all short courses

Data manipulation and visualisation with R

Biology Department, University of Missouri, St Louis, MO. October 2009

Introduction to ggplot2.

How to create scatterplots, and how to add extra variables with aesthetics (like colour, shape and size) or facetting. Data: fuel economy of US cars.

Graphics for large data.

Histograms and bar charts for displaying distributional summaries. Boxplots. Other techniques for overcoming overplotting when drawing scatterplots of large datasets. Data: prices and characteristics of 50,000 diamonds.

Transformations.

Group-wise summaries and transformations to add extra information to your plots. How to visualise time series. Data: trends in US baby names over the last 120 years.

Polishing plots for publication.

Tweaking your plots for maximum presentation impact. Introduction to colour theory. Labels, legends and axes. Tweaking the plot themes.

Subsetting & structure

    Overview of the main types of subsetting, and main data structures of R.