Getting Started with RMarkdown

To create a new RMarkdown document in RStudio:

• Go to File > New File > R Markdown
• Choose a title and author for your document
• Select your preferred output format (HTML, PDF, or Word)

Basic Components

YAML Header

Every RMarkdown document starts with a YAML header that contains metadata about your document:

---
title: "My Analysis"
author: "Your Name"
date: "2024-03-19"
output: html_document
---

Text Formatting

RMarkdown uses simple syntax for text formatting:

# This is a heading
## This is a subheading

*This text is in italics*
**This text is bold**

- This is a bullet point
- This is another bullet point

1. This is a numbered list
2. This is another item

[This is a link](https://www.example.com)

Code Chunks

Code chunks are where you write and execute R code. They start with three backticks and {r}:

```{r}
# Your R code goes here
x <- 1:10
mean(x)
```

You can add options to code chunks to control their behavior:

```{r, echo=FALSE, warning=FALSE}
# This code will run but not show the code itself
# Warnings will be suppressed
```

Common Code Chunk Options

Code chunk options control how your code and its output are displayed in the final document. Here are the most commonly used options:

General Options

• echo=FALSE: Hide the code but show the output
• eval=FALSE: Show the code but don’t run it
• include=FALSE: Run the code but don’t show code or output
• warning=FALSE: Hide warnings
• message=FALSE: Hide messages
• error=FALSE: Hide error messages

Figure Options

• fig.width= and fig.height=: Set figure dimensions in inches
• fig.cap=: Add a figure caption
• fig.align=: Align figures (“left”, “center”, or “right”)
• out.width= and out.height=: Control the size of figures in the output document
• dpi=: Set the resolution of the figure (dots per inch)

Example of using figure options:

```{r plot-example, fig.width=8, fig.height=6, fig.cap="My beautiful plot", fig.align="center"}
ggplot(data, aes(x = value)) +
  geom_histogram() +
  theme_minimal()
```

Inline Code

You can include R code directly in your text using single backticks (`) and the letter r followed by a space as the prefix:

The mean of our data is `r mean(x)`.

Knit Your Document

Knit is the process of converting your RMarkdown document into its final format. When you knit a document, R runs all the code chunks and combines the results with your text to create a complete document.

How to Knit

• Click the “Knit” button in RStudio (looks like a ball of yarn)

• Or use the keyboard shortcut: Ctrl+Shift+K (Windows/Linux) or Cmd+Shift+K (Mac)

Output Formats

RMarkdown supports multiple output formats. The most common ones are:

• HTML: Creates a webpage that can be viewed in any browser. Great for interactive elements and sharing online.
• PDF: Creates a PDF document. Requires LaTeX to be installed on your system. Best for formal reports and publications.
• Word: Creates a Microsoft Word document. Useful when you need to share with collaborators who prefer Word.

You can specify the output format in your YAML header:

---
title: "My Analysis"
output:
  html_document:    # For HTML output
    toc: true      # Add a table of contents
    theme: cosmo   # Choose a theme
  pdf_document:     # For PDF output
    toc: true
    number_sections: true
  word_document:    # For Word output
    toc: true
---

Knit Options

You can customize the knitting process using various options in your YAML header:

• toc: true: Add a table of contents
• number_sections: true: Number the sections automatically
• code_folding: hide: Hide code chunks by default
• highlight: tango: Choose a syntax highlighting theme

---
title: "Simple Data Analysis"
author: "Your Name"
date: "2024-03-19"
output: html_document
---

# Introduction

This is a simple analysis of some ecological data.

## Data Analysis

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(tidyverse)
```

```{r load-data}
# Load and examine the data
data <- read.csv("my_data.csv")
head(data)
```

## Results

The mean value in our dataset is `r mean(data$value)`.

```{r plot, fig.cap="Distribution of values"}
ggplot(data, aes(x = value)) +
  geom_histogram() +
  theme_minimal()
```

Further Resources

• RMarkdown Website
• RMarkdown: The Definitive Guide
• RMarkdown Cheat Sheet