📘 Introduction

R Markdown and Quarto are powerful tools for creating dynamic documents that combine text, R code, tables, visualizations, and results in a single file. They support reproducible research by automatically updating outputs whenever the source code changes. Documents can be rendered into formats such as HTML, PDF, Word, presentations, websites, and books.

🎯 Why Learn R Markdown and Quarto?

📚 R Markdown vs Quarto

📦 Installing Required Packages

install.packages("rmarkdown")
install.packages("knitr")

library(rmarkdown)
library(knitr)

📄 Basic Structure of an R Markdown Document

An R Markdown document consists of a YAML header, Markdown text, and executable R code chunks.

---
title: "Sales Report"
author: "John Doe"
date: "2026-07-09"
output: html_document
---

# Introduction

This report analyzes monthly sales.

```{r}
summary(cars)
```

📄 Basic Structure of a Quarto Document

Quarto uses a similar structure but includes a simplified YAML configuration.

---
title: "Sales Report"
format: html
---

# Introduction

This report analyzes monthly sales.

```{r}
summary(cars)
```

📝 Markdown Syntax

💻 R Code Chunks

Code chunks contain executable R code enclosed within triple backticks.

```{r}
x <- 10
y <- 20

x + y
```

⚙️ Chunk Options

Chunk options control how code and results appear in the output document.

```{r echo=FALSE, warning=FALSE}
summary(iris)
```

📊 Including Tables

library(knitr)

kable(
  head(iris),
  caption = "Sample Iris Dataset"
)

📈 Including Charts

Charts generated inside code chunks automatically appear in the rendered document.

```{r}
plot(
  iris$Sepal.Length,
  iris$Sepal.Width,
  col = "blue",
  pch = 19
)
```

📑 Generating Reports

R Markdown and Quarto documents can be rendered into multiple output formats.

📤 Rendering Documents

library(rmarkdown)

render(
  "report.Rmd"
)

quarto render report.qmd

📊 Parameters in R Markdown

Parameters allow reports to be generated dynamically using different input values.

---
title: "Sales Report"
params:
  year: 2026
output: html_document
---

```{r}
params$year
```

🎨 Quarto Callouts

Quarto supports built-in callouts for highlighting important information.

::: {.callout-note}
This report was generated automatically using Quarto.
:::

📖 Creating Presentations

Both R Markdown and Quarto can generate presentations using formats such as Reveal.js and Beamer.

---
title: "Sales Presentation"
format: revealjs
---

# Sales Summary

- Revenue increased.
- Expenses decreased.
- Profit improved.

🌐 Creating Websites

Quarto can generate complete websites from multiple documents.

project:
  type: website

website:
  title: "My Data Science Website"

🌍 Real-World Example

A data analyst prepares a monthly business report that includes descriptive statistics, visualizations, and predictive models. The report is written in Quarto so that every month, updated data automatically produces a new HTML report with refreshed tables and charts.

---
title: "Monthly Sales Report"
format: html
---

# Sales Summary

```{r}
summary(iris)

plot(
  iris$Sepal.Length,
  iris$Petal.Length
)
```

🔄 Report Generation Workflow

📋 Common Functions and Commands

⚠️ Common Mistakes

💡 Best Practices

📝 Summary

R Markdown and Quarto enable the creation of dynamic, reproducible documents that integrate text, code, tables, and visualizations. In this chapter, you learned the structure of R Markdown and Quarto documents, Markdown syntax, code chunks, chunk options, table generation, chart integration, rendering documents, parameterized reports, presentations, websites, and report publishing. Mastering these tools allows you to automate report generation, improve reproducibility, and communicate analytical results professionally across multiple output formats.