Data Visualization

Effective use of visualization techniques requires a combination of skills, including a working knowledge of a programming platform such as Python version 3.x, a strong background in uploading, downloading, and parsing data into data structures; use of files like CSVs and JPEGs, and knowledge of a toolset of libraries for Python. This course creates a framework using open-source tools to outline how to approach different visualization projects. This is a hands-on course with students using Python 3.x at an intermediate level as the driving force behind the visualizations. Knowledge and previous use of Import and the associated requirements to make an Import available to Python is a prerequisite.

The successful data visualization expert can source data, put it into a working model, and visualize the information via thousands of possible plots. This course puts forward a three-step process resulting in a visualization. The process begins with sourcing your data, and you’ll learn several of the most common ways to source or build your own data sets. Once you have the raw data, then we’ll look at how you might plot it out, and what other information you might need, such as timeline data. Finally, with the data sourced and in an appropriate model, you’ll learn how to plot one, two, or more variables in one of the thousands of plot options available.