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Data visualization in Python

Data visualization in Python

This workshop will consist of about an hour of presentation and discussion followed by about an hour for in-class practice exercises. The presentation will cover creation of 2-D plots with Matplotlib (v. 2.0), including publication-quality plots, and interactive Web plots with Bokeh. Plots will include histograms, bar graphs, line graphs, scatter plots, and several types of statistical graphs. Demonstration and practice data will be pulled from a variety of sources including deidentified clinical data.

Requirements: Participants should have a working knowledge of Python programming and the Pandas library, and should bring a laptop with Python 3, Pandas, the Jupyter Notebook, Matplotlib v. 2.0, and Bokeh installed (these are included in the Anaconda 4.3 distribution). Python 3.5 or 3.6 and Anaconda 4.3 are recommended, Python 3.5.2 will be used in class demonstrations. Installation instructions and practice data sets will be sent to registrants prior to the session.

Date:
Thursday, November 2, 2017
Time:
2:00pm - 4:30pm
Location:
Health Sciences Library Carter Classroom
Instructor:
James Harrison, PhD