Exploratory Data Analysis (EDA)

Overview

EDA is the disciplined first pass over a dataset: understand shape, types, distributions, missingness, relationships, and red flags before writing a single model. Skipping it is the #1 cause of silent modeling failures (leakage, broken splits, garbage features).

When to use

• A new dataset just landed.
• You're asked to "look at", "profile", "explore", or "summarize" data.
• A model underperforms and you need to understand the inputs.

Workflow

Follow this order. Do not jump to modeling until every step is answered.