Level: Intermediate (I)
This virtual course will run over 2 afternoons. As spatial datasets get larger and more sophisticated software needs to be harnessed for their analysis. R is now a widely used open source software platform for working with spatial data thanks to its powerful analysis and visualisation packages.
Please note: Bookings will close 4 working days before the course start date or when the course has reached its maximum capacity.
This course has the Society's Quality Mark so can be used as part of your application for professional membership including Data Analyst.
Level: Intermediate (I)
As spatial datasets get larger and more sophisticated software needs to be harnessed for their analysis. R is now a widely used open source software platform for working with spatial data thanks to its powerful analysis and visualisation packages.
This training course provides an introduction to sf, a popular package for handling geographic data in R. Participants will learn how to load, manipulate and visualise geographic vector data, creating both static and interactive maps. The focus is on the principles rather than the specific methods, providing participants with the understanding needed to apply R's powerful suite of geographical tools to their own problems.
Topics Covered
- Introducing R as a GIS
- The structure of spatial objects in R
- Loading and interrogating spatial data
- Visualisaing spatial datasets with tmap
- Data manipulation with spatial data using dplyr
- Spatial operations such as intersections
- Interactive maps with leaflet
Target Audience
Participants with spatial data problems who are not making use of R and are falling behind in the ever changing world of data science.
Assumed Knowledge
A basic understanding of the R software is assumed.
For this online course, participants are not required to have R installed on their own laptops. A virtual environment, which can be accessed through a web browser, will be used to run R and view course materials.
Dr. Nicola Rennie
Nicola has a PhD in Statistics and Operational Research, with a focus on outlier detection in functional data. She enjoys sharing her knowledge of R, creating data visualisations, working closely with clients to help them get the most from their data.
Fees
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Registration before
17 April 2023
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Registration on/after
17 Aprl 2023
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Non Member
RSS Fellow
RSS CStat/Gradstat/Data Analyst
also MIS & FIS
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£419.83+vat
£355.57+vat
£336.29+vat
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£465.89+vat
£396.27+vat
£373.78+vat
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Group discounts are also available*:
3-5 people
6-8 people
9+ people
*Discount only applies to non-member price
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10% discount
15% discount
20% discount
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