R provides a flexible environment for statistical analysis, including a number of facilities to manipulate, visualize and analyze spatial information. Here, the emphasis is on visualization. “Mapping in R” concentrates on the use of R for the display of spatial data, especially area lattice data (e.g. states, counties, provinces). You will learn how to handle different map projections, how to incorporate data acquired over the internet, and how to produce publication quality maps. Much of the work involves the use of the instructor’s own GISTools package, and you will review a number of other diverse methods to use R to visually represent geographical information.
Mapping in R
This course will teach you how spatial data may be written/read and visualized in R, and show how publication quality maps may be produced in R, based on the GISTools package, as well as providing a review of a number of other diverse methods for visually representing geographical information in R.
This course will teach you how spatial data may be visualized in R and provides a review of a number of other diverse methods for visually representing geographical information in R.
Students who complete this course will understand the strengths and weaknesses of R as a tool for creating maps. Students will learn how to manipulate spatial objects, how to create legends, scales and labels, and how to map data from the Internet. You will also explore other approaches to mapping using a variety of mapping and graphics tools.
- Appraise the use of R as a tool for creating maps, identifying its strengths and weaknesses
- Read shapefile data into R and visualiuze it with rgdal
- Produce scales, north arrows, labels, legends and coloring schemes
- Map data from the internet
- Use rgeos for basic GIS operations
Who Should Take This Course
Those who have a need to incorporate data with a spatial location into the R environment, appraise the use of packages in R to visualize such data (as opposed to use of a GIS) and to produce publication quality maps of these data, including mashing them onto public domain products such as Google Maps.
Spatial Objects in R
- Types of Spatial Objects
- Getting shapefiles into R
- Map projections and rgdal
Map Components in R
- Scales, North Arrows, Labels
- Colouring schemes
- Can a red/green colorblind person read your map?
Mapping Data from the Internet
- The RgoogleMaps Library
- The Google coordinate system
- Sources of geographical data and APIs
- A live map in a function
- Other approaches to mapping: ggmap
- Incorporating maps in 3d graphics
- Basic GIS operations via rgeos
- Basic map topology with spdep
Nov 22, 2019 to Dec 20, 2019
May 1, 2020 to May 29, 2020
Nov 20, 2020 to Dec 18, 2020
No classes scheduled at this time.
If you are new to R and doubtful about your ability to learn R quickly enough to follow along in the course, we recommend first taking one of the introductory R courses.
Class Start Dates: Jan 10, 2020, May 15, 2020, Sep 11, 2020
Class Start Dates: Mar 13, 2020, Jul 17, 2020, Nov 13, 2020, Mar 12, 2021
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Class Start Dates: Jun 5, 2020, Oct 23, 2020
Additional Course Information
Organization of Course
This course takes place online at The Institute for 4 weeks. During each course week, you participate at times of your own choosing – there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.
At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.
This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.
In this course the homework is a mixture of some simple exercises and consists of guided mapping and visualisation problems using R.
In addition to assigned readings, this course also has supplemental readings available online, and practice exercises.
All required materials will be provided.
Note: If you’re unfamiliar with cartographic concepts, a good and affordable introduction is given in Designing Better Maps: A Guide for GIS Users by Cynthia A. Brewer (ESRI Press, 2005), but it is not required in the course, nor is it referenced in the materials.
You must have a copy of R for the course.
Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?”
Course Fee & Information
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.
Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.
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Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.
Options for Credit and Recognition
This course is eligible for the following credit and recognition options:
You may take this course without pursuing credit or a record of completion.
Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.
CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.
This course is recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam and can help CAP® analysts accrue Professional Development Units to maintain their certification.
There is no supplemental content for this course.
There is no additional information for this course.
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