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This is Part 2 of our Scientific Data Visualization class. This session builds on Part 1, and participants continue to learn how to use matplotlib and different ways of visualizing data. The code that is developed in this course can be used on data in other contexts.

At the end of this class, participants will be able to:

• Create a scatter plot to visualize the distribution of continuous variables
• Create a box plot to visualize the distribution of one continuous variable against a discrete variable
• Create a heatmap to visualize a matrix
• Work through a full example to create a publication-grade figure

Basic Python knowledge is required for this class. The library's two-session Python course covers the required material.

This class is in person, please bring your own laptop. If you are planning to attend Part 1 (previous week), please make sure you register for each class separately.

Accreditation Statement
In support of improving patient care, Stanford Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.
Credit Designation
American Medical Association (AMA)
Stanford Medicine designates this live activity for a maximum of 1.5 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.