Data Visualization

Catalog description

Investigates the processing and cleaning of real-world datasets and their appropriate representation in visual form. Data resides in a multitude of databases and formats and comes in a variety of forms such as structured, semi-structured, and unstructured. Making data understandable to non-technical users requires knowledge of the best techniques for presenting data to aid in its interpretation. This course focuses on the use of data visualization coding techniques in software applications such as TableauT, Python, and R. Students discover how to create bar charts, line charts, dual axis plots, histograms, trellis charts, pie charts, donut charts, nested pie charts, bump charts, heatmaps, spider plots, maps, and more. <i>Prior programming experience is recommended. DS/IMC</i>