liveBook · Manning

Wide format

Wide format is a tabular layout in which each entity occupies a row and distinct measurements, variables, or attributes occupy separate columns.

How 2 Manning books explain it

Statistics Slam Dunk

Wide format is a tabular arrangement in which repeated measurements or categories are represented by separate columns.

How it is used
Prepares tabular measurements for summaries, visualizations, and subsequent analysis.
How deep it goes
Defines column-based organization and works through salary reshaping, but does not develop formal data-model theory.
Examples
Uses NBA salary-cap, real salary, inflation-adjusted salary, and playoff-classification columns across multiple seasons.
What you can do after
Apply it via dplyr and pivot_longer() to convert season columns into chart-ready long data.

Read how Statistics Slam Dunk explains wide format →

The Well-Grounded Data Analyst

Wide data is a tabular representation in which each entity occupies a row and measurements or attributes occupy columns.

How it is used
Supports data-modeling decisions when organizing one row per entity and selecting columns for attributes or measurements.
How deep it goes
Defines row and column structure, contrasts long format, and shows how granularity affects analytical questions.
Examples
Uses football matches with teams, goals, and competitions, then reorganizes matches into participant-level rows.
What you can do after
Evaluate which table structure makes a stakeholder’s analytical question easier to answer.

Read how The Well-Grounded Data Analyst explains wide format →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.