A dataset consisting of 2-D plots with various types, styles, and complexities can be useful studying the application of generative adversarial networks (GAN) on various tasks such as image generation and style transfer. In order to generate such a dataset, plotting APIs based on ggplot2 and MATLAB were created, along with a data generation tool used to produce the underlying datasets of the plots. Using the created tools, a 30-class plot image dataset consisting of 30,000 images was created. In addition, a conditional GAN was implemented to generate synthetic examples of plots.