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Programming with data

Jan 07, 2020, Location TBD

Haley Jeppson, hjeppson@iastate.edu.
Sam Tyner, sctyner@iastate.edu.
Heike Hofmann, hofmann@iastate.edu.

In Programming with data you get a head start with the statistical software R. R has gained a huge number of users in the last years and the number of methods from add-on packages is growing rapidly. The course will be data centric, with lots of different data sets that illustrate examples of the different techniques used for different problems.

The course will be a mix of instruction and follow-up exercises. It will be held in a computer lab but you are encouraged to bring your own laptops, with software already loaded. A list of software is available to help you prepare your machine for the workshop.

Lectures and timetable

Date	Notes	Lecture and Resources
9:00 – 9:15	Setting Up	This will make sure that everybody's system is up and running. You should try to install R ahead of time, so that this time can be used to address potential problems. 1-Setup.R 1-Setup.Rmd
9:15 – 10:15	Motivating Example	First taste of R: Jumping right into it to get an idea of how to use R and what it is capable of. 2-MotivatingExample.R 2-MotivatingExample.Rmd tips.csv
10:15 – 11:15	Basics	Working with data and learning about vectors, indexing vectors, and additional statistical functions. 3-Basics.R 3-Basics.Rmd R Reference Card
11:15 – 11:45	Break
11:45 – 12:45	Data Structures	Using and examining the other data structures that are available in R. 4-DataStructures.R 4-DataStructures.Rmd
12:45 – 1:45	Lunch Break
1:45 – 2:45	Packages and Basic Programming	Introduction to packages and finding useful packages. We will also cover simple programming constructs to make your life easier with R. 5-PackagesProgramming.R 5-PackagesProgramming.Rmd
2:45 – 3:00	Break
3:00 – 4:00	Working with Regular Expressions	Learn about using regular expressions for parsing data 6-RegularExpressions.Rmd

Learning outcomes

After the end of the this one course, we expect you to be able to do the following:

• Use R for scientific/statistical calculations
• Be able to create or read in data and have the ability to manipulate the data accordingly
• Have the ability to explore data set characteristics and calculate summary statistics for real data sets
• Use the help functionality to find the functions you need to do what you want to do
• Install, use, and search for helpful external packages
• How to use basic programming constructs to make working with data easier
• Create documents that contain your R code/output/results and convert between HTML/pdf/Word at the click of a button.

Getting Ready on your own machine

You can bring your own laptop and work on it, if you like to. In order to keep up with everybody else, we're asking that you start installing the following pieces of software ahead of coming to the workshop:

• Install the newest R version (3.2.x) (from www.r-project.org)
• It is recommended that you install the latest version of RStudio (from www.rstudio.org)

Useful links

Recommended Reading:

• Introduction to R, by Andreas Buja. The whole introduction is written in R, so you can run through it and experiment. Before running each line I recommend you predict what output you will get. This will help you learn faster
• R for ecologists, yes, even though you might not be an ecologists, this is still good

This work is licensed under a Creative Commons Attribution 3.0 Unported License.