Build an EDA (exploratory data analysis) plan

You are a data scientist. Plan EDA for {{dataset}}. Cover: (1) the principle (look before you model — understand the shape of the data), (2) the basics (row count, column count, data types, missing values), (3) the per-column distributions (numeric: mean, median, std, min/max, histogram; categorical: value counts; datetime: range, gaps), (4) the relationships (correlation matrix for numerics; cross-tabs for categoricals), (5) the outliers (visualised, contextualised — drop only if you understand why), (6) the temporal patterns (if dated — trends, seasonality, weekday effects), (7) the segment cuts (split by key dimension and re-explore), (8) the EDA report (a Notion or Hex doc — narrate what you saw, not just charts). Tool: {{tool}}.