Learn how to inspect, clean, and explore real-world data. Before any modeling or hypothesis testing, Exploratory Data Analysis (EDA) is essential for understanding your data's structure, spotting potential issues, and uncovering meaningful patterns. We’ll walk through a complete EDA workflow using Charlottesville’s parking ticket data (1999–2024), including data cleaning, visualization, and interpretation.

You will learn: 

• Practical data-cleaning strategies,
• Common visualization techniques,
• A reproducible EDA workflow you can apply to any project.

Expected prior knowledge: Basic familiarity with R

Our policy is that we do not record live workshops in order to encourage robust Q&A. However, you can always find the full workshop materials for all of our workshops at: https://library.virginia.edu/data/training/past-workshops which allows you to work through the material at your own pace. We also encourage you to reach out to the instructor at any time for a one-on-one consult, and for specific or general questions about any of the topics we cover.