Easily connect to Statistics Canada’s Web Data Service with R. Open economic data (formerly known as CANSIM tables, now identified by Product IDs (PID)) are accessible as a data frame, directly in the user’s R environment.

Installation

The released version of statcanR package is accessible through CRAN and devtools.

install.packages("statcanR")

install.packages("devtools")
devtools::install_github('warint/statcanR')

Example

This section presents an example of how to use the statcanR R package and its function sqs_statcan_data().

The following example is provided to illustrate how to use the function. It consists in collecting some descriptive statistics about the Canadian Labour Force at the federal, provincial and industrial levels, on a monthly basis.

With a simple web search ‘statistics canada wages by industry metropolitan area monthly’, the table number can easily be found on Statisitcs Canada’s webpage. Here is below a figure that illustrates this example, such as ‘27-10-0014-01’ for the Federal expenditures on science and technology, by socio-economic objectives.

Once the table number is identified, the statcan_data() function is easy to use in order to collect the data, as following:

Statistics Canada Open Licence

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Please refer to the terms of licence before using the Information.

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Why SQS?

SQS stands for SKEMA Quantum Studio, a research and technological development centre based in Montreal, Canada, that serves as the engine room for the SKEMA Global lab in AI.

SKEMA Quantum Studio is also a state-of-the-art platform developed by our team that enables scholars, students and professors to access one of the most powerful analytical tools in higher education. By using data science and artificial intelligence within the platform, new theories, methods and concepts are being developed to study globalisation, innovation and digital transformations that our society faces.

To learn more about the SKEMA Quantum Studio and the mission of the SKEMA Global Lab in AI, please visit the following websites : SQS ; Global Lab.

Acknowledgments

The authors would like to thank the Center for Interuniversity Research and Analysis of Organizations (CIRANO, Montreal) for its support, as well as Thibault Senegas, Marine Leroi and Martin Paquette at SKEMA Global Lab in AI. However, errors and omissions are ours.