Learn with runnable examples

Get started in the browser

• Open a .dta file onlineLoad a Stata-format dataset and inspect its variables.
• Run a do-fileKeep commands in a reusable script and run it in the browser.
• Run supported commandsSee the scope of the implemented command language.
• Work on a ChromebookPrepare a browser-first classroom workflow.

Command examples

• import delimitedLoad a CSV and verify rows, variables, types, and missing values.
• summarizeCalculate observation counts, means, standard deviations, ranges, and inspect missingness.
• regressFit OLS with a categorical predictor and robust standard errors.
• egenCreate row-wise, standardized, aggregate, and grouped variables.
• mergeJoin two datasets by an identifier and diagnose unmatched observations.
• collapseReplace individual rows with grouped means and nonmissing counts.
• tabulateCreate one-way and two-way frequency tables.
• ttestCompare means between two independent groups.
• generateCreate numeric, string, and indicator variables from expressions.
• replaceChange selected values while preserving the rest of a variable.
• recodeMap numeric values and ranges into clearly labeled categories.
• reshapeConvert repeated measurements between wide and long layouts.
• duplicatesReport, tag, inspect, and carefully remove duplicate records.
• tabstatBuild compact tables with selected summary statistics.
• correlateCalculate Pearson correlations and inspect current missing-data limits.
• pwcorrCalculate pairwise Pearson correlations when values are missing.
• logitFit a binary-response model with robust standard errors.
• predictCreate fitted values, residuals, and prediction standard errors.

Check compatibility before adapting an example

Each example documents the stats.camp behavior it actually uses. An existing do-file can still depend on other options, stored results, user-written packages, or exact formatting that is not implemented.

Review the maintained command and limitation table before moving a consequential workflow.