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R-ecology-lesson

Data Analysis and Visualization in R for Ecologists.
https://github.com/datacarpentry/R-ecology-lesson

Category: Sustainable Development
Sub Category: Education

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carpentries data-carpentry data-visualisation data-visualization data-wrangling ecology english lesson open-educational-resources r stable

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Data Analysis and Visualization in R for Ecologists

README.md

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Data Carpentry: R for data analysis and visualization of Ecological Data

This is an introduction to R designed for participants with no programming
experience. It can be taught in 3/4 of a day (approximately 6 hours).
It is a redesigned version of the original Data Carpentry lesson.

The initial effort towards this redesign was done by Michael Culshaw-Maurer in another repository in The Carpentries Incubator: https://github.com/carpentries-incubator/R-ecology-lesson (now archived). See Michael's notes while preparing the redesign in the update_plans.md file of that repository.

The lesson starts with information about the R programming language and the RStudio interface. It then moves to loading in data and exploring how to visualise it with ggplot2. The next episode takes learners through an exploration of data frames and some common data cleaning operations, before discussing vectors and factors. The final episode introduces the flow of data in R, and how to combine operations to select, filter, and mutate a data frame.

Providing feedback on this lesson

If you teach this redesigned lesson, please open an issue on this repository to share your experience.

Prerequisites

The lesson assumes no prior knowledge of R or RStudio.
Learners should have R and RStudio installed on their computers. They will also
need to be able to install R packages from CRAN, create directories, and
download files.
See the lesson website
for instructions on installing R, RStudio, and the required R packages.

Contributing

Contributions to the content and development of these lesson are very welcome!
If you would like to contribute, we encourage you to review our contributing guide.

Questions

If you have any questions or feedback, please open an issue, contact the
maintainers, or come chat with us on the
Slack Channel for this lesson.
If you don't already have a Slack account with the Carpentries, you can
create one.

Maintainers

Citation (CITATION.Rmd)

# CITATION

```{r, echo=FALSE, results="hide"}
eds <- personList(
    person(given = "Ana Costa", family = "Conrado"),
    person(given = "Auriel M.V.", family = "Fournier"),
    person(given = "Brian", family = "Seok"),
    person(given = "Francois", family = "Michonneau")
)

generate_citation <- function(authors = "AUTHORS",
                              editors = eds,
                              doi = "10.5281/zenodo.3264888") {
    aut <- readLines(authors)
    
    # remove first line
    aut <- aut[-1]
    
    aut <- as.person(aut)
    
    bibentry(
        bibtype = "Misc",
        author = personList(aut),
        title = "datacarpentry/R-ecology-lesson: Data Carpentry: Data Analysis and Visualization in R for Ecologists, June 2019",
        editor = editors,
        month = format(Sys.Date(), "%B"),
        year = format(Sys.Date(), "%Y"),
        url = "https://datacarpentry.org/R-ecology-lesson/",
        doi = doi
    )
}

generate_zenodo_json <- function(editors) {
    tfile <- tempfile()
    system(paste("git shortlog -n -e -s >", tfile))
    aut <- read.table(file = tfile, sep = "\t")
    aut <- as.person(aut[, 2])
    pp <- lapply(aut,  function(x) {
        res <- gsub("^\\s", "", paste(paste(x$given, collapse = " "),
                                      x$family))
        list(name =  res)
    })
    eds <- paste(editors$given, editors$family)
    res <- list(creators = pp)
    
    if (!is.null(editors)) {
        ctb <- lapply(paste(editors$given, editors$family),
                      function(x)
                          list(type = "Editor", name = x))
        res <- c(list(contributors = ctb), res)
    }
    cat(jsonlite::toJSON(res, auto_unbox = TRUE), file = ".zenodo.json")
}

system("update-copyright.py")
## generate_zenodo_json(editors = eds)
```

## Data

Data is from the paper S. K. Morgan Ernest, Thomas J. Valone, and James
H. Brown. 2009. Long-term monitoring and experimental manipulation of a
Chihuahuan Desert ecosystem near Portal, Arizona, USA. Ecology 90:1708.

[http://esapubs.org/archive/ecol/E090/118/](http://esapubs.org/archive/ecol/E090/118/)

A simplified version of this data, suitable for teaching is available on
[figshare](https://doi.org/10.6084/m9.figshare.1314459.v5).

## Lessons

The first workshop was run at NESCent on May 8-9, 2014 with the development and
instruction of lessons by Karen Cranston, Hilmar Lapp, Tracy Teal, and Ethan
White and contributions from Deb Paul and Mike Smorul.

Original materials adapted from SWC Python lessons by Sarah Supp. John Blischak
led the continued development of materials with contributions from Gavin
Simpson, Tracy Teal, Greg Wilson, Diego Barneche, Stephen Turner, and Karthik
Ram. This original material has been modified and expanded by François
Michonneau.

The **`dplyr`** lesson was created by Kara Woo, who copied and modified and
modified from Jeff
Hollister's [materials](https://usepa.github.io/introR/2015/01/14/03-Clean/).

The **`ggplot2`** lesson was initially created by Mateusz Kuzak, Diana Marek,
and Hedi Peterson, during a Hackathon in Espoo, Finland on March 16-17, 2015,
sponsored by the [ELIXIR project](https://elixir-europe.org/).

You can cite this Data Carpentry lesson as follow:

```{r, echo=FALSE, results="asis"}
print(generate_citation(), style = "html")
```

or as a BibTeX entry:

```{r, echo=FALSE, comment=""}
print(generate_citation(), style = "bibtex")
```



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Last synced: 6 days ago

Total Commits: 1,020
Total Committers: 217
Avg Commits per committer: 4.7
Development Distribution Score (DDS): 0.634

Commits in past year: 24
Committers in past year: 5
Avg Commits per committer in past year: 4.8
Development Distribution Score (DDS) in past year: 0.583

Name Email Commits
Francois Michonneau f****u@g****m 373
Tobias Busch t****h@g****m 46
Toby Hodges t****s@g****m 31
Katrin Leinweber K****r@t****u 27
Brian Seok s****k@c****u 27
Adam Obeng g****b@b****m 25
zkamvar z****r 19
Mateusz Kuzak m****k@g****m 15
Katrin Leinweber 9****r 14
Tracy Teal t****l@g****m 14
Edmund Hart e****t@g****m 14
Ana Costa 2****t 13
Philip Lijnzaad p****d@g****m 12
Kara Woo w****a@g****m 12
Ben Marwick b****k@h****m 10
maneesha sane 8****a 10
Aleksandra Pawlik a****k@g****m 9
Auriel M.V. Fournier a****r@g****m 9
Matthias Grenié m****e@h****m 8
kathy0305 k****5@h****m 8
Erin Becker e****r@c****g 8
Ben Bolker b****r@g****m 8
Ethan White e****n@w****g 7
chriseshleman e****s@g****m 7
Kari L. Jordan k****n@m****m 7
Doug Joubert d****C 5
Mark Robinson m****n@i****h 5
David k****d@s****u 5
Sergio Martínez Cuesta s****e@g****m 5
Ruud Steltenpool g****m@s****m 5
and 187 more...

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Past year issues: 8
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Past year issue authors: 6
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Past year average comments per issue: 1.25
Past year average comments per pull request: 1.35
Past year merged pull request: 18
Past year bot issues: 0
Past year bot pull requests: 0

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Dependencies

DESCRIPTION cran
  • RSQLite * imports
  • dbplyr * imports
  • gridExtra * imports
  • hexbin * imports
  • hunspell * imports
  • knitr * imports
  • patchwork * imports
  • remotes * imports
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  • tidyverse * imports

Score: 11.214708090603065