8 R Markdown in VSCode

Keywords

R Markdown in VSCode, report generation in R, dynamic reports in R, VSCode for R Markdown, R Markdown tutorial

8.1 Introduction

R Markdown is a powerful tool for creating dynamic reports that combine code, narrative, and visualizations. In this chapter, we will explore how to set up and use R Markdown within VSCode for generating reproducible reports and documents.

8.2 Prerequisites

Install essential tools for R programming in VSCode as outlined in the previous chapters (Chapter 2 and Chapter 3).
Ensure you have the rmarkdown package installed in R and the vscode-R extension in VSCode, as well as Pandoc for converting R Markdown documents to different output formats. Pandoc comes pre-installed with RStudio, but you can also install it separately from Pandoc’s official website.

8.3 Creating an R Markdown Document

To create a new R Markdown document in VSCode, follow these steps:

Create a New File: In VSCode, click on File > New File, then save it with the .Rmd extension (e.g., report.Rmd).
Add YAML Header: Start by adding a YAML header at the top of your file. This header defines the document’s title, author, output format, and other metadata.
```
---
title: "Data Analysis Report"
author: "Your Name"
date: "2024-12-06"
output: html_document
---
```
Add Content: You can mix R code chunks, text, and visualizations in your R Markdown document. Use triple backticks with {r} to create a code chunk.
```
## Introduction

This is an example of an R Markdown document in VSCode.

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

8.4 Running R Code in R Markdown

Place your cursor inside a code chunk and use the following shortcuts:

Run Code Chunk: Press Ctrl + Shift + Enter (Windows/Linux) or Cmd + Shift + Enter (Mac) to execute the current chunk.
Run Line or Selection: Press Ctrl + Enter or Cmd + Enter to run the selected line or lines of code.

The output from the code will be displayed directly below the chunk, providing immediate feedback and results.

8.5 Generating Output

R Markdown allows you to generate documents in various formats, such as HTML, PDF, and Word. To knit the document in VSCode:

Open Command Palette: Press F1 or Ctrl + Shift + P to open the command palette.
Run Knit Command: Type rmarkdown: Render and select the desired output format (e.g., HTML, PDF).
View the Output: The generated document will be saved in the same directory as your .Rmd file. You can view the HTML output directly in your browser or open a PDF/Word document.

8.6 Customizing R Markdown Output

VSCode allows you to customize the output of your R Markdown documents by editing the YAML header or adding custom parameters.

Themes and Highlighting: You can change the appearance of your document by specifying different themes and highlight styles in the YAML header.
```
output:
  html_document:
    theme: united
    highlight: tango
```
Parameterization: R Markdown documents can be parameterized, allowing you to create dynamic reports based on user inputs.
```
params:
  data_file: "data.csv"
```
You can then use params$data_file within your R code to reference the specified file.

8.7 Inline Code and Dynamic Text

R Markdown supports inline code to add dynamic content to your report. For example, you can include the current date or calculated values directly in the text:

As of `{r} Sys.Date()`, the dataset contains `{r} nrow(cars)` observations.

This feature is particularly useful for creating reproducible reports that update automatically when the data changes.

8.8 Best Practices for Report Generation

Organize Code into Chunks: Break your code into logical chunks and label each chunk for easy reference.
```
```{r load-data, echo=FALSE}
data <- read.csv("data.csv")
```
```
Use Caching: For time-consuming computations, use the cache = TRUE option to avoid re-running the code every time you knit the document.
```
```{r model, cache=TRUE}
model <- lm(mpg ~ wt + hp, data = mtcars)
```
```
Hide Code or Output: You can control the visibility of code and output by using chunk options like echo, results, and include.
```
```{r, echo=FALSE}
plot(mtcars$wt, mtcars$mpg)
```
```

8.9 Tips for Using R Markdown in VSCode

Live Preview: Use the Live Preview extension to view changes in real-time as you edit your R Markdown document.
Code Folding: VSCode allows you to fold and unfold code chunks, making it easier to navigate large documents.
Linting and Formatting: Use the lintr and styler packages for linting and formatting your R Markdown code to maintain readability and consistency.

8.10 Example of an R Markdown Document File Content

8.10.1 Source code---
title: 'Example Report for R Markdown'
author: 'Datanovia'
date: '`{r} Sys.Date()`'
output: html_document
---

## Introduction

This R Markdown document provides a simple demonstration of using code, text, and visualizations together to create an interactive report.



## Summary of the `cars` Dataset

The `cars` dataset in R contains speed and stopping distance data from the 1920s. Here is a summary of the data:

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

## Scatter Plot of Speed vs. Stopping Distance

Let's create a scatter plot to visualize the relationship between speed and stopping distance:

```{r}
plot(cars$speed, cars$dist,
     xlab = "Speed (mph)",
     ylab = "Stopping Distance (ft)",
     main = "Speed vs. Stopping Distance")
```

## Conclusion

This is a simple example of how you can use R Markdown to create informative and visually appealing reports. You can mix text, R code, and visualizations to produce dynamic content.

Feel free to add more sections, analyses, or visualizations as you continue to explore the power of R Markdown!

8.10.2 Execution output

Execution of the R Markdown document in Vscode

8.11 Conclusion

R Markdown in VSCode provides a flexible and efficient way to create dynamic, reproducible reports. You can generate professional-quality documents that integrate code, analysis and visualization.