Suggested Prerequisites
- Have a basic understanding of how data visualization works.
- Be familiar with why different kinds of plot types are used.
- Have some knowledge of univariate, bivariate, and multivariate statistics.
- Know this is not a coding course and will not teach how each graph is recreated.
Data visualization is a critical component of data analysis and data science. In this course, economics professor Franz Buscha introduces you to 10 types of graphs that you would not commonly encounter in regular practice. For each type of graph, Franz presents a data visualization problem and an advanced graph type that solves the problem. He explains each graph and its variations, then highlights some useful tips of what to do and what not to do. Data visualizations include ridgeline plots, violin plots, heat plots, sparkline plots, rainbow plots, table plots, mosaic plots, matrix plots, ternary plots, and Chernoff faces.
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