r-ecology-lesson-1

https://github.com/tobyhodges/r-ecology-lesson-1

Science Score: 77.0%

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CITATION.cff file
Found CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
Found 7 DOI reference(s) in README
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Academic publication links
Links to: zenodo.org
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39 of 195 committers (20.0%) from academic institutions
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Low similarity (12.9%) to scientific vocabulary

Keywords from Contributors

english lesson stable carpentries data-carpentry data-wrangling ecology open-educational-resources bootstrapping auroc

Last synced: 6 months ago · JSON representation ·

Repository

Basic Info

Host: GitHub
Owner: tobyhodges
License: other
Language: R
Default Branch: main
Homepage: https://tobyhodges.github.io/R-ecology-lesson-1/
Size: 16.6 MB

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Stars: 0
Watchers: 1
Forks: 16
Open Issues: 1
Releases: 0

Created over 3 years ago · Last pushed almost 3 years ago

Metadata Files

Readme Changelog Contributing License Citation Authors Zenodo

README.md

ATTENTION This is an experimental test of the {sandpaper} lesson infrastructure with automated conversion via the lesson transition script.

If anything seems off, please contact Zhian Kamvar zkamvar@carpentries.org

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). The lesson starts with some basic information about syntax for the R programming language, the RStudio interface, and moves through to specific programming tasks, such as importing CSV files, the structure of data frame objects in R, dealing with categorical variables (i.e. factors), basic data manipulation (adding/removing rows and columns), and finishing with calculating summary statistics and a brief introduction to plotting. There is also a lesson on how to use databases from R that is intended to be taught after the SQL lesson, and ideally at the end of a Data Carpentry workshop.

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.

Topics

Code handout

There is a code handout that is intended to be distributed to the participants. This file includes some of the examples used during teaching and the titles of the section. It provides a guide that the participants can fill in as the lesson progresses. Participants can also source code from this file to avoid typos in more complex examples.

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.

Tobias Busch
Ana Costa Conrado
François Michonneau
Maneesha Sane
Brian Seok
Ashwin Srinath

Citation

Please cite as

François Michonneau, Tracy Teal, Auriel Fournier, Brian Seok, Adam Obeng, Aleksandra Natalia Pawlik, … Ye Li. (2019, July 1). datacarpentry/R-ecology-lesson: Data Carpentry: Data Analysis and Visualization in R for Ecologists, June 2019 (Version v2019.06.1). Zenodo. http://doi.org/10.5281/zenodo.3264888

Owner

Name: Toby Hodges
Login: tobyhodges
Kind: user
Location: Heidelberg, Germany
Company: @carpentries

Website: https://tbyhdgs.info
Twitter: tbyhdgs
Repositories: 25
Profile: https://github.com/tobyhodges

Director of Curriculum @carpentries

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/

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")
```


```{r, child="_page_built_on.Rmd"}
```

GitHub Events

Total

Last Year

Committers

Last synced: 8 months ago

All Time

Total Commits: 983
Total Committers: 195
Avg Commits per committer: 5.041
Development Distribution Score (DDS): 0.607

Past Year

Commits: 0
Committers: 0
Avg Commits per committer: 0.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
Francois Michonneau	f**u@g**m	386
Tobias Busch	t**h@g**m	46
Zhian N. Kamvar	z**r@g**m	29
Katrin Leinweber	K**r@t**u	27
Brian Seok	s**k@c**u	27
Adam Obeng	g**b@b**m	25
Tracy Teal	t**l@g**m	19
Mateusz Kuzak	m**k@g**m	15
Edmund Hart	e**t@g**m	14
Katrin Leinweber	9****r	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
Auriel M.V. Fournier	a**r@g**m	9
maneesha sane	8****a	9
Aleksandra Pawlik	a**k@g**m	9
Toby Hodges	t**s@c**g	9
Matthias Grenié	m**e@h**m	8
kathy0305	k**5@h**m	8
Ben Bolker	b**r@g**m	8
Ethan White	e**n@w**g	8
Kari L. Jordan	k**n@m**m	7
chriseshleman	e**s@g**m	7
ashander	a****r	6
Hugo Tavares	h**s@g**m	5
Harriet Dashnow	h**w@g**m	5
Kate Hertweck	k**k@g**m	5
Ruud Steltenpool	g**m@s**m	5
Sergio Martínez Cuesta	s**e@g**m	5
and 165 more...

Committer Domains (Top 20 + Academic)

weecology.org: 3 ufl.edu: 3 ucdavis.edu: 2 wisc.edu: 2 carpentries.org: 2 umich.edu: 2 cam.ac.uk: 2 uw.edu: 2 msu.edu: 2 canada.ca: 1 illinois.edu: 1 geo.uio.no: 1 iimog.org: 1 mac.com: 1 umb.edu: 1 idyll.org: 1 bu.edu: 1 soton.ac.uk: 1 drycafe.net: 1 member.fsf.org: 1 si.edu: 1 colorado.edu: 1 wfu.edu: 1 ncl.ac.uk: 1 slcu.cam.ac.uk: 1 ex.ac.uk: 1 sub.uni-goettingen.de: 1 unm.edu: 1 g.harvard.edu: 1 ucdenver.edu: 1 uchicago.edu: 1 mail.nih.gov: 1 ucsd.edu: 1 jhu.edu: 1 utexas.edu: 1 mcgill.ca: 1 york.ac.uk: 1 email.arizona.edu: 1 calpoly.edu: 1

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Average comments per pull request: 1.0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

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DESCRIPTION cran

RSQLite * imports
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gridExtra * imports
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knitr * imports
patchwork * imports
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tidyverse * imports