Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Ontario population by age. The dataset can be utilized to understand the age distribution and demographics of Ontario.
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/.
Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Ontario population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Ontario across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2023, the population of Ontario was 6,653, a 0.14% decrease year-by-year from 2022. Previously, in 2022, Ontario population was 6,662, a decline of 0.28% compared to a population of 6,681 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Ontario increased by 1,384. In this period, the peak population was 6,681 in the year 2021. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
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 Ontario Population by Year. You can refer the same here
Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.
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 Ontario by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Ontario. The dataset can be utilized to understand the population distribution of Ontario by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Ontario. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Ontario.
Key observations
Largest age group (population): Male # 30-34 years (7,947) | Female # 25-29 years (8,143). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
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 Ontario Population by Gender. You can refer the same here
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
Data includes: board and school information, grade 3 and 6 EQAO student achievements for reading, writing and mathematics, and grade 9 mathematics EQAO and OSSLT. Data excludes private schools, Education and Community Partnership Programs (ECPP), summer, night and continuing education schools.
How Are We Protecting Privacy?
Results for OnSIS and Statistics Canada variables are suppressed based on school population size to better protect student privacy. In order to achieve this additional level of protection, the Ministry has used a methodology that randomly rounds a percentage either up or down depending on school enrolment. In order to protect privacy, the ministry does not publicly report on data when there are fewer than 10 individuals represented.
The information in the School Information Finder is the most current available to the Ministry of Education at this time, as reported by schools, school boards, EQAO and Statistics Canada. The information is updated as frequently as possible.
This information is also available on the Ministry of Education's School Information Finder website by individual school.
Descriptions for some of the data types can be found in our glossary.
School/school board and school authority contact information are updated and maintained by school boards and may not be the most current version. For the most recent information please visit: https://data.ontario.ca/dataset/ontario-public-school-contact-information.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Annual population projections, from 2023 to 2051. These datasets include population projections by age and gender organized by geography: * Projections for Ontario * Projections for each of the 6 regions * Projections for each of the 49 census divisions * Projections for each of the 34 public health units * Projections for each of the 9 Ministry of Children, Community and Social Services’ Service Delivery Division (SDD) regions For Ontario only, the projected annual components of demographic change are provided for the reference, low- and high-growth scenarios. For all other geographies, only the reference scenario is produced. An Interim Update to MOF population projections (2024-2051) was released in April 2025, including two new tables for Ontario only. The previous tables (2023-2051) for Ontario and the sub-provincial geographies remain available. Updated projections for all sub-provincial geographies will be released in Summer 2025.
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
The dataset highlights key OPS workforce demographics extracted from the OPS payroll reporting system (WIN), including:
A data dictionary is included to define all workforce demographics, metrics and limitations.
This data has been released due to the demand expressed through a public vote to determine which datasets the Government of Ontario should publish. This was the fourth most voted on dataset out of a pool of approximately 1000 entries.
The Data in this report is as of March 31, 2025, unless otherwise indicated.
*[WIN]: Workforce Information Network *[OPS]: Ontario Public Service
Components of population growth, annual: births, deaths, immigrants, emigrants, returning emigrants, net temporary emigrants, net interprovincial migration, net non-permanent residents, residual deviation.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the data for the Ontario, WI population pyramid, which represents the Ontario population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age groups:
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 Ontario Population by Age. You can refer the same here
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
Data includes public and Catholic schools and school authorities. Private schools and publicly funded hospital and provincial schools and care, treatment and correctional facilities are not included.
Includes:
Source: As reported by schools in Ontario School Information System (OnSIS), October Submissions.
Boards update and maintain "/dataset/ontario-public-school-contact-information">contact information related to schools and boards of education.
Small cells have been suppressed:
Note:
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
**Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool **
As of January 26, 2023, the population counts are based on Statistics Canada’s 2021 estimates. The coverage methodology has been revised to calculate age based on the current date and deceased individuals are no longer included. The method used to count daily dose administrations has changed is now based on the date delivered versus the day entered into the data system. Historical data has been updated.
Please note that Cases by Vaccination Status data will no longer be published as of June 30, 2022.
Please note that case rates by vaccination status and age group data will no longer be published as of July 13, 2022.
Please note that Hospitalization by Vaccination Status data will no longer be published as of June 30, 2022.
Learn more about COVID-19 vaccines.
All data reflects totals from 8 p.m. the previous day.
This dataset is subject to change.
Additional notes
Hospitalizations
Cases
Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This dataset details the total number of electric vehicles (EVs) in Ontario. This includes both battery-electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). Data includes: * Total EVs by Forward Sortation Area (FSA) (the first three characters of the postal code) of the vehicle plate owner’s registered address * Number of BEVs by FSA of the vehicle plate owner’s registered address * Number of PHEVs by FSA of the vehicle plate owner’s registered address Note: Datasets from July 1, 2024 onward include all electric vehicles with licence plates that have been automatically renewed.
Educational attainment of the population aged 25 to 64, by age group and sex, Organisation for Economic Co-operation and Development (OECD), Canada, provinces and territories. This table is included in Section D: Postsecondary education: Educational attainment of the population aged 25 to 64 of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Ontario population by year. The dataset can be utilized to understand the population trend of Ontario.
The dataset constitues the following 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/.
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
Data from the Ministry of Colleges and Universities' College Enrolment Statistical Reporting system.
Provides aggregated key enrolment data for college students, such as:
To protect privacy, numbers are suppressed in categories with less than 10 students.
Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.
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...
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Unemployment Rate in Canada decreased to 6.90 percent in June from 7 percent in May of 2025. This dataset provides - Canada Unemployment Rate - 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 Ontario population by age. The dataset can be utilized to understand the age distribution and demographics of Ontario.
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/.