layout: lesson title: Data carpentry -- Starting with R for data analysis keywords: ["R", "subset", "data.frame", "read.csv"]

This is an introduction to R designed for participants with no programming experience. These lessons can be taught in 3/4 of a day. They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data.frame, how to deal with factors, how to add/remove rows and columns, and finish with how to calculate summary statistics for each level and a very brief introduction to plotting.

(This particular set of lessons has revisions by Karl Broman for a Data Carpentry workshop at UW-Madison on 1-2 June 2016; further revised for 23 Aug 2016 and 10 Jan 2017.)

Prerequisites

• Having RStudio installed

Topics

• Before we start
• Introduction to R
• Starting with data
• The data.frame class
• Aggregating and analyzing data with dplyr

Other resources

• Motivation

Organization of the repository

The lessons are written in Rmarkdown. A Makefile generates an html page for each topic using knitr. In the process, knitr creates an intermediate markdown file. These are removed by the Makefile to avoid clutter.

The Makefile also generates a "skeleton" file that is intended to be distributed to the participants. This file includes some of the examples used during teaching and the titles of the section. It provides a guide that the participants can fill in as the lesson progresses. It also avoids typos while typing more complex examples. Each topic generates a skeleton file, and the files produced are then concatenated to create a single file and the intermediate files are deleted. To be included in the skeleton file, a chunk of code needs to have the arguments purl=TRUE.