Andrews' curves are a way of visualizing high-dimensional data. Each observation is projected onto a set of orthogonal trigonometric functions and displayed as a curve. It is known that Andrews' curves preserve distances, so they have many uses for data analysis and exploration. However, they are not very useful when working with large data sets because of over plotting. In this talk, I present an alternative visualization methodology suitable for Andrews' curves that is based on a technique sometimes known as data images. This new visualization methodology is most useful when the size of the data set is large. I first describe the data sets that are used to illustrate the concepts. I then present some background information on Andrews' curves, as well as data images. Finally, I provide examples and show how this technique can be used to explore the data sets.