Exploratory Data Analysis with Python

This workshop will provide an introduction to Exploratory Data Analysis (EDA) in python using the polars package, base python, and visualization packages like matplotlib and seaborn. The workshop will focus on loading data, creating a basic summary of the data, visualizing trends and using basic model building to explore relationships in data.

This workshop incorporates hands-on work, and there will be plenty of time for questions. No software installation is needed; participants will be instructed how to use Google Colab to write, store, and share code in the cloud. Previous workshops within this series include Introduction to Computational Thinking and Getting Started with Python: Basics, and Getting Started with Python: Loops and Functions

Learning Objectives:

By the end of this workshop, you will be able to:

• Generate descriptive statistics

• Generate visualizations to explore distribution, location, variation and covariation in your data

• Choose appropriate visualizations for given data types (e.g. categorical vs. continuous) 

• Use EDA to identify patterns or clusters in data, common and rare value, as well as outliers