Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Key information about Canada population
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Canadian Business Counts, location counts with employees, by employment size ranges and North American Industry Classification System (NAICS), census metropolitan areas and census subdivisions, June 2024.
Housing Assessment Resource Tools (HART) This dataset contains 2 tables and 5 files which draw upon data from the 2021 Census of Canada. The tables are a custom order and contain data pertaining to older adults and housing need. The 2 tables have 6 dimensions in common and 1 dimension that is unique to each table. Table 1's unique dimension is the "Ethnicity / Indigeneity status" dimension which contains data fields related to visible minority and Indigenous identity within the population in private households. Table 2's unique dimension is "Structural type of dwelling and Period of Construction" which contains data fields relating to the structural type and period of construction of the dwelling. Each of the two tables is then split into multiple files based on geography. Table 1 has two files: Table 1.1 includes Canada, Provinces and Territories (14 geographies), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); and Table 1.2 includes Canada and the CMAs of Canada (44). Table 2 has three files: Table 2.1 includes Canada, Provinces and Territories (14), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); Table 2.2 includes Canada and the CMAs of Canada excluding Ontario and Quebec (20 geographies); and Table 2.3 includes Canada and the CMAs of Canada that are in Ontario and Quebec (25 geographies). The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and data fields: Geography: - Country of Canada as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia) as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), as a whole as well as all census divisions (CDs) within the 3 territories - All 43 census metropolitan areas (CMAs) in Canada Data Quality and Suppression: - The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. - Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. Source: Statistics Canada - When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. Universe: Full Universe: Population aged 55 years and over in owner and tenant households with household total income greater than zero in non-reserve non-farm private dwellings. Definition of Households examined for Core Housing Need: Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. Data Fields: Table 1: Age / Gender (12) 1. Total – Population 55 years and over 2. Men+ 3. Women+ 4. 55 to 64 years 5. Men+ 6. Women+ 7. 65+ years 8. Men+ 9. Women+ 10. 85+ 11. Men+ 12. Women+ Housing indicators (13) 1. Total – Private Households by core housing need status 2. Households below one standard only...
Annual population estimates as of July 1st, by census metropolitan area and census agglomeration, single year of age, five-year age group and gender, based on the Standard Geographical Classification (SGC) 2021.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Canadian by race. It includes the population of Canadian across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Canadian across relevant racial categories.
Key observations
The percent distribution of Canadian population by race (across all racial categories recognized by the U.S. Census Bureau): 87.26% are white, 3.30% are American Indian and Alaska Native and 9.43% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Canadian Population by Race & Ethnicity. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The total population in Canada was estimated at 41.5 million people in 2024, according to the latest census figures and projections from Trading Economics. This dataset provides - Canada Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Canadian County population by age. The dataset can be utilized to understand the age distribution and demographics of Canadian County.
The dataset constitues the following three datasets
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
The 2024 Census Subdivision Boundary File depicts the boundaries of all 5,028 census subdivisions, which combined, cover all of Canada. It contains the unique identifier (UID), name and type, as well as the UIDs, names and types (where applicable) of selected higher geographic levels. The 2024 Census Subdivision Boundary File is portrayed in Lambert conformal conic projection (North American Datum of 1983 [NAD83]) and is available as a national file.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
The 2024 Census Subdivision Boundary File depicts the boundaries of all 5,028 census subdivisions, which combined, cover all of Canada. It contains the unique identifier (UID), name and type, as well as the UIDs, names and types (where applicable) of selected higher geographic levels. The 2024 Census Subdivision Boundary File is portrayed in Lambert conformal conic projection (North American Datum of 1983 [NAD83]) and is available as a national file.
https://borealisdata.ca/api/datasets/:persistentId/versions/2.0/customlicense?persistentId=doi:10.5683/SP3/IT8REThttps://borealisdata.ca/api/datasets/:persistentId/versions/2.0/customlicense?persistentId=doi:10.5683/SP3/IT8RET
The PCCF is a digital file which provides a correspondence between the CPC six-character postal code and Statistics Canada’s standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution. New to the June 2022 version, a separate data file is available for retired postal codes. The retired file uses the same record layout as the PCCF file. The same syntax file can be used for both the PCCF data file and the retired data file. The geographic coordinates, which represent the standard geostatistical areas linked to each postal code on the PCCF, are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for marketing, planning, or research purposes. In April 1983, the Statistical Geomatics Centre released the first version of the PCCF, which linked postal codes to 1981 Census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect changes. For this release of the PCCF, the postal codes are directly geocoded to 2021 Census geographic areas. A quality indicator for the confidence of this linkage is available in the PCCF.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Canadian population by age. The dataset can be utilized to understand the age distribution and demographics of Canadian.
The dataset constitues the following three datasets
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Little Canada. Based on the latest 2018-2022 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Little Canada. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.
Key observations: Insights from 2022
In terms of income distribution across age cohorts, in Little Canada, householders within the 25 to 44 years age group have the highest median household income at $77,780, followed by those in the 45 to 64 years age group with an income of $77,181. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $62,243. Notably, householders within the under 25 years age group, had the lowest median household income at $36,828.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.
Age groups classifications include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Little Canada median household income by age. You can refer the same here
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.
Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.
The statistic shows the total population in Canada from 2020 to 2024, with projections up until 2030. In 2024, the total population in Canada amounted to about 41.14 million inhabitants. Population of Canada Canada ranks second among the largest countries in the world in terms of area size, right behind Russia, despite having a relatively low total population. The reason for this is that most of Canada remains uninhabited due to inhospitable conditions. Approximately 90 percent of all Canadians live within about 160 km of the U.S. border because of better living conditions and larger cities. On a year to year basis, Canada’s total population has continued to increase, although not dramatically. Population growth as of 2012 has amounted to its highest values in the past decade, reaching a peak in 2009, but was unstable and constantly fluctuating. Simultaneously, Canada’s fertility rate dropped slightly between 2009 and 2011, after experiencing a decade high birth rate in 2008. Standard of living in Canada has remained stable and has kept the country as one of the top 20 countries with the highest Human Development Index rating. The Human Development Index (HDI) measures quality of life based on several indicators, such as life expectancy at birth, literacy rate, education levels and gross national income per capita. Canada has a relatively high life expectancy compared to many other international countries, earning a spot in the top 20 countries and beating out countries such as the United States and the UK. From an economic standpoint, Canada has been slowly recovering from the 2008 financial crisis. Unemployment has gradually decreased, after reaching a decade high in 2009. Additionally, GDP has dramatically increased since 2009 and is expected to continue to increase for the next several years.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of New Canada town by race. It includes the population of New Canada town across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of New Canada town across relevant racial categories.
Key observations
The percent distribution of New Canada town population by race (across all racial categories recognized by the U.S. Census Bureau): 74.50% are white, 0.25% are Asian, 19.80% are some other race and 5.45% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for New Canada town Population by Race & Ethnicity. You can refer the same here
This table presents the 2021 population counts for census metropolitan areas and census agglomerations, and their population centres and rural areas.
Families of tax filers; Census families with children by age of children and children by age groups (final T1 Family File; T1FF).
In 2048, the population in Manitoba is projected to reach about 1.84 million people. This is compared to a population of 1.46 million people in 2024.
This table shows the 2021 population and dwelling counts for reported forward sortation areas.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Key information about Canada population