--- title: "A penguin story" date: "2024-07-08" format: html --- ## Data For this analysis, we'll use the penguin dataset in the R package `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} penguins |> count(species) |> knitr::kable() ``` ```{r} #| echo: false #| out-width: 75% #| fig-align: center #| fig-alt: Illustration of penguin culmen length and depth knitr::include_graphics("https://allisonhorst.github.io/palmerpenguins/reference/figures/culmen_depth.png") ``` The figure below shows the differences in culmen by species. ```{r} #| label: species #| warning: false #| fig-width: 5 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)") ``` ## Penguins The table below shows the top 10 penguins in the dataset. ```{r} #| label: top10 penguins |> slice_head(n = 10) |> select(species, island, bill_length_mm, bill_depth_mm) |> gt() ``` ## To find out more about this dataset See the R **palmerpenguins** package vignette available at