cm002 2017-09-07 Thursday overview

Since last time:

  • you should at least have R and RStudio installed.


To do before next class:

  • Please fill out this survey.
  • R/RStudio novices: finish today’s activity
  • Finish getting your git and GitHub setup done.
  • Optional: check out swirl – it offers mini walk-through courses in R.

Resources for effective programming and data analytic work:

Optional resources: python

python is another very effective programming language for data analysis. We won’t cover this language in class, but in case you’d like to get a feel for the language, here are some resources.

  1. I recommend installing anaconda as a means for programming in python through Jupyter Notebooks. By the way – you can program in both R and python in a Jupyter Notebook!
  2. Take a look at the Think Python book. These chapters are particularly relevant for today’s class:
  3. The Python documentation is also useful. The following are relevant for today’s class: