Visualization in R

BAN422 Visualization in R

Spring 2020

  • Topics

    Visualization is one of the key strengths of R. However, visualization involves many choices, and R offers such a wide range of choices that guidance is desirable. There are two major underlying technologies, base graphics and grid graphics, and several toolboxes built on these (trellis graphics and grammar of graphics on grid graphics). In addition, much work has been done on the effective use of shapes and colours.

  • Learning outcome


     On successful completion, the student will be able to:

    • understand the principles underlying base and grid graphics
    • understand how toolkits build on grid graphics are structured
    • understand the choices involved in the effective use of colours and glyphs
    • understand the motivations underlying the choices made in visualization in R programming
    • use this understanding in customising graphical outputs



     On successful completion, the student will be able to:

    • assign correct descriptions to visualization techniques used in scripts and functions encountered in simple workflows
    • define new visualization templates for workflow output


    General competence

     On successful completion, the student will be able to:

    • handle the graphical output of R functions with greater confidence
    • customise the graphical output of R functions to meet specific needs

  • Teaching

    This course combines lectures and programming tutorials. Lectures focus on methodological issues. In programming tutorials, the student will implement the learned methodologies using R.

  • Recommended prerequisites

    Programming skills with R are helpful and expected, best at the level  of BAN420

  • Credit reduction due to overlap

    Course identical to BUS464.

  • Requirements for course approval

    A group project, with a presentation during the course (conditional on participant numbers).

    Course approval from BUS464 is valid for BAN422.

  • Assessment

    Group term paper, based on the group project (conditional on participant numbers). 

    The group written term paper is due two weeks after course ends. The term paper must be written in English.

    This course is a continuation of BUS464 and the total number of attempts applies to the course (not the course code).

  • Grading Scale


  • Computer tools

    R ( and RStudio ( and contributed packages packages as needed.

  • Literature

    Unwin, A. (2015) Graphical Data Analysis with R. Boca Raton, FL: CRC Press.

    Murrell, P. (2011) R Graphics. Boca Raton, FL: CRC Press.

    Sarkar, D. (2008) Lattice: Multivariate Data Visualization with R. New York: Springer.

    Wickham, H. (2016) ggplot2: Elegant Graphics for Data Analysis. New York: Springer.

    Wilke, C. (2019) Fundamentals of Data Visualization ( Sebastopol, CA: O'Reilly Media


ECTS Credits
Teaching language

Spring. First week of spring semester. Offered spring 2020.

Course responsible

Professor Roger Bivand, Department of Economics