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Module

autolabel

Apply variable and value labels to register data in one line. Backed by a curated, multilingual, cross-agency metadata catalog.

What it does

Given a register-data dataset with cryptic variable names and coded value fields, autolabel applies human-readable labels — in the language of your choice — from the RegiStream catalog. No manual label define blocks, no looking up codebooks PDF by PDF. 

use lisa_2020.dta, clear
autolabel variables, domain(scb) lang(eng)
autolabel values,    domain(scb) lang(eng)
* Done.

Platforms

Live · v3.0.0

Stata

Reference implementation. Stata 16.0+. Full command set: variables, values, lookup, scope, suggest.

Stata docs →

Live · v3.0.0

Python

Pandas accessor + monkey-patched shortcuts. Depth-agnostic scope(), Jupyter-friendly return types, matplotlib/seaborn label integration. pip install registream.

Python docs →

Live · v3.0.0

R

Native R port using haven_labelled storage. Pipe-friendly, depth-agnostic scope(). Installs from registream.org/r/; CRAN publish on the way.

R docs →

Quick start

  1. Install registream + autolabel.
  2. Load a dataset from a supported agency (SCB, DST, SSB, Försäkringskassan, Socialstyrelsen, Statistics Iceland).
  3. Call autolabel variables, domain(<domain>) lang(eng) — the catalog bundle downloads automatically on first use.
  4. Call autolabel values for value labels.
  5. For precise context, pass scope("REGISTER" "VARIANT") and release("2020") — see the Stata reference.