From picking the right plot for the particular type of data, statistic, or result; to pre-processing sophisticated datasets, and even making important decisions about the aesthetic of a figure, visualization is both a science and art that requires both knowledge and practice to master.
This tutorial is for python users who are familiar with python and basic plotting, and want to build strong visualization skills that will let them effectively communicate any data, statistic, or result.
We will use python libraries such as seaborn, matplotlib, plotly, and sklearn; and discuss topics such as density estimation, dimensionality reduction, exploring similar datasets, interactive plotting, and making suitable choices for communication. Drawing examples from datasets in the scientific, financial, geospatial (mapping) fields and more.