Mapping in R

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.

$799 | Enroll Now
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Overview

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.

Intermediate Level Course
4-Week Course
100% Online Courses
CAP Credit Eligible
Expert Instructors
Teacher Assistant Support
Tution-Back Guarantee

Learning Outcomes

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.

Instructors

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Prof. Chris Brunsdon

Prof. Chris Brunsdon

Prof. Chris Brunsdon is currently Professor of Geocomputation, and Director of the National Centre for Geocomputation, at the National University of Ireland, Maynooth, having taken up the position in January 2014. The National Centre for Geocomputation is the principal centre for geocomputation and spatial analyses in Ireland, combining a strong focus on fundamental research and partnerships with industry

See Instructor Bio

Course Syllabus

Week 1

Spatial Objects in R

  • Types of Spatial Objects
  • Getting shapefiles into R
  • Attributes
  • Map projections and rgdal

Week 2

Map Components in R

  • Legends
  • Scales, North Arrows, Labels
  • Colouring schemes
  • Can a red/green colorblind person read your map?

Week 3

Mapping Data from the Internet

  • The RgoogleMaps Library
  • The Google coordinate system
  • Sources of geographical data and APIs
  • A live map in a function

Week 4

Further Topics

  • Other approaches to mapping: ggmap
  • Incorporating maps in 3d graphics
  • Basic GIS operations via rgeos
  • Basic map topology with spdep

Class Dates

2023

Jun 2, 2023 to Jun 30, 2023

2024

Jun 7, 2024 to Jul 5, 2024

2025

No classes scheduled at this time.

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Prerequisites

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.

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R Programming - Introduction Part 1

Introduction to R Programming

This course provides an easy introduction to programming in R.
Topic: Data Science, Using R | Skill: Introductory | Credit Options: ACE, CAP, CEU
Class Start Dates: May 12, 2023, Sep 8, 2023, Jan 12, 2024
Mapping in R Course

R Programming – Introduction Part 2

This course is a continuation of the introduction to R programming.
Topic: Data Science, Using R | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jul 7, 2023, Nov 10, 2023, Mar 8, 2024

What Our Students Say​

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Left Square Qoute

This course definitely adds another dimension to my map visualization capabilities other than just relying on QGIS.

Eugene Chua
Right Square Qoute
Left Square Qoute

This was an awesome course! I learned so much about mapping. This is a fascinating topic and I wish you had a specialty just on that!

Erin Hodgess
University of Houston-Downtown
Right Square Qoute

Frequently Asked Questions

What is your satisfaction guarantee and how does it work?

We offer a “Student Satisfaction Guarantee​” that includes a tuition-back guarantee, so go ahead and take our courses risk free. That’s our commitment to student satisfaction. Students may cancel, transfer, or withdraw from a course under certain conditions. If you’re not satisfied with a course, you may withdraw from the course and receive a tuition refund.

Please see our knowledge center for more information.

Who are the instructors at the Institute?

The Institute has more than 60 instructors who are recruited based on their expertise in various areas in statistics. Our faculty members are:

  • Authors of well-regarded texts in their area;
  • Advisory board members;
  • Senior faculty; and
  • Educators who have made important contributions to the field of statistics or online education in statistics.

The majority of our instructors have more than five years of teaching experience online at the Institute.

Please visit our faculty page for more information on each instructor at The Institute for Statistics Education.

Please see our knowledge center for more information.

What type of courses does the Institute offer?

The Institute offers approximately 80 courses each year. Topics include basic survey courses for novices, a full sequence of introductory statistics courses, bridge courses to more advanced topics. Our courses cover a range of topics including biostatistics, research statistics, data mining, business analytics, survey statistics, and environmental statistics.

Please see our course search or knowledge center for more information.

Do your courses have for-credit options?

Our courses have several for-credit options:

  • Continuing education units (CEU)
  • College credit through The American Council on Education (ACE CREDIT)
  • Course credits that are transferable to the INFORMS Certified Analytics Professional (CAP®)

Please see our knowledge center for more information.

Is the Institute for Statistics Education certified?

The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV). For more information visit: https://www.schev.edu/

Please see our knowledge center for more information.

Visit our knowledge base and learn more.

FAQs + Knowledge Base

Related Courses

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Spatial Statistics for GIS Using R

Spatial Statistics for GIS Using R

This course will teach you spatial statistical analysis methods to address problems in which spatial location. This course will explain and give examples of the analysis that can be conducted in a geographic information system such as ArcGIS or Mapinfo.
Topic: Statistics, Analytics, Data Exploration, Statistical Modeling, Using R | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jul 7, 2023, Jan 12, 2024, Jul 12, 2024

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.

Time Requirements

This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.

Homework

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.

Course Text

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.

Software

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

Enrollment
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.

Group Rates
Contact us to get information on group rates.

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout.

New to Statistics.com?  Click here for a special introductory discount code.  

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:

No Credit
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.

INFORMS-CAP
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.

Supplemental Information

Literacy, Accessibility, and Dyslexia

At Statistics.com, we aim to provide a learning environment suitable for everyone. To help you get the most out of your learning experience, we have researched and tested several assistance tools. For students with dyslexia, colorblindness, or reading difficulties, we recommend the following web browser add-ons and extensions:

 

Chrome

 

Firefox

 

Safari

  • Navidys (for colorblindness, dyslexia, and reading difficulties)
  • HelperBird for Safari (for colorblindness, dyslexia, and reading difficulties)

Miscellaneous

There is no additional information for this course.

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Mapping in R
$799 | Enroll Now
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