Datasets: the data editor

Creating and importing

• Project → Data → New dataset: name it and define the first variables (label and type); ten empty rows are created so you can start typing.
• Import file: CSV, TSV or Excel are read in your browser. Types are detected from the values (number, integer, text, date, yes/no); check names, labels, types and measures, skip columns you do not need, then import. Values that do not fit a type become missing and are counted before you confirm.
• Every dataset has a change history: who added rows, changed variables, computed or filtered, and when.

Data view

• Double-click a cell, press Enter or start typing to edit; Tab and Enter move on; Delete clears; Ctrl+C copies the selected block as TSV and Ctrl+V pastes a block from a spreadsheet.
• Every value is validated against its variable type before it is saved; other members' saves appear within seconds.
• Click a row number to select rows (Shift for a range) and delete them; add rows from the toolbar; drag a column edge to resize; switch on Value labels to see labels instead of codes.

Variable view

One row per variable: name (snake_case, used in formulas), label, type, measure (scale, ordinal, nominal, identifier), role, decimals, value labels (1 = Female) and user-defined missing values (999, ranges). Changing a type converts the stored values; anything that cannot be converted becomes missing and is reported. Reorder with the arrows; deleting a variable removes its values from every case.

Computed variables, Select Cases, pivots and descriptives

• Compute: a formula over other variables — arithmetic, comparisons, AND/OR/NOT, IF, MISSING, ROUND, MEAN, DATEDIFF, AGE and more — previewed on the first rows and kept up to date when the inputs change.
• Select cases: a condition such as age >= 18 AND sex = "F"; excluded cases are greyed out and left out of descriptives, pivots and exports until the filter is cleared.
• Pivot: rows by one variable, optional columns by another, count or a summary (mean, median, SD, min, max, sum) of a numeric variable; copy as TSV.
• Descriptives: n, mean, SD, SE, 95% CI, median, quartiles, range, skewness and kurtosis for numeric variables; frequencies with percentages for categorical ones.
• Export CSV honours the active filter and, optionally, writes value labels instead of codes.