Introduction to Python and the Principles of Data Visualization

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A Tufts University DISC Workshop

View the Project on GitHub annahaensch/DataVizWorkshop

Workshop

Virtual , July 14th-16th, 10am - 12pm

Description

In this 3-day Tufts DISC workshop we’ll learn how to use Python to create impactful data visualizations. We’ll discuss the fundamentals of data cleaning and exploratory data analysis with Python, we’ll talk about the principles of effective data visualizations, and we’ll explore the most common Python based tools in a data scientist’s toolkit. The workshop will include lots of hand-on tutorials and time to experiment.

There are no prerequisites for this workshop. It will be assumed that participants are new/novice Python users. No special software/downloads will be required; all programming exercises will take place online in Google Colab notebooks.

Agenda & Materials

Day 1: Data Preparation with Python

Day 2: Principles of Data Visualization

Day 3: Fancy Charts

Organizers

Dr. Anna Haensch is a Senior Data Scientist in the Tufts Data Intensive Studies Center and has a PhD in mathematics. Her research involves approaches of machine learning and Bayesian inference to understand complicated multi-tiered time series data. She is also interested in the ways that numerical and data literacy impact the way we produce and consume media.

Dr. Georgios Georgalis is a Data Scientist in the Tufts Data Intensive Studies Center and has a PhD in Aeronautics & Astronautics. His research has involved applications of machine learning, design of experiments, and uncertainty quantification in aerospace and systems engineering problems. He is interested in ways that data science applies to complex problems that include multiple layers of data sources, stakeholders, or solution approaches.

Dr. Karin Knudson is a Senior Data Scientist in the Tufts Data Intensive Studies Center and has a PhD in mathematics. Her research has involved the development and application of methods from machine learning, Bayesian statistics, and compressive sensing, particularly to neural data. She is interested in using approaches from data science to support scholarship across and between a range of disciplines, and is also interested in education for data science.

Additional Resources

Principles of Effective Data Visualization

Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures by Claus Wilke: A nice, readable, very visual overview of different plots, when to use them, and how to make them effective. (Available from Tufts library.)

How Charts Lie: Getting Smarter About Visual Information by Alberto Cairo: An excellent book about how data visualizations are used and misused.

The Truthful Art: Data, Charts, and Maps for Communication by Alberto Cairo. (Available from Tufts library.)