Among data scientists and analysts, R has long held its own against Python in the battle to determine the “best” analytical programming language. Statisticians and numerically-savvy academics of all stripes have typically preferred R to Python, so lots of R&D—both inside the ivory tower and in various industries— gets done in R.
Part of R's popularity comes from its dizzying array of packages, contributed by a lively community of developers. As of January 2017, there were 10,000 R packages available for download, a milestone that testifies to its wide-spread adoption across lots of different industries.
Still, for all its flexibility, R remains true to its roots as a statistical programming language. Stack Overflow's 2017 survey found that while R is growing in every industry surveyed, it's growing fastest in sectors that lean heavily on statistics: academia, healthcare, and government.
Whether you're new to the R for data science community, or you're already an active package-creator or analyst, listening in on conversations among influencers is great way to stay up to speed and find the most relevant news about R for data science.
On the heels of releasing support for R in Mode's integrated Notebooks, we've compiled a list of the people we follow most closely in the R data science community. If you want to stay in the know, here are 7 people you should follow on Twitter.
- Hadley Wickham. Author of R for Data Science (with Garrett Grolemund), chief scientist at RStudio, and author of the tidyverse packages, including ggplot2, plyr, dplyr, and reshape2.
Follow Hadley: @hadleywickham
- Mara Averick. Tidyverse developer advocate at RStudio. Open source contributor and civic tech advocate.
Follow Mara: @dataandme
- Roger Peng. Professor at Johns Hopkins Department of Biostatistics. Author of R Programming for Data Science. Co-editor of Simply Statistics. Co-host of the podcast The Effort Report (with Elizabeth Matsui).
Follow Roger: @rdpeng
Follow Hilary: @hspter
Follow Gabriela: @gdequeiroz
- David Robinson. Chief data scientist at DataCamp. Co-author of tidytext and Text Mining with R. Author of the broom, gganimate, and fuzzyjoin packages, and Introduction to Empirical Bayes.
Follow David: @drob
- Julia Silge. Data science and visualization at StackOverflow, co-author of tidytext and Text Mining with R.
Follow Julia: [**@juliasilge**](https://twitter.com/juliasilge) *** Are there R data science influencers you think we should add to this list? We'd love to hear who you follow! Tweet at us [@ModeAnalytics](https://twitter.com/ModeAnalytics). Or, reach out on the [Mode forum](https://forum.modeanalytics.com/), where you can talk to other analysts and data scientists and compare notes.
Check out my new @DataCamp course on practical supervised machine learning with #rstats! In four case studies, 💪 exercise your skills from 📊 exploratory data analysis to ⚖️ model evaluation.https://t.co/dvcpSqAZBy pic.twitter.com/8FB5a0NCmF— Julia Silge (@juliasilge) April 23, 2018