Event Date
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
TIME ZONE – UTC+2 – however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional 1/2 days support after the official course finish date (please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).
The aim of the course is to introduce you to a spatial data processing, analysis, and visualization capabilities of the R programming language. It will teach a range of techniques using a mixture of lectures, computer exercises and case studies.
By the end of the course participants should:
Academics and post-graduate students working on projects related to spatial data and want access to a powerful (geo)statistical and visualization programming language.
Applied researchers and analysts in public, private or third-sector organizations who need the reproducibility, speed and flexibility of a command-line language such as R.
The course is designed for intermediate-to-advanced R users interested in spatial data analysis and R beginners who have prior experience with geographic data.
Delivered remotely
Venue – Delivered remotely
Time zone – Poland local time (UTC+2)
Availability – 20 places
Duration – 4 days
Contact hours – Approx. 27 hours
ECT’s – Equal to 2 ECT’s
Language – English
The course will be a mixture of theoretical and practical. Each concept will be first described and explained, and next there will be a time to exercise the topics using provided data sets. Participants are also very welcome to bring their own data.
The course is designed for intermediate-to-advanced R users interested in spatial data analysis and R beginners who have prior experience with geographic data.
Attendees should already have experience with R and be able to read csv files, create simple plots, and manipulate data frames.
However, if you do not have R experience but already use GIS software and have a strong understanding of geographic data types, and some programming experience, the course may also be appropriate for you.
A laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs, Macs, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/.
All the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed, and a full list of required packages will be made available to all attendees prior to the course.
A working webcam is desirable for enhanced interactivity during the live sessions, we encourage attendees to keep their cameras on during live zoom sessions.
Although not strictly required, using a large monitor or preferably even a second monitor will improve he learning experience
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
Classes from 09:00 – 17:00
Introduction to the course
Key concepts related to spatial data
R’s spatial ecosystem
Reading data from spatial file formats
Understanding R’s spatial classes
Creating static and interactive maps:
Customizing maps
Making facet maps
Classes from 09:00 – 17:00
Attribute data operations:
Vector attribute subsetting, aggregation and joining
Creating new vector attributes
Raster subsetting
Summarizing raster objects
Spatial data operations:
Spatial subsetting
Classes from 09:00 – 17:00
Attribute data operations:
Vector attribute subsetting, aggregation and joining
Creating new vector attributes
Raster subsetting
Summarizing raster objects
Spatial data operations:
Spatial subsetting
Classes from 09:00 – 17:00
Attribute data operations:
Vector attribute subsetting, aggregation and joining
Creating new vector attributes
Raster subsetting
Summarizing raster objects
Spatial data operations:
Spatial subsetting
Works at: Adam Mickiewicz University