registream-autolabel 3.0.2

RegiStream Autolabel: accessor for register data labeling.

registream-autolabel

Apply variable and value labels from the RegiStream catalog to pandas DataFrames. Native schema v2; depth-agnostic scope; Jupyter-friendly return types; matplotlib + seaborn plot-label integration.

Full documentation: https://registream.org/docs/autolabel/python.

Install

pip install registream-autolabel

Pulls in registream-core as a dependency. For the full ecosystem (core + autolabel + future modules) you can instead pip install registream (meta-package).

Requires Python 3.11 or later. Pandas is the only hard runtime dependency besides registream-core. Seaborn is optional; install it separately to light up the label-aware plot wrappers.

Quick start

import pandas as pd
import registream.autolabel  # side effect: installs autolabel methods on pd.DataFrame

df = pd.read_stata("lisa_2020.dta")

# Apply variable and value labels from SCB metadata (English); scope auto-inferred.
df.autolabel(domain="scb", lang="eng")

# Display-time labeled view without mutating df.
df.lab.head()

Labels land on df.attrs['registream']; the column data itself is never mutated.

What you get as DataFrame methods

Importing the package adds a small set of methods directly onto pd.DataFrame, so the API reads like a native pandas method:

Method	What it does
df.autolabel(domain, lang, scope, release, …)	Apply variable + value labels
df.lookup(variables, detail=…)	Metadata for one or more variables (returns a LookupResult)
df.lab	A LabeledView for display-time labeling (a property)
df.variable_labels()	Dict of variable labels
df.value_labels()	Dict of value labels
df.get_variable_labels(columns) / df.get_value_labels(columns)	Column-aware getters
df.set_variable_labels({...}) / df.set_value_labels(col, {...})	In-place edits
df.copy_labels(source, target)	Copy a label bundle between columns
df.meta_search(pattern)	Filter label metadata by regex

This matches the Stata surface (autolabel variables, domain(scb) lang(eng)) and the R surface (df |> autolabel(domain = "scb", lang = "eng")) verb-for-verb: the data is always the subject; the command is always the verb.

Module-level functions

For operations that don't have a single DataFrame as their subject:

from registream.autolabel import suggest, scope, info, cite, update_datasets

suggest(df)                                   # preview coverage; returns SuggestResult
scope(domain="scb", lang="eng")               # catalog browser, no df
update_datasets("scb", "eng")                 # refresh the on-disk metadata bundle

info()                                        # dict: config + cache + versions
cite()                                        # versioned APA citation

Full signatures, arguments, labeling rules, and worked examples are on the Python reference page.

Command-line

python -m registream.autolabel version     # installed autolabel version
python -m registream.autolabel info        # config + cache + versions
python -m registream.autolabel cite        # APA citation

Plotting integration

When seaborn is installed, autolabel wraps 16 plotting functions on import so value labels show on categorical axes and variable labels flow into axis titles + legend. Zero extra setup:

import seaborn as sns
import registream.autolabel  # wraps seaborn on import

df.autolabel(domain="scb", lang="eng")

sns.barplot(data=df, x="kon", y="alder")
# x-axis ticks: "Man", "Woman"
# x label:     "Sex"
# y label:     "Age (years)"

Opt out with REGISTREAM_NO_PLOT_PATCH=1. Pandas column patches (labels follow through df["new"] = df["old"] and df.rename(columns=...)) opt out with REGISTREAM_NO_PANDAS_PATCH=1. All three opt-outs read the environment at import time.

Library-author opt-out

If you're writing a library that imports registream.autolabel as a transitive dependency and don't want to add methods to your users' DataFrames, set REGISTREAM_NO_SHORTCUTS=1 before import. The accessor (df.rs.*) and the module-level functions stay fully available:

from registream.autolabel import autolabel, lookup
autolabel(df, domain="scb", lang="eng")

End-user documentation uses the method form throughout; this opt-out exists so library code doesn't surprise end users.

Catalog coverage

Metadata bundles ship for Statistics Sweden (scb), Statistics Denmark (dst), Statistics Norway (ssb), Statistics Iceland (hagstofa), Försäkringskassan (fk), and Socialstyrelsen (sos). Institutions can create their own domains; see the schema v2 reference and the institutional setup guide.

Citation

Clark, J. & Wen, J. (2024). RegiStream: Infrastructure for Register Data Research. https://registream.org

registream.autolabel.cite() returns the versioned APA form.

Authors

• Jeffrey Clark — [e-mail]
• Jie Wen — [e-mail]

License

BSD 3-Clause. See LICENSE.