VancouvR

VancouvR is an R wrapper around the City of Vancouver Open Data API. It allows transparent and reproducible access to the Vancouver Open Data Portal to facilitate data analysis and sharing of code.

The package caches downloaded data for the duration of the current session, so re-running code blocks will not result in repeated downloads. This speeds up the code, cuts down on unnecessary network traffic and reduces strain on the City of Vancouver Open Data infrastructure.

Datasets with a spatial component are automatically returned as sf objects, ready for mapping with ggplot2::geom_sf() or any other spatial workflow. The where and select parameters accept ODSQL syntax for server-side filtering and column selection.

Reference

VancouverOpenData package reference

Installing the package

To install the latest release version of VancouvR from CRAN use

install.packages("VancouvR")

The development version of VancouvR is available from GitHub via

remotes::install_github("mountainmath/VancouvR")

API key

Smaller datasets can be accessed without an API key, but for larger datasets an API key is required. API keys are available after registering at the City of Vancouver Open Data Portal.

Setting the API key in the .Rprofile file via

options(VancouverOpenDataApiKey=<your api key>)

will ensure that it is automatically loaded and not exposed when you share your code. The key is sent as an Authorization header, so it does not appear in request URLs.

The portal enforces a daily request quota, shared across everything using your key. VancouvR warns once per session as it runs low, and get_cov_rate_limit() reports what is left.

Examples

Get a list of datasets relating to properties

library(VancouvR)

search_cov_datasets("properties")

Get the first 10 records of the property tax report for 2019 tax year.

get_cov_data(dataset_id = "property-tax-report",where="tax_assessment_year='2021'",rows=10)

Get metadata for the public trees dataset.

get_cov_metadata("public-trees")

Count the number of cherry trees by genus, aggregated server-side.

aggregate_cov_data("public-trees", where = "common_name LIKE 'CHERRY'", group_by = "genus_name")

See what values a field takes before filtering on it.

get_cov_facets("public-trees", facet = "genus_name")

Filtering, sorting and limiting all happen on the server, so only the rows you want are downloaded.

get_cov_data("public-trees", refine = "genus_name:ACER", order_by = "height_m DESC", rows = 10)

Browse the catalogue rather than searching it: list_cov_facets() shows what themes and keywords exist, and list_cov_datasets() filters on them.

list_cov_facets(facet = "theme")
list_cov_datasets(refine = "theme:Sustainability")

The features facet is worth knowing about — its geo value identifies the datasets that come back as sf objects.

list_cov_datasets(refine = "features:geo")

Spatial datasets are downloaded as FlatGeobuf and returned as sf, with the coordinate reference system already set.

library(ggplot2)

areas <- get_cov_data("local-area-boundary")
ggplot(areas) + geom_sf()

Cite VancouvR

If you wish to cite VancouvR:

von Bergmann, J. VancouvR: Access the ‘City of Vancouver’ Open Data API. v0.1.11, DOI: 10.32614/CRAN.package.VancouvR.

A BibTeX entry for LaTeX users is

  @Manual{VancouvR,
    author = {Jens {von Bergmann}},
    title = {{VancouvR}: Access the {'City of Vancouver' Open Data API},
    year = {2026},
    note = {R package version 0.1.11},
    doi = {10.32614/CRAN.package.VancouvR},
    url = {https://mountainmath.github.io/VancouvR/},
  }