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One of rOpenSci’s aims is to build capacity of software users and developers and foster a sense of pride in their work. What better way to do that than to encourage you to participate in Hacktoberfest, a month-long celebration of open source software!
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It doesn’t take much to get involved
Beginners to experts. Contributors and package maintainers welcome. You can get involved by applying the label Hacktoberfest to issues in your rOpenSci repo (or any project) that are ready for contributors to work on. You can find already-labelled rOpenSci and ropenscilabs issues here. A contribution can be anything - fixing typos, improving documentation, writing tests, fixing bugs, or creating new features. Who better to improve a vignette than the person who’s using the package?!
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What is rrricanes
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Why Write rrricanes?
There is a tremendous amount of weather data available on the internet. Much of it is in raw format and not very easy to obtain. Hurricane data is no different. When one thinks of this data they may be inclined to think it is a bunch of map coordinates with some wind values and not much else. A deeper look will reveal structural and forecast data. An even deeper look will find millions of data points from hurricane reconnaissance, computer forecast models, ship and buoy observations, satellite and radar imagery, …
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Why care about patents?
1. Patents play a critical role in incentivizing innovation, without which we wouldn’t have much of the technology we rely on everyday
What does your iPhone, Google’s PageRank algorithm, and a butter substitute called Smart Balance all have in common?
The R package ecosystem now contains more than 10K packages, and several flagship packages belong under the rOpenSci suite. Some of these are: magick for image manipulation, plotly for interactive plots, and git2r for interacting with git.
rOpenSci is a community of people making software to facilitate open and reproducible science/research. While the rOpenSci team continues to develop and maintain core infrastructure packages, an increasing number of packages in our suite are contributed by members of the extended R community.
...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.
Working together to push science forward
Happy rOpenSci users can be found at
