point() +
  labs(x = "Culmen length (mm)", 
       y = "Culmen depth (mm)")
```


## Manchots

The table below (numbered [-@tbl-top10]) below shows the top 10 penguins in the dataset.

```{r}
#| label: tbl-top10
#| tbl-cap: The first 10 elements of the dataset
#| tbl-cap-location: bottom
penguins |>
  slice_head(n = 10) |>
  select(species, island, 
         bill_length_mm, bill_depth_mm) |>
  gt() # <1>
```

1. We use **gt** here, but any table package can be used, for example **flextable** or **tinytable**.

Let's get a summary of all our data set in a fancy table[^fancy_table]

```{r}
#| echo: false
spanners_and_header <- function(gt_tbl) {
  gt_tbl |>
    tab_spanner(
      label = md("**Adelie**"),
      columns = 3:4
    ) |>
    tab_spanner(
      label = md("**Chinstrap**"),
      columns = c("Chinstrap_female", "Chinstrap_male")
    ) |>
    tab_spanner(
      label = md("**Gentoo**"),
      columns = contains("Gentoo")
    ) |>
    tab_header(
      title = "Penguins in the Palmer Archipelago",
      subtitle = "Data is courtesy of the {palmerpenguins} R package"
    )
}

penguin_counts <- penguins |>
  filter(!is.na(sex)) |>
  mutate(year = as.character(year)) |>
  group_by(species, island, sex, year) |>
  summarise(n = n(), .groups = "drop")

penguin_counts_wider <- penguin_counts |>
  pivot_wider(
    names_from = c(species, sex),
    values_from = n
  ) |>
  # Make missing numbers (NAs) into zero
  mutate(across(.cols = -(1:2), .fns = ~ replace_na(., replace = 0))) |>
  arrange(island, year)

desired_colnames <- colnames(penguin_counts_wider) |> 
  str_remove('(Adelie|Gentoo|Chinstrap)_') |> 
  str_to_title() |> 
  set_names(nm = colnames(penguin_counts_wider))

penguin_counts_wider |>
  mutate(across(.cols = -(1:2), ~ if_else(. == 0, NA_integer_, .))) |>
  mutate(
    island = as.character(island),
    year = as.numeric(year),
    island = paste0("Island: ", island)
  ) |>
  gt(groupname_col = "island", rowname_col = "year") |>
  cols_label(.list = desired_colnames) |>
  spanners_and_header() |>
  sub_missing(missing_text = "-") |>
  summary_rows(
    groups = TRUE,
    fns = list(
      "Maximum" = ~ max(.),
      "Total" = ~ sum(.)
    ),
    formatter = fmt_number,
    decimals = 0,
    missing_text = "-"
  ) |>
  tab_options(
    data_row.padding = px(2),
    summary_row.padding = px(3), # A bit more padding for summaries
    row_group.padding = px(4) # And even more for our groups
  ) |>
  opt_stylize(style = 6, color = "gray")
```

[^fancy_table]: Thanks to [\@AlbertRapp](https://github.com/AlbertRapp/gt_book/commits?author=AlbertRapp) for its great example of ["creating beautiful tables in R with {gt}"](https://gt.albert-rapp.de/getting_started)

::: {.callout-note collapse=true}

## To find out more about this dataset

See the R **palmerpenguins** package vignette available at <https://allisonhorst.github.io/palmerpenguins/>
:::