03 Quarto Document using `plamerpenguins`

Notebooks for Academics

guided-exercise

palmerpenguins is a great dataset for data exploration & visualization

Author

Carlos Granell

Published

May 2, 2024

Create an RStudio Project on Posit Cloud using an existing template

In Your Workspace, click New Project > New RStudio Project
Select File > New File > Quarto Document… to create the file notebook.qmd
Open it and delete all the content of the body section

Structure of the notebook using markdown

Write main headings (‘##’):
- Introduction
- Data & methods
- Exploratory analysis
- Conclusion
- References
Add YAML options for authoring and table of contents

YAML header: authoring and table of content

---
title: "Notebook using `palmerpenguins`"
author: "Carlos Granell"
description: "`palmerpenguins` is a great dataset for data exploration & visualization"
date: "04/20/2024"
format: 
  html:
    toc: true
    toc-location: left
    toc-title: Contents
---

Numbering sections:
- Add YAML option number-sections: true
- Add “{.unnumbered}” next to References section to make it non-numbered section

Body: Non-numbered section

## References {.unnumbered}

Set up code libraries

Select File > New File > R Script to create the file install.R
Add libraries to use in the notebook

install.R

install.packages("knitr")
install.packages("rmarkdown")
install.packages("palmerpenguins")
install.packages("tidyverse")
install.packages("gt")

Open the R Script and run it
Add code chunk in the notebook.qmd

Body: 'setup' chuck

```{r}
#| label: setup
#| echo: false
#| warning: false

library(tidyverse) # tidy data management. Similar to python's pandas
library(palmerpenguins) # our working dataset
library(gt)  # tabular data

```

Citations

Select File > New File > Text File to create the file references.bib
Add A YAML options to support citations: bibliography: references.bib
Open Console and type citation("palmerpenguins"). Copy and paste the bib entry into reference.bib

This notebook explores the palmerpenguins dataset as a Quarto (http://quarto.org) document. The dataset comes in its own package, so we install the palmerpenguins package.

This notebook explores the palmerpenguins dataset as a Quarto document. The dataset comes in its own package, so we install the palmerpenguins package (Horst, Hill, and Gorman 2020).

Check Citations & Footnotes for help and look at the References section once you render the notebook

Write Dataset section

Add a subheading “Dataset” (###) to the “Dataset & Methods” section

Raw text
Final result

Data were collected and made available by Dr. Kristen Gorman (https://www.uaf.edu/cfos/people/faculty/detail/kristen-gorman.php) and the Palmer Station, Antarctica LTER, a member of the Long Term Ecological Research Network (https://lternet.edu/).

The palmerpenguins package contains two datasets:

penguins: is a simplified version of the raw data
penquings_raw: contains all the variables and original names

In this notebook we are going to use the penguins dataset, which contains the following 8 variables are: species, island, bill_length_mm, bill_depth_mm, flipper_length_mm, body_mass_g, sex, year.

Data were collected and made available by Dr. Kristen Gorman and the Palmer Station, Antarctica LTER, a member of the Long Term Ecological Research Network.

The palmerpenguins package contains two datasets:

penguins: is a simplified version of the raw data
penquings_raw: contains all the variables and original names

In this notebook we are going to use the penguins dataset, which contains the following 8 variables:

[1] "species"           "island"            "bill_length_mm"   
[4] "bill_depth_mm"     "flipper_length_mm" "body_mass_g"      
[7] "sex"               "year"

Use of inline expressions
Add a table & reference to the table. Check Tables
Add a figure and reference to the figure. Check Figures

Write Methods section

Add a subheading “Methods” (###) to the “Dataset & Methods” section

Raw text
Final result

For data manipulation, we use the tidyverse meta package. For visualization purpose, we use ggplot2 package and the gt package.

The ggplot2 package, which is already included in the tidyverse, is an R package to create visualisation using the Grammar of Graphics (https://www.amazon.com/Grammar-Graphics-Statistics-Computing/dp/0387245448), originally created by Leland Wilkinson.

The gt package offers a different and easy-to-use set of functions that helps us build display tables from tabular data. The gt philosophy states that a comprehensive collection of table parts can be used to create a broad range of functional tables. The output formats that gt currently supports are HTML, LaTeX, and RTF.

For data manipulation, we use the tidyverse meta package (Wickham et al. 2019). For visualization purpose, we use ggplot2 package (Wickham 2016) and the gt package (Iannone et al. 2024).

The ggplot2 package, which is already included in the tidyverse, is an R package to create visualisation using the Grammar of Graphics, originally created by Leland Wilkinson.

The gt package offers a different and easy-to-use set of functions that helps us build display tables from tabular data. The gt philosophy states that a comprehensive collection of table parts can be used to create a broad range of functional tables. The output formats that gt currently supports are HTML, LaTeX, and RTF.

Write Exploratory analysis section

Explanation in class: code chucks to produce output figures, YAML options for code execution, and freeze.

Write Conclusions section

Raw text
Final result

This notebook demonstrates that the palmerpenguins package is a great data set to get started with computational notebooks with Quarto Document (https://quarto.org/docs/output-formats/html-basics.html). We have learned YAML options (table of content, section numbering, for HTML & PDF output, dhow to create content with markdown (headings, tables, figures, citations, cross references, margin content), execute code chucks, display code outputs, and specify options for code chunks.

This notebook demonstrates that the palmerpenguins package is a great data set to get started with computational notebooks with Quarto Document. We have learned YAML options (table of content, section numbering, for HTML & PDF output, dhow to create content with markdown (headings, tables, figures, citations, cross references, margin content), execute code chucks, display code outputs, and specify options for code chunks.

Support PDF format

Add YAML options for PDF

YAML header: PDF output format

---
format: 
  html:
    toc: true
    toc-location: left
    toc-title: Contents
  pdf:
    toc: true
    colorlinks: true
---

tinytext is required to compile PDF documents. Use the following command:

Terminal

quarto install tinytex

References

Horst, Allison Marie, Alison Presmanes Hill, and Kristen B Gorman. 2020. Palmerpenguins: Palmer Archipelago (Antarctica) Penguin Data. https://doi.org/10.5281/zenodo.3960218.

Iannone, Richard, Joe Cheng, Barret Schloerke, Ellis Hughes, Alexandra Lauer, and JooYoung Seo. 2024. Gt: Easily Create Presentation-Ready Display Tables. https://gt.rstudio.com.

Wickham, Hadley. 2016. Ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. https://ggplot2.tidyverse.org.

Wickham, Hadley, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D’Agostino McGowan, Romain François, Garrett Grolemund, et al. 2019. “Welcome to the tidyverse.” Journal of Open Source Software 4 (43): 1686. https://doi.org/10.21105/joss.01686.