Section outline

  • Course Overview

    This course introduces you to techniques and tools for presenting data in visually attractive and interactive ways using the R programming language and RStudio. You will learn how to implement a reproducible, repeatable workflow and produce visualizations for various scenarios. At the end of the course, you will create a report that tells a story from data using appropriate interactive visualizations.

    This course contains a lot of guided activities and there is an expectation that you immerse yourself in the tasks and investigate additional documentation and features of the tools presented.

    Learning Outcomes

    This course will help you to:

    1. Understand the need for interactive visualizations and reports, and the associated workflow
    2. Produce a range of visualizations relevant to the available data
    3. Produce and publish a report that contains appropriate interactive visualizations to tell a story about the data

    • Course Instructors

      • Charlie Hadley

        Charlie Hadley is currently a Research Technology Specialist at the University of Oxford specializing in data visualization. Their background is in biophysics and statistical computing, completing their MPhys at University of Leeds. At University of Oxford, Charlie is helping to launch a data visualization service for researchers and is experienced in teaching data science skills to social scientists.

        View Bio for Charlie Hadley

      • Professor Richard Traunmüller

        Richard Traunmüller is currently a visiting Professor of Quantitative Methods at the University of Mannheim and on leave from his Junior Professorship in Empirical Democracy Research at Goethe University Frankfurt. Prior to coming to Frankfurt, he has held positions at the Universities of Konstanz, Berne, Mannheim, and Essex. Richard has taught semester long courses on data visualization at these universities and has been invited to teach statistical visualization at the German Institute of Global and Area Studies (GIGA) and the European University Institute (EUI) in Florence. In addition, he is a regular instructor for data visualization at the Essex Summer School in Social Science Data Analysis. His work has appeared in major social science journals such as Comparative Political Studies, European Journal of Political Research, and Political Analysis, amongst others.

        View Bio for Professor Richard Traunmüller

      • Course Resources

        You will need to access certain files and resources throughout the course to get the most out of the activities. You can find them all here. 

      • Video Transcripts

        You can access all video transcripts here. 

      • Pre-Course Self Assessment

        Before you dive into this course, spend a few moments reflecting on your familiarity with the topic and your current level of skills confidence. 

        You will then re-visit the same questions in our Post-Course Self Assessment and reflect on how the course has helped you develop in confidence and grow your skills. 

        • Module One: Toolkit

          This module covers:

          1. An overview of interactive visualization, and how to set up the various toolkits you’ll be using throughout the course

        • Module Two: Getting Ready

          This module covers:

          1. Overview of the workflow for putting together an interactive visualization and report
          2. What needs to be considered when planning visualizations and reports
          3. Coverage of defined tidyverse packages to get data ready for visualization, along with a simple exercise
          4. Preparing data using tidyverse and producing a simple bar chart with {plotly}

        • Module Three: Interactive Charts and Maps

          This module covers:

          1. More in-depth look at using {plotly} to make a chart
          2. Making a chart with {highcharter} and comparison to {plotly}
          3. Creating a map with interactive markers
          4. Creating a network chart using tibbles and {visNetwork}

        • Module Four: Shiny Basics and RMarkdown

          This module covers:

          1. Outputting charts in {shiny}
          2. Adding and configuring controls
          3. Controlling when variables update, and publishing your app
          4. Creating the right type of document for your report
          5. Adding charts, code chunks and {shiny} apps
          6. Publishing RMarkdown documents

        • Post-Course Self Assessment

          Now you’ve completed the course, spend a few moments reflecting on where your familiarity with the topics and your confidence skills levels are at now. 

          Has the course helped you develop new skills and grow your confidence?

          You'll need to complete the Post-Course Self Assessment in order to download your certificate. If you didn't do the Pre-Course Self Assessment before starting the course, please go to the top of the page and reflect on your familiarity with the topic and your level of skills confidence before you started the course.

          • Completion: Certificate

            Completing all modules (plus the pre and post-course assessments) will unlock the course certificate, which you can then download here. Your course certificate will only be made available once you have completed all these sections.

            If you have difficulty accessing your certificate, please contact the Sage support team at: onlinesupport@sagepub.co.uk. You can also check out this FAQ page which may be helpful.

            • Give Feedback About This Course

              Did you enjoy the course? Please take two minutes to share your feedback. We use learner feedback in future course updates and developments to provide an excellent learning experience.

            • Accessibility

              We have high standards of accessibility on Sage Campus and as of May/June 2024 all activities within this course are keyboard and screen reader compatible. For more details on accessibility standards, please see the Sage Campus Accessibility Guide.

              For those using assistive technology, please note that within this course:

              • Tab components: JAWS and NVDA behave slightly differently. For NVDA to keep reading, it is best to exit focus mode and go back to browse mode. 
              • Matching: JAWS does not read out question label on dropdown focus.