Gross domestic product at basic prices for the construction industry in Canada from 1997 to 2023

The dataset titled "Gross domestic product at basic prices for the construction industry in Canada from 1997 to 2023" falls under the domain of Construction. It is tagged with keywords such as Business and Economy, Construction, and Housing Potential. The dataset is available in various formats including PDF, Excel, PowerPoint, and PNG. The metadata identifier for this dataset is "/statistics/519742/gdp-for-construction-sector-in-canada/". It was published on June 10, 2024, and covers the time period from January 1, 1997, to December 31, 2023. The geographical area covered by the dataset is Canada. However, access to the dataset is closed and the location is provided upon request. The dataset is owned and published by Statistia, and they can be contacted at support@statista.com for access.

The dataset was accessed on March 12, 2025, and its unique identifier is "/statistics/519742/gdp-for-construction-sector-in-canada/". The language of the dataset is English. The dataset has a persistent and globally unique identifier. It does not contain data about individuals, identifiable individuals, or Indigenous communities. The temporal resolution of the dataset is irregular, and the geospatial resolution is at the city level. The dataset provides a description of the GDP at basic prices of the construction industry in Canada from 1997 to 2023. The resources available in the dataset include the title of the dataset. The metadata was created on March 12, 2025, and was last modified on March 19, 2025.

AI Generated

Datasets available for download

Additional Info

Field Value
Last Updated April 10, 2025, 13:34 (UTC)
Created March 12, 2025, 15:51 (UTC)
Domain / Topic
Domain or topic of the dataset being cataloged.
Construction
Description
A description of the dataset.

GDP at basic prices of the construction industry in Canada 1997-2023 Published by Fernando de Querol Cumbrera, Jun 10, 2024 The size of Canada's construction industry fell by over two billion Canadian dollars in 2023. That year, the gross domestic product (GDP) of that industry amounted to 164.7 billion Canadian dollars. Despite some fluctuations, the GDP of the construction industry has increased since 1997.

Tags
Keywords/tags categorizing the dataset.
Format (CSV, XLS, TXT, PDF, etc)
File format of the dataset.
.pdf - application/pdf, .xlsx - application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, .pptx - application/vnd.openxmlformats-officedocument.presentationml.presentation, .png - image/png
Dataset Size
Dataset size in megabytes.
Metadata Identifier
Metadata identifier – can be used as the unique identifier for catalogue entry
/statistics/519742/gdp-for-construction-sector-in-canada/
Published Date
Published date of the dataset.
2024-06-10
Time Period Data Span (start date)
Start date of the data in the dataset.
1997-01-01
Time Period Data Span (end date)
End date of time data in the dataset.
2023-12-31
GeoSpatial Area Data Span
A spatial region or named place the dataset covers.
Canada
Field Value
Access category
Type of access granted for the dataset (open, closed, service, etc).
Closed
Limits on use
Limits on use of data.
Location
Location of the dataset.
Stastia
Data Service
Data service for accessing a dataset.
Statistia
Owner
Owner of the dataset.
Statistia
Contact Point
Who to contact regarding access?
support@statista.com
Contact Point Email
The email to contact regarding access?
support@statista.com
Publisher
Publisher of the dataset.
Statistia
Publisher Email
Email of the publisher.
support@statista.com
Author
Author of the dataset.
Statistia
Author Email
Email of the author.
support@statista.com
Accessed At
Date the data and metadata was accessed.
2025-03-12
Field Value
Identifier
Unique identifier for the dataset.
/statistics/519742/gdp-for-construction-sector-in-canada/
Language
Language(s) of the dataset
English
Link to dataset description
A URL to an external document describing the dataset.
https://www.statista.com/study/60779/construction-in-canada/
Persistent Identifier
Data is identified by a persistent identifier.
Yes
Globally Unique Identifier
Data is identified by a persistent and globally unique identifier.
Yes
Contains data about individuals
Does the data hold data about individuals?
No
Contains data about identifiable individuals
Does the data hold identifiable data about individual?
No
Contains Indigenous Data
Does the data hold data about Indigenous communities?
No
Field Value
Source
Source of the dataset.
https://www.statista.com/statistics/519742/gdp-for-construction-sector-in-canada/
Version notes
Version notes about the dataset.
Is version of another dataset
Link to dataset that it is a version of.
Other versions
Link to datasets that are versions of it.
Provenance Text
Provenance Text of the data.
Provenance URL
Provenance URL of the data.
Temporal resolution
Describes how granular the date/time data in the dataset is.
Irregular
GeoSpatial resolution in meters
Describes how granular (in meters) geospatial data is in the dataset.
GeoSpatial resolution (in regions)
Describes how granular (in regions) geospatial data is in the dataset.
City
Field Value
Indigenous Community Permission
Who holds the Indigenous Community Permission. Who to contact regarding access to a dataset that has data about Indigenous communities.
Community Permission
Community permission (who gave permission).
The Indigenous communities the dataset is about
Indigenous communities from which data is derived.
Field Value
Number of data rows
If tabular dataset, total number of rows.
Number of data columns
If tabular dataset, total number of unique columns.
Number of data cells
If tabular dataset, total number of cells with data.
Number of data relations
If RDF dataset, total number of triples.
Number of entities
If RDF dataset, total number of entities.
Number of data properties
If RDF dataset, total number of unique properties used by the triples.
Data quality
Describes the quality of the data in the dataset.
Metric for data quality
A metric used to measure the quality of the data, such as missing values or invalid formats.

0 Comments

Please login or register to comment.