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CS 06 — An Introduction to Creating Data Visualizations with Python

Quarter: Fall
Day(s): Tuesdays
Course Format: On-campus
Duration: 10 weeks
Date(s): Sep 24—Dec 3
Time: 7:00—8:50 pm
Drop Deadline: Oct 7
Units: 2
Tuition: $530
Instructor(s): Charlie Flanagan
Status: Closed
Please Note: No class on November 26
Fall
On-campus
Tuesdays
7:00—8:50 pm
Date(s)
Sep 24—Dec 3
10 weeks
Drop By
Oct 7
2 Units
Fees
$530
Instructor(s):
Charlie Flanagan
Closed
Please Note: No class on November 26
In today’s world, being able to tell a story with data is essential. This course will teach students how to create and publish stunning data visualizations and interactive graphics using the latest open source tools. In addition to lectures and labs, guest speakers who are data visualization experts from leading tech companies will show how they leverage the tools we will use in class.

We will begin with an introduction to loading and pre-processing data using Python and SQL. We will survey the ecosystem of visualization tools, explaining the pros and cons of each, and review the different visualization chart types and explain what they are best at conveying. We will then move to creating beautiful visualizations using popular open source libraries such as matplotlib and seaborn. We will also try out Altair, an open source package that will allow us to build interactive and connected visualizations. We will hold lab sections each week after class so students can apply their learning to their own projects, with help from the instructor. The class will consist of lectures, live coding demonstrations, hands-on practice, and guest speakers. Students will finish the course with a portfolio of visualizations that they understand deeply and can leverage going forward.

Previous basic coding experience will be helpful but not essential as we will be editing existing code. This course includes an optional field trip. Date and time to be announced in class.

Charlie Flanagan, Senior Data Scientist, Google

Charlie Flanagan spent ten years on Wall Street as a quantitative analyst prior to Google. He received an MS in software engineering from Harvard and an MBA from Columbia, and is a Chartered Financial Analyst.

Textbooks for this course:

There are no required textbooks; however, some fee-based online readings may be assigned.