Category " Data Visualisation"

Data Visualisation: The Power and Beauty of the Grammar of Graphics

In previous blog posts, we introduced and implemented the Grammar of Graphics plotting concept. Here, we want to show how implementing this framework in R allows for the efficient, flexible and transparent production of reproducible plots that effectively communicate key messages.  This data set comes from Lenka Forkelova, a student of one of our Data Visualisation workshops held at the Max Planck...


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Implementing the Grammar of Graphics

This is the second part of a three-part Grammar of Graphics series (See part one). In this post, I want to explore how data can be represented in different ways. It is only when we take advantage of a plot's grammer that we can being communicating results and uncovering interesting trends.   Case Study: Representing the Wage Gap During my talk at re:publica 14, I presented a case study...


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Introducing the Grammar of Graphics Plotting Concept

In my recent talk at re:publica 14 in Berlin, I introduced the audience to the Grammar of Graphics((For a comprehensive introduction see Leland Wilkinson's The Grammar of Graphics, 2nd Ed.)) plotting concept. This concept is implemented in the second day of our Data Visualisation workshop. So, what do we mean by the Grammar of Graphics? In a series of three posts, I will introduce the plotting...


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Why Use R? R’s 3 Core Strengths: Simplicity, Power, Flexibility

In my experience, most biologists justify their continued use of Microsoft Excel with the excuse "better the devil you know". It doesn't have to be that way! R is a statistical programming environment that is not only extremely powerful and highly flexible but is also surprisingly easy to use. In this post, I'd like to introduce the absolute beginner to some of the core strengths of R that set it apart...


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