appendixB.qmd

---
title: "Appendix B: Quarto"
author: "Your Name"
date: 'Rendered on `r Sys.Date()`'
format: 
  html:
    toc: true
    toc-float: true
    number-sections: true
    df-print: paged # default, kable, tibble, paged, or a custom function
    code-folding: show # null, hide, show
    self-contained: true
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(
  echo = TRUE,
  out.width = '100%'
)

# packages used ----
library(tidyr)      # for data processing
library(dplyr)      # for data processing
library(readr)      # for reading/saving data
library(ggplot2)    # for plots
library(kableExtra) # for tables

# load external scripts ----
source("R/functions.R")
```

You can reference figures or tables using the chunk name, e.g., Figure @fig-disp-hp-vs and Table @tbl-mtcars. In quarto, figure chunk names must start with "fig-" and tables must start with "tbl-".

## Data Processing

Scripts typically start with the code to transform raw data into processed data. Time-consuming code may be set to not evaluate and the results saved and loaded in a separate code chunk.

```{r, eval = FALSE}
# calculate means by number of gears and carburetors
aggregated <- mtcars |>
  group_by(gear, carb) |>
  summarise(mpg = mean(mpg),
            disp = mean(disp),
            hp = mean(hp),
            .groups = "drop")

write_csv(aggregated, "data/aggregated.csv")
```

```{r}
# load saved data
aggregated <- read_csv("data/aggregated.csv", show_col_types = FALSE)
```



## Tables

If you use `knitr::kable()` or `kabelExtra::kable()` to display tables as HTML, they are added to the auto-numbered tables. In Quarto you can add the caption in the code chunk.

```{r tbl-mtcars}
#| tbl-cap: Mean miles per gallon (mpg), displacement (disp) and horsepower (hp) by number of forward gears (gear) and carburetors (carb)

table1 <- aggregated |>
  kable(digits = 1) |>
  kable_material()

save_kable(table1, "tables/table1.html")

table1
```



## Figures

The fig-alt option sets alt-text for screen readers. This should allow a person with low or no vision to understand the meaning of the plot. 

```{r fig-disp-hp-vs}
#| fig.cap: The relationship between displacement and horsepower for V-shaped and straight engines.
#| fig.alt: A scatterplot with Displacement (cu.in.) along the x-axis, ranging from ~50 to ~500, and Gross Horsepower along the y-axis, ranging from ~50 to ~350. 15 red points are plotted for V-shaped engines and 12 blue points for straight engines. There is a positive relationship between displacement and horsepower, with the V-shaped engines having typically higher values on both than straight engines. 

ggplot(mtcars, aes(x = disp, y = hp, color = as.factor(vs))) +
  geom_point() +
  labs(x = "Displacement (cu.in.)",
       y = "Gross Horsepower") +
  scale_color_manual(name = "Engine", 
                     labels = c("V-shaped", "straight"), 
                     values = c("firebrick", "dodgerblue3"))

ggsave("figures/plot1.png", width = 7, height = 5)
```