The cansim package provides R bindings to Statistics Canada’s main socioeconomic time series database, previously known as (and frequently referred to in this package, and elsewhere, as) CANSIM. Data can be accessed by table number, vector or both table number and coordinate. The package accepts both old and new (NDM) CANSIM table catalogue numbers.

Installing cansim

The cansim package is available on CRAN and can be installed directly using the default package installation process:

Alternatively, the latest development version of the package can be downloaded from Github using the devtools or remotes packages.

# install.packages("remotes")



If you know the data table catalogue number you are interested in, use get_cansim to download the entire table.

data <- get_cansim("14-10-0293")
#> Accessing CANSIM NDM product 14-10-0293 from Statistics Canada
#> Parsing data
#> # A tibble: 6 × 24
#>   <chr>    <chr>  <chr>   <chr> <chr>  <chr>         <chr>     <chr>  <chr>     
#> 1 2001-03  Canada 2016A0… Pers… 249    thousands     3         v9141… 1.1.1     
#> 2 2001-03  Canada 2016A0… Pers… 249    thousands     3         v9141… 1.2.1     
#> 3 2001-03  Canada 2016A0… Pers… 249    thousands     3         v1018… 1.2.2     
#> 4 2001-03  Canada 2016A0… Pers… 249    thousands     3         v1018… 1.2.3     
#> 5 2001-03  Canada 2016A0… Pers… 249    thousands     3         v9141… 1.3.1     
#> 6 2001-03  Canada 2016A0… Pers… 249    thousands     3         v1018… 1.3.2     
#> # … with 15 more variables: VALUE <dbl>, STATUS <chr>, SYMBOL <chr>,
#> #   TERMINATED <chr>, DECIMALS <chr>, GeoUID <chr>, `Hierarchy for GEO` <chr>,
#> #   `Classification Code for Labour force characteristics` <chr>,
#> #   `Hierarchy for Labour force characteristics` <chr>,
#> #   `Classification Code for Statistics` <chr>,
#> #   `Hierarchy for Statistics` <chr>, val_norm <dbl>, Date <date>,
#> #   `Labour force characteristics` <fct>, Statistics <fct>

By default, the data tables retrieved by the package comes in the original format provided by Statistics Canada and is enriched by several added columns and transformations.

  • An additional Date column is added that tries to intelligently infer a Date object from the REF_DATE column.
  • An additional val_norm column is added, that applies the appropriate scaling factor to the VALUE column. So if data is coded as “thousands of dollars”, a value of 2.4 in the VALUE column is converte to a value of 2400 in the val_norm column. Similarly, a percentage of 12.2 in the VALUE column is converted to a value of 0.122 in the val_norm column.
  • Categorical variables are converted to factors and, if necessarily, de-duplicated by appending the name of the “parent” category in parenthesis. This ensures that column variables are unique and that they retain their original ordering.

Taking a look at an overview of the data within a table is a common first step. This is implemented in the package with the get_cansim_table_overview(table_number) function.

#> Labour force characteristics by economic region, three-month moving average, unadjusted for seasonality, last 5 months, inactive
#> CANSIM Table 14-10-0293
#> Start Reference Period: 2001-03-01, End Reference Period: 2020-12-01, Frequency: Monthly
#> Column Geography (76)
#> Canada, Newfoundland and Labrador, Avalon Peninsula, Newfoundland and Labrador, South Coast-Burin Peninsula and Notre Dame-Central Bonavista Bay, Newfoundland and Labrador, West Coast-Northern Peninsula-Labrador, Newfoundland and Labrador, Prince Edward Island, Nova Scotia, Cape Breton, Nova Scotia, North Shore, Nova Scotia, Annapolis Valley, Nova Scotia, ...
#> Column Labour force characteristics (10)
#> Population, Labour force, Employment, Full-time employment, Part-time employment, Unemployment, Not in labour force, Unemployment rate, Participation rate, Employment rate
#> Column Statistics (3)
#> Estimate, Standard error of estimate, Standard error of year-over-year change

When a table number is unknown, you can browse the available tables or search by survey name, keyword or title.

search_cansim_cubes("housing price indexes")
#> Retrieving cube information from StatCan servers...
#> # A tibble: 2 × 19
#>   cansim_table_number cubeTitleEn   cubeTitleFr productId cansimId cubeStartDate
#>   <chr>               <chr>         <chr>       <chr>     <chr>    <date>       
#> 1 18-10-0073          New housing … Indices de… 18100073  327-0005 1981-01-01   
#> 2 18-10-0095          New housing … Indices de… 18100095  327-0029 1981-01-01   
#> # … with 13 more variables: cubeEndDate <date>, releaseTime <dttm>,
#> #   archived <lgl>, subjectCode <chr>, surveyCode <chr>, frequencyCode <chr>,
#> #   corrections <chr>, dimensionNameEn <chr>, dimensionNameFr <chr>,
#> #   surveyEn <chr>, surveyFr <chr>, subjectEn <chr>, subjectFr <chr>

Individual series in Statistics Canada data tables can also be accessed by using individual numbered vectors. This is especially useful when building reports using specific indicators. For convenience, the cansim package allows users to specify named vectors, where the label field will be added to the returned data frame containing the specified name for each vector.

get_cansim_vector(c("Metro Van Apartment Construction Price Index"="v44176267",
                    "Metro Van CPI"="v41692930"),
                  start_time = "2015-05-01",
#> Accessing CANSIM NDM vectors from Statistics Canada
#> # A tibble: 5 × 12
#>      <int> <dbl> <chr>     <chr>        <int>         <int>     <int> <chr>     
#> 1        1  122. 2015-05-… 2021-07-28…      0             6         0…
#> 2        1  122. 2015-06-… 2021-07-28…      0             6         0…
#> 3        1  122. 2015-07-… 2021-07-28…      0             6         0…
#> 4        1  123. 2015-08-… 2021-07-28…      0             6         0…
#> 5        1  153  2015-07-… 2015-11-10…      0             9         0…
#> # … with 4 more variables: VECTOR <chr>, label <chr>, val_norm <dbl>,
#> #   Date <date>


The code in this package is licensed under the MIT license. The bundled table metadata in Sysdata.R, as well as all Statistics Canada data retrieved using this package is made available under the Statistics Canada Open Licence Agreement, a copy of which is included in the R folder. The Statistics Canada Open Licence Agreement requires that:

Subject to this agreement, Statistics Canada grants you a worldwide, royalty-free, non-exclusive licence to:

  - use, reproduce, publish, freely distribute, or sell the Information;
  - use, reproduce, publish, freely distribute, or sell Value-added Products; and,
  - sublicence any or all such rights, under terms consistent with this agreement.

In doing any of the above, you shall:

  - reproduce the Information accurately;
  - not use the Information in a way that suggests that Statistics Canada endorses you or your use of the Information;
  - not misrepresent the Information or its source;
  - use the Information in a manner that does not breach or infringe any applicable laws;
  - not merge or link the Information with any other databases for the purpose of attempting to identify an individual person, business or organization; and
  - not present the Information in such a manner that gives the appearance that you may have received, or had access to, information held by Statistics Canada about any identifiable individual person, business or organization.


Subject to the Statistics Canada Open Licence 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.