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Rougier NP, Droettboom M, Bourne PE (2014) Ten Simple Rules for Better Figures. PLoS Comput Biol 10(9): e1003833.

VanderPlas, J. (2017). Python Data Science Handbook. Sebastopol: O'Reilly Media, Inc., Ch. 3 (Data Manipulation in Pandas)
This open-source textbook instructs the student on “doing data science” with python, it provides easy to follow code examples and real-world applications for the cross-disciplinary set of skills that are becoming increasingly important in many applications across industry and academia.

“Python for Data Visualization” on LinkedIn Learning, 1. Data Visualization Tools - 2. pandas
This course underscores the importance of data visualization as a means of communicating insight to a greater audience. The course also instructs students on how to generate and customize charts and graphs using python.

LinkedIn Learning: “Python for Data Visualization [External Link]” (Introduction – 1. Data Visualization Tools, 8:13) Review the video on LinkedIn Learning.
This LinkedIn Learning course provides a solid claim for using Python as the essential tool for working large amounts of data, it also discusses the value of data visualizations, and describes the mechanics for working with core visualization libraries, such as Matplotlib and Seaborn.