/R_workshop_intermediate

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Improve your R workflow with dplyr and broom

Paul Paczuski [AMA!]

Quick Start

R is a fantastic tool for data analysis, and you can take it to the next level by learning the pipe %>% operator and using the packages dplyr, tidyr, ggplot2, and broom.

This workshop will present code examples and key concepts to help you quickly get started with these packages.

See the numbered R markdown files for workshop content, including exercises.

The sample dataset (/data) is a subset of the CMS data found and documented here.

Set-up

  1. Install R (optionally RStudio), and these packages: dplyr, tidyr, ggplot2, and broom [see Installing the R environment below]

  2. Download this repository (see green button "Clone or download", then click "Download Zip" link). Unzip the file to a convenient location on your computer. We will be working with its contents.

  3. Open file test-me.R and set up your working directory to make sure it runs and gives correct results.

Installing the R environment

Below are instructions to install R, a few packages, as well as RStudio, which we will be using during the workshop.

  1. Install R

    Mac OS X
    download and install from:
    http://cran.r-project.org/bin/macosx/ [click R-3.2.0.pkg on left]

    Windows
    download and install from:
    http://cran.r-project.org/bin/windows/base/

    Linux, etc
    See top of:
    http://cran.us.r-project.org

  2. Installing R packages:

    a) MAC OS X and Linux:

    • Open R (not RStudio for this step)
    • In Menu, go to “Packages and Data” - > “Package Installer”
    • Search for and install the above two packages (may need to choose a “mirror” - click on something in the USA) as follows:
    • Type in the name of one package, click “get list”, check “Install Dependencies” and then “Install Selected”
    • Do the same for the other package

    b) Windows:

    • Open R (not RStudio for this step)
    • In Menu, go to "Packages" -> "Install package(s)..." and select each of the packages at top to install.

  3. Install RStudio (a great interface for using R)

    Install for your appropriate system from the list at: http://www.rstudio.com/products/rstudio/download/

R Resources

Data Wrangling handout
http://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf

Other R handouts:
https://www.rstudio.com/resources/cheatsheets/

Stack Overflow documentation!
http://stackoverflow.com/documentation/r/topics

An Introduction to Statistical Learning with Applications in R, by James et al:
http://www-bcf.usc.edu/~gareth/ISL/

R Cookbook
http://cookbook-r.com

Quick-R
http://www.statmethods.net