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March 21, 2016
Sarah Supp
John Blischak
Gavin Simpson
Tracy Teal
Greg Wilson
Diego Barneche
Stephen Turner
Francois Michonneau
Francois Michonneau
Auriel Fournier
Ecology
R for data analysis
R
Teaching

Note

This particular set of lessons has revisions by Karl Broman for a Data Carpentry workshop at UW-Madison on 23-24 August 2016. The official Data Carpentry R-Ecology lessons are at http://www.datacarpentry.org/R-ecology-lesson/.

Data Carpentry {{ page.topic }} for {{ page.domain }}

Data Carpentry's aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with {{page.domain %}} data in {{page.topic %}}.

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.

Content Contributors: {{page.contributors | join: ', ' %}}

Lesson Maintainers: {{page.maintainers | join: ', ' %}}

Lesson status: {{ page.status }}

Lessons:

  1. Introduction to R
  2. Aggregating and analyzing data with dplyr
  3. Data visualization with ggplot2
  4. Reproducible reports with R Markdown
  5. Capstone project

Data

The data for this lesson is available as a single CSV file, http://kbroman.org/datacarp/portal_data_joined.csv.

We'll download the file during the course of the lesson.

Requirements

Data Carpentry's teaching is hands-on, so participants are encouraged to use their own computers to insure the proper setup of tools for an efficient workflow. These lessons assume no prior knowledge of the skills or tools, but working through this lesson requires working copies of the software described below. To most effectively use these materials, please make sure to install everything before working through this lesson.

{% if page.software == "Python" %} {% include pythonSetup.html %} {% elsif page.software == "Spreadsheets" %} {% include spreadsheetSetup.html %} {% elsif page.software == "R" %} {% include rSetup.html %} {% else %} {% include anySetup.html %} {% endif %}

Twitter: @datacarpentry