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README.Rmd
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README.Rmd
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---
output: github_document
bibliography: ["vignettes/packages.bib", "vignettes/PAGES.bib"]
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-"
)
```
# PAGES
<!-- badges: start -->
[](https://zenodo.org/badge/latestdoi/370009359)
<!-- badges: end -->
The package PAGES is the supportive material of a webinar designed for the [PAGES Early-Career Network (ECN)](http://pastglobalchanges.org/ecn/intro). The goal is to give some useful pointers to explore geological data, in particular stratigraphic occurrences, and uses RStudio and packages from the [tidyverse universe](https://www.tidyverse.org/packages/).
[](https://www.youtube.com/watch?v=r99jsChi4HU)
```{r pkgs, echo=FALSE, message=FALSE}
# following code for loading and writing the bibtex references for the used pkgs
pkgs <- c("dplyr", "tidyr", "tibble", "readr", "magrittr", "ggplot2",
"devtools", "roxygen2", "knitr", "rmarkdown", "bibtex",
"marelac", "datasauRus", "thematic")
# load
invisible(mapply(library, pkgs, character.only = TRUE))
# Get the R reference
rref <- citation()
# Create ref key
rref$key <- "rversion"
hadley <- bibentry(
key = "Wickham2015",
bibtype = "Book",
title = "R packages: organize, test, document, and share your code",
author = person("Hadley","Wickham"),
year = "2015",
publisher = " O'Reilly Media, Inc.",
url = "https://r-pkgs.org/"
)
knitr::write_bib(pkgs, "vignettes/packages.bib", prefix = "")
pkgs <- bibtex::read.bib("vignettes/packages.bib")
bibtex::write.bib(
purrr::reduce(list(rref, hadley, pkgs), append),
file = "vignettes/packages.bib"
)
# copy presentation
fs::file_copy(
fs::path("vignettes/PAGES", ext = "bib"),
fs::path("inst", "presentation", "PAGES", ext = "bib"),
overwrite = TRUE
)
fs::file_copy(
fs::path("vignettes/packages", ext = "bib"),
fs::path("inst", "presentation", "packages", ext = "bib"),
overwrite = TRUE
)
```
## R for Data Science (R4DS)
This class is modelled after Hadley Wickham's and Garrett Grolemund's R4DS. However, I have augmented the examples with cases from geology.
```{r cover, echo=FALSE, fig.cap="Book cover [@Wickham2016]", out.width="40%"}
knitr::include_graphics("man/figures/cover.png")
```
## Credits
The construction of the R [@rversion] package *PAGES* and associated documentation was aided by the packages; *devtools* [@devtools], *roxygen2* [@roxygen2], *knitr* [@knitr; @knitr2014 ; @knitr2015], *rmarkdown* [@rmarkdown; @rmarkdown2018; @rmarkdown2020], *bibtex* [@bibtex], and the superb guidance in the book: *R packages: organize, test, document, and share your code*, by @Wickham2015. In addition, this package relies on a set of external packages from the tidyverse universe, including: *dplyr* [@dplyr], *tidyr* [@tidyr], *tibble* [@tibble], *readr* [@readr], *magrittr* [@magrittr], and *readr* [@readr]. Plots are made with *ggplot2* [@ggplot2; @ggplot22016] and *thematic* [@thematic] is used for a consistent design in the presentation.
The package *marelac* [@marelac] is used for chemical data and transformations, and the package *datasauRus* [@datasauRus] is used as an example for the strength of plotting data.
## Installation
You can install the released version of PAGES from [github](https://github.io) with:
``` r
# Install PAGES from GitHub:
# install.packages("devtools")
devtools::install_github("MartinSchobben/PAGES", build_vignettes = TRUE)
```
## Usage
Load PAGES with `library`.
```{r}
library(PAGES)
```
## Data sources
The study on the Triassic--Jurassic (~201 million years before present) boundary section of Bonenburg (Germany) and Kuhjoch (Austria) by @Schobben2019 is used as the example material for this course. Lazy load datasets constitute:
-`kuhjoch` - Kuchjoch is a palynological dataset where the counts have summed for spores, pollen, aquatic and terrestrial elements.
-`bonenburg` - Bonenburg is a geochemical dataset containing: elemental analyser total organic carbon (TOC) and total nitrogen (TN), XRF element data; Aluminium (Al), Potassium (K) and sodium (Na), as well as the carbon isotope composition of TOC (del13Ctoc).
Raw datasets (`kuhjoch_raw.csv` and `bonenburg_raw.csv`) can be easily accessed with the `PAGES_example()` function and a call to the `readr` function `read_csv()`.
``` r
readr::read_csv(PAGES_example("kuhjoch_raw.csv"))
```
## Render presentation slides
To render the presentation slides:
``` r
render_slides()
```
## Exercises
Details regarding the exercise and live programming during the webinar can be found under the package vignettes (called with `vignette()`).
- RStudio projects: `vignette("project", package = "PAGES")`
- Exploratory data analysis: `vignette("explore", package = "PAGES")`
- Patterns and models: `vignette("model", package = "PAGES")`
- Load, tidy and transform data: `vignette("wrangle", package = "PAGES")`
## Tidy format
The lazy load datasets are provided in a tidy format. Look-up directory `data-raw` on the Github repository for details on the data processing.
```{r tidy}
head(bonenburg)
```
Besides wide format data the similarly named datasets with the suffix `_long` are used to generate, for example, multi-proxy stratigraphic plots for initial data exploration.
```{r strat, fig.height=4, fig.width=8, fig.cap="Bonenburg geochemical data traversing the Triassic-Jurassic boundary."}
ggplot(data = bonenburg_long) +
geom_point(mapping = aes(x = value, y = height)) +
facet_grid(cols = vars(measurement), scales = "free_x") +
theme_classic()
```
# Further reading
**Data science with R**
Hadley Wickham & Garrett Grolemund 2016 *R for Data Science*
**General statistics with R**
Peter Dalgaard 2008 *Introduction to statistics with R*
**Regression with R**
John Fox & Sanford Weisberg 2018 *An R companion to applied regression*
**Mixed effect models with R**
Alain Zuur et al. 2008 *Mixed Effects Models and Extensions in Ecology with R*
---
nocite: |
@Dalgaard2008; @Fox2018; @Zuur2008; @Wickham2016
...
# References