---
layout: lesson
title: Data carpentry: R for data analysis and visualization of Ecological Data
keywords: ["R", "subset", "data.frame", "read.csv", "dplyr", "ggplot2"]
---
This is an introduction to R designed for participants with no programming experience. These lessons can be taught in 3/4 of a day (6 hours). They start with some basic information about syntax for the R programming language, the RStudio interface, and move through to specific programming tasks, such as importing CSV files, the structure of data frame objects in R, dealing with categorical variables (i.e. factors), basic data manipulation (adding/removing rows and columns), and finishing with calculating summary statistics and a brief introduction to plotting.
- Having R and RStudio installed (though see the first lesson, Before we start for installation instructions)
- Before we start
- Introduction to R
- Starting with data
- Aggregating and analyzing data with dplyr
- Data visualization with ggplot2
- R and Databases
The lessons are written in Rmarkdown format. A Makefile generates the corresponding html page for each lesson using the rmarkdown package from within R.
The Makefile also generates a "code handout" file (code-handout.R) 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. Participants can
also copy and paste from this file to avoids typos for more complex
examples. Each lesson generates a code handout file, and the files produced are
then concatenated to create a single file (the intermediate files are
deleted). To be included in the code handout file, a code chunk in the Rmarkdown
lesson file needs to have the arguments purl=TRUE.
If you would like to contribute to the content and development of these lessons, we encourage you to review our contributing guide.