I'm so thankful for R, it's community and their great libraries! I've built a eight year (so far) career in data science using R to model data and perform experiments. I love R's functional programming style / dplyr which makes manipulating data a delight. ggplot2 is such a great plotting library, well worth the investment to learn. Then there's all the stats tools like glm, MASS, through brms for advanced Bayesian analysis (https://github.com/paul-buerkner/brms#brms). With R and Python, it's a great time to be a statistician-programmer!
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I'm so thankful for R, it's community and their great libraries! I've built a eight year (so far) career in data science using R to model data and perform experiments. I love R's functional programming style / dplyr which makes manipulating data a delight. ggplot2 is such a great plotting library, well worth the investment to learn. Then there's all the stats tools like glm, MASS, through brms for advanced Bayesian analysis (https://github.com/paul-buerkner/brms#brms). With R and Python, it's a great time to be a statistician-programmer!
I recommend folks looking to start with R check out: https://r4ds.had.co.nz/
There is also ”Advanced R” by Wickham, that goes into more technical details on how the language itself works (and datastructures, etc).
It is also available for free.