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Package Development

Resources tagged Package Development#

Athanasia M. Mowinckel | Make a package - Make some friends | RStudio

Athanasia M. Mowinckel | Make a package - Make some friends | RStudio

In 2017, I had never exposed my code to anyone other than a select few before, and I was terrified. I had some functions made from a colleagues script that I thought might be useful for others, and dared myself to make a package and push it to github. In stead of the dreaded ridiculing of poor code and development, people embraced the package and helped us make it better. Within just a couple of days, pull requests came from others to help us improve the code, implement tests, and improve documentation. I learned so much just by looking through the PRs and seeing how others worked. Rather than make me shy off development, the R neuro community's positive feedback has helped me find a new interest and joy in developing tools. About Athanasia: Athanasia M. Mowinckel is a staff scientist at the Center for Lifespan Changes in Brain and Cognition, at the University of Oslo. She has a background on cognitive psychology, and uses R for almost everything. She goes by the nickname "Mo" (closer to 'Mou' than 'Moe'), and is a member of the R-Ladies Global team

Feb 20, 2021

5 min

rstudio RStudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Dplyr Ggplot2 Tibble Readr Stringr Tidyr Purrr Github Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education Forcats Rstats Open Source Oss Reticulate Athanasia M. Mowinckel Package Development

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Alex Cookson | The Power of Great Datasets | RStudio

Alex Cookson | The Power of Great Datasets | RStudio

There are a few classic datasets, like mtcars, nycflights, or Titanic passengers. They're okay, but they leave something to be desired for folks learning R: they're kind of boring. There's a big difference between "Okay Datasets" and "Great Datasets". Great Datasets prompt you to exclaim, "That's so cool!" They get your blood pumping and mind racing with questions you want answered. They give tremendous motivation to answer those questions. And in answering those questions, you'll probably learn some R. I want you to curate Great Datasets. You'll contribute to the richness of our community, you'll learn some R yourself, and you'll feel fantastic when someone finds your Great Dataset and exclaims, "That's so cool!" About Alex: Alex Cookson helps the Customer Intelligence team at the Royal Canadian Mint make the most of their data. When he's not working on A/B testing, recommendation engines, or exploratory data analysis at the Mint, he can be found participating in Tidy Tuesday or thinking up cool datasets to explore. And when he's not doing that, he's probably cycling around Toronto or doting on his two cats, Tom Tom and Ruby

Feb 20, 2021

5 min

rstudio RStudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Ggplot2 Tibble Readr Stringr Tidyr Purrr Github Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education Forcats Rstats Open Source Oss Reticulate Package Development Alex Cookson

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Malcolm Barrett | You're Already Ready: Zen and the Art of R Package Development | RStudio

Malcolm Barrett | You're Already Ready: Zen and the Art of R Package Development | RStudio

R packages make it easier to write robust, reproducible code, and modern tools in R development like usethis make it easy to work with packages. When you write R packages, you also unlock a whole ecosystem of tools that will make it easier to test, document, and share your code. Despite these benefits, many believe package development is too advanced for them or that they have nothing to offer. A fundamental belief in Zen is that you are already complete, that you already have everything you need. I’ll talk about why your project is already an R package, why you’re already an R package developer, and why you already have the skills to walk the path of development. About Malcolm: Malcolm Barrett is Clinical Research Data Scientist at Teladoc Health, an epidemiologist, and an R developer. He is also an organizer for the Los Angeles R Users Group. Malcolm is the author of several R packages, including ggdag and precisely. Previousy, he was an intern at RStudio and spent two years of service in AmeriCorps. In 2013 and 2014, while serving in AmeriCorps, Malcolm lived in the Zen Center of New York City, where he is still a student

Feb 19, 2021

15 min

rstudio usethis RStudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Ggplot2 Tibble Readr Stringr Tidyr Purrr Github Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education Forcats Rstats Open Source Oss Reticulate Malcolm Barrett Package Development