R: why and for whom?

Author

Marie-Hélène Burle

There are other high level programming languages such as Python or Julia, so when might it make sense for you to turn to R?

Why R?

Here are a number of reasons why you might want to consider using R:

  • Free and open source
  • High-level and easy to learn
  • Large community
  • Very well documented
  • Unequalled number of statistics and modelling packages
  • Integrated package manager
  • Easy connection with fast compiled languages such as C and C++
  • Powerful IDEs (e.g. RStudio, ESS, Jupyter)

For whom?

For whom is R particularly well suited?

  • Fields with heavy statistics, modelling, or Bayesian analysis such as biology, linguistics, economics, or statistics
  • Data science using a lot of tabular data

Downsides of R

Of course, R also has its downsides:

  • Inconsistent syntax full of quirks
  • Slow
  • Large memory usage