Long To Wide Format Via Longitudinal Dataset - #88
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Expose `to_wide` / `to_long` so cohorts stored in tidy long format can be pivoted into the wide layout that Sklong estimators expect (and back), keeping `features_group` and `non_longitudinal_features` in sync without silently dropping or duplicating rows. Signed-off-by: Provost Simon <simon1.provost@epitech.eu>
Validate round-trips, padded groups, duplicate (id, time) rows, and varying static columns so future changes to the reshape helpers cannot regress data integrity. Signed-off-by: Provost Simon <simon1.provost@epitech.eu>
Add a tutorial explaining how `LongitudinalDataset.to_wide` / `to_long` move cohorts between layouts, with Apple-styled 4K-rendered animations driving the explanation. Wire the page into the tutorials overview and Zensical nav. Signed-off-by: Provost Simon <simon1.provost@epitech.eu>
Remove the deprecated long-format ingestion shim from the TpT decision tree estimators (and its private `_preprocessing` helper); reshaping is now the caller's responsibility via `LongitudinalDataset.to_wide`, keeping a single, validated reshape implementation in the codebase. Signed-off-by: Provost Simon <simon1.provost@epitech.eu>
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A long wanted, and needed feature! Thanks to @MathiasValla to push it a little bit through #80.
Solving #64.
Cheers