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canpumf

The goal of canpumf is to facilitate ingesting, organizing, and working with StatCan PUMF data in R.

Installation

You can install the current development version of canpumf from GitHub with:

remotes::install_github("mountainmath/canpumf")

Documentation

Please consult the documentation and example articles for further information.

StatCan publishes an official guide to the Labour Force Survey for different vintages of the LFS.

Cache path

PUMF data can be large and should be cached locally. Set the canpumf.cache_path option to a local directory via options(canpumf.cache_path="<your local path>") in your .Rprofile. Without this, data is stored in tempdir() for the session only.

DuckDB

On first use PUMF data is imported into DuckDB. By default a PUMF DuckDB connection will be shown in the RStudio (or Positron) Connections Pane once a connection is opened, you control the default behaviour by setting the canpumf.register_connection option in your .Rprofile:

options("canpumf.register_connection" = TRUE)

Basic usage

Some PUMF data is available from StatCan via direct download and can be accessed directly via get_pumf(). In other cases, PUMF data must be ordered via EFT and deposited in the cache directory so get_pumf() can find it.

get_pumf() downloads (if needed), parses metadata, applies value labels automatically, and returns a lazy dplyr::tbl() backed by a local DuckDB database. Call dplyr::collect() to load into memory.

Column values are labeled automatically (e.g. province codes become factor levels like "British Columbia"). Column names remain as short coded names by default (e.g. PROV, LFSSTAT). To rename columns to human-readable variable labels, pipe through label_pumf_columns():

tbl <- get_pumf("LFS", "2022") |>
  label_pumf_columns()

When done querying, release the DuckDB connection with close_pumf(tbl).

LFS data

LFS data is organized by year, except for the current year where it is organized by month. To access data for a specific year:

lfs_2022 <- get_pumf("LFS", "2022")

This downloads the 2022 LFS PUMF data if needed, parses it, loads labeled data into a shared DuckDB database, and returns a lazy tbl filtered to 2022. To access all LFS data currently in the local database:

lfs_all_local <- get_pumf("LFS")

To ensure the local database contains all available LFS versions, use refresh = "auto". This checks StatCan for versions not yet in the database and imports them:

lfs_all <- get_pumf("LFS", refresh = "auto")

Census data

The canpumf package supports Census PUMF from 1971 through 2021. All releases from 1991 onward are available via direct download; years 1986 and earlier must be ordered through Statistics Canada’s EFT portal and placed in the cache directory.

pumf_2021 <- get_pumf("Census", "2021")

By default the package loads the individuals file. Available variants by year:

pumf_h_2016 <- get_pumf("Census", "2016 (hierarchical)")

Verified datasets

The following datasets have been end-to-end tested (metadata parsed, data imported, DuckDB built) without errors or warnings. Versions marked direct download can be fetched automatically by get_pumf(); others must be placed in the cache directory via Statistics Canada’s EFT portal.

GSS surveys are keyed by their canonical Cycle N (YYYY) version (e.g. get_pumf("GSS", "Cycle 16 (2002)")), since a bare year is not unique across the GSS — several years carry both a regular cycle and a Giving/Volunteering survey. For convenience the cycle number alone ("Cycle 16", "16"), the bare year ("2002"), and the historical theme name ("Aging and Social Support", "Family 2017", "Time Use 2022") all resolve to the canonical key.

CPSS and CCAHS are keyed by their bare cycle number (get_pumf("CPSS", "1"), get_pumf("CCAHS", "1")). StatCan styles these cycles “Series N” (CPSS) and “Cycle N” (CCAHS), so "Series 3", "Cycle 4", and "CPSS 6" resolve to the number; CCAHS additionally accepts its reference year "2022". A bare year is not a CPSS alias, since several CPSS cycles share a calendar year.

Related packages

The cansim package is designed to retrieve and work with public Statistics Canada data tables. cansim prepares retrieved data tables as analysis-ready tidy dataframes and provides a number of convenience tools and functions to make it easier to work with Statistics Canada data. It is available on CRAN and on Github.

The cancensus package is designed to retrieve and work with public Statistics Canada census data via the CensusMapper API. It is available on CRAN and on Github.

Cite canpumf

If you wish to cite the canpumf package in your work:

von Bergmann, J. (2026), canpumf: Import StatCan PUMF data into R. v0.5.2.

A BibTeX entry for LaTeX users is

  @Manual{,
    author = {Jens {von Bergmann}},
    title = {canpumf: Import StatCan PUMF data into R},
    year = {2026},
    note = {R package version 0.5.2},
    url = {https://mountainmath.github.io/canpumf/},
  }

Statistics Canada Attribution

Subject to the Statistics Canada Open Data License Agreement, licensed products using Statistics Canada data should employ the following acknowledgement of source:

Acknowledgment of Source

(a) You shall include and maintain the following notice on all licensed rights of the Information:

  - Source: Statistics Canada, name of product, reference date. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.
 
(b) Where any Information is contained within a Value-added Product, you shall include on such Value-added Product the following notice:

  - Adapted from Statistics Canada, name of product, reference date. This does not constitute an endorsement by Statistics Canada of this product.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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