Thank You, #rstats World

February 17, 2018
By

(This article was first published on R on R(e)Thinking, and kindly contributed to R-bloggers)

Why start another data science blog? Two main reasons. First and foremost, this blog is an effort to contribute back to the amazing #rstats community from which I have benefited so much over the past year. Second, I hope it will also challenge me to tackle new and interesting questions related to my field, experiment, and keep my R skills sharp and up to date.

While I’d known of R for some time (and even used one of its commercial predecessors, S-plus, many moons ago) it was only last year that I became aware of how vibrant, generous, and inclusive the useR community had become. After googling for answers to my R questions and encountering a wealth of resources, I awoke a long-dormant twitter account and began following R torchbearers such as @hadleywickham and @dataandme. From their perch as technical and community leaders, I learnt an immense amount regarding R packages, books, blogs, and gatherings. Their attitude was always very welcoming and generous toward beginners. Soon I started composing documents using knitr, adopted git, and began coding following a tidy workflow. Thank you @jennybc and @xieyihui! I also want to express tremendous gratitude toward the R/Finance folks who have developed powerful tools I use daily, including @eddelbuettel, Jeffrey Ryan, Joshua Ulrich, and Brian Peterson. Sincere apologies to the many other contributors, traced all the way back to the R core group and too numerous to name, I know I’ve left out. Thank you.

This blog will track my progress as I investigate ESG data and experiment with R package and Shiny app development. It is itself an experiment using Yihui’s blogdown following @apreshill’s setup guide. Thank you for reading this far and feel free to reach out.

To leave a comment for the author, please follow the link and comment on their blog: R on R(e)Thinking.

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