layout | title | keywords | ||||
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lesson |
Data carpentry -- Starting with R for data analysis |
|
This is a 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.
- Having RStudio installed
- Before we start
- Introduction to R
- Starting with data
- The
data.frame
class - Manipulating data
- Analyzing and Plotting data
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
.
The README.md
file is also generated by the Makefile and is simply a copy of
the index.md
. Only edit index.md
if you want to make changes.
- distributed - the files that were distributed at the workshop
- materials - the original materials that the lessons were built on. It also includes more advanced lessons on functions, loops and plotting that we didn't go through
- ref - R references, including a lesson on reshaped and ggplot (ggplot.pdf)