All posts (Page 96 of 127)
We have started working on a new rOpenSci package called writexl. This package wraps the very powerful libxlsxwriter library which allows for exporting data to Microsoft Excel format.
The major benefit of writexl over other packages is that it is completely written in C and has absolutely zero dependencies. No Java, Perl or Rtools are required.
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Getting Started
The write_xlsx function writes a data frame to an xlsx file. You can test that data roundtrips properly by reading it back using the readxl package. Columns containing dates and factors get automatically coerced to character strings.
It all started January 26th this year when I signed up to volunteer as a reviewer for R packages submitted to rOpenSci. My main motivation for wanting to volunteer was to learn something new and to contribute to the R open source community. If you are wondering why the people behind rOpenSci are doing this, you can read How rOpenSci uses Code Review to Promote Reproducible Science.
Three months later I was contacted by Maëlle Salmon asking whether I was interested in
reviewing the R package patentsview for rOpenSci. And yes, I
was! To be honest I was a little bit thrilled.
The new rOpenSci spelling package provides utilities for spell checking common document formats including latex, markdown, manual pages, and DESCRIPTION files. It also includes tools especially for package authors to automate spell checking of R documentation and vignettes.
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Spell Checking Packages
The main purpose of this package is to quickly find spelling errors in R packages. The spell_check_package() function extracts all text from your package manual pages and vignettes, compares it against a language (e.g. en_US or en_GB), and lists potential errors in a nice tidy format:
At rOpenSci, we create and curate software to help scientists with the data life cycle. These tools access, download, manage, and archive scientific data in open, reproducible ways. Early on, we realized this could only be a community effort. The variety of scientific data and workflows could only be tackled by drawing on contributions of scientists with field-specific expertise.
With the community approach came challenges. How could we ensure the quality of code written by scientists without formal training in software development practices? How could we drive adoption of best practices among our contributors? How could we create a community that would support each other in this work?
...Are you thinking about submitting a package to rOpenSci’s open peer software review? Considering volunteering to review for the first time? Maybe you’re an experienced package author or reviewer and have ideas about how we can improve.
Join our Community Call on Wednesday, September 13th. We want to get your feedback and we’d love to answer your questions!
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Agenda
- Welcome (Stefanie Butland, rOpenSci Community Manager, 5 min)
- guest: Noam Ross, editor (15 min) Noam will give an overview of the rOpenSci software review and onboarding, highlighting the role editors play and how decisions are made about policies and changes to the process.
- guest: Andee Kaplan, reviewer (15 min) Andee will give her perspective as a package reviewer, sharing specifics about her workflow and her motivation for doing this.
- Q & A (25 min, moderated by Noam Ross)
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Speaker bios
Andee Kaplan is a Postdoctoral Fellow at Duke University. She is a recent PhD graduate from the Iowa State University Department of Statistics, where she learned a lot about R and reproducibility by developing a class on data stewardship for Agronomists. Andee has reviewed multiple (two!) packages for rOpenSci, iheatmapr and getlandsat, and hopes to one day be on the receiving end of the review process.
