R for Transport Applications 26th - 27th April 2018
Early Bird - All others
Early Bird - Students
Early Bird - University staff, public and charitable sector staff
Eleri Pound: firstname.lastname@example.org
This course will provide tools, example code and data and above all face-to-face teaching to empower participants with new software to answer these questions and more. The focus is on the programming language R (we will briefly look at visualising results in QGIS). However, the principles and skills learned will be cross-transferable to other languages. By providing strong foundations in spatial data handling and the use of an up-coming language for statistical computing, R for Transport Applications aims to open a world of possibilities for generating insight from your transport datasets for researchers in the public sector, academia and industry alike.
As with any language, it is important to gain a strong understanding of the underlying syntax and structure before moving on to complex uses. This course therefore starts with the foundations: how R can be used to load, manipulate, process, transform and visualise spatial data.
In terms of content, the first day will focus on how the R language works, general concepts in efficient R programming, and spatial and non-spatial data classes in R. Building on this strong foundation the second day will cover the application of the skills developed in Day 1 to transport datasets, with a focus on geographical transport data.
Is this course for me:
Prior experience with transport datasets or common geographic data formats is essential.
Some exposure to software with a command-line interface, such as Stata, Python or R is highly recommended.
Attendees who are already proficient with their R programming skills are welcome to attend just the second day, although attendance of both days is recommended for most attendees: even advanced R users are likely to learn something on the first day.