iBOTS
Tidy data
Organize observations and variables consistently for tabular analysis.
Our View
Consistent tabular structures make transformations, visualizations, and statistical comparisons easier to understand and reuse; other data models may suit arrays or specialized recordings better.
Provisional positions are editorial proposals awaiting group review.
Teaching — Discussed in our dataframe and statistics topics; individual offerings are not yet attributed to this practice.
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Related themes: Scientific Computing
Related topics: Dataframes and Statistics
Getting started
For tabular measurements, decide what one observation means. Give each observation a row and each variable a column, with stable identifiers to connect related tables. Document units and missing-value conventions rather than encoding them in formatting.
Reshape tables deliberately when plotting or comparing groups. Keep the original data and the transformation code so collaborators can follow how the analysis table was produced.