Exploratory Data Analysis (EDA)

Use this skill for understanding datasets before modeling: profiling distributions, detecting anomalies, identifying relationships, and assessing data quality.

When to use this skill

• New dataset — need orientation on structure, types, distributions
• Before feature engineering — understand variable relationships
• Data quality investigation — find anomalies, missing patterns, outliers
• Model preparation — validate assumptions about data

Core EDA workflow