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 Toronto by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Toronto. The dataset can be utilized to understand the population distribution of Toronto by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Toronto. 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 Toronto.
Key observations
Largest age group (population): Male # 5-9 years (307) | Female # 30-34 years (311). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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 Toronto Population by Gender. You can refer the same here
Between 2001 and 2023, the population of Toronto, in the Canadian province of Ontario, increased by around ** percent. Indeed, the metropolis's inhabitants were about *** million in 2001, and more than *** million two decades later.In 2023, Toronto was the largest metropolitan area in Canada in terms of population, ahead of Montreal and Vancouver.
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 Toronto by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Toronto. The dataset can be utilized to understand the population distribution of Toronto by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Toronto. 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 Toronto.
Key observations
Largest age group (population): Male # 10-14 years (21) | Female # 10-14 years (24). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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 Toronto Population by Gender. You can refer the same here
In 2022, more than half of the population (about ** percent) of the city of Toronto, in the province of Ontario, Canada, was between the ages of 20 and 60 years old. The largest age group was 25-34, with over *********** individuals.In 2022, Toronto was the largest metropolitan area in Canada in terms of population, ahead of Montreal, Quebec, and Vancouver, British Columbia.
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.
Demographics (2006 and 2011 Census Data) This dataset contains three worksheets. The full description for each column of data is available in the first worksheet called "IndicatorMetaData". The data came from the 2006 and 2011 Census. Some of the data from the 2011 Census was not available at the time of publishing. Refer to the descriptions in worksheet 1 for more information. Users should note that the data for each neighbourhood are based on the mathematical aggregation of smaller sub-areas (in this case Census Tracts) that when combined, define the entire neighbourhood. Since smaller areas may have their values rounded or suppressed (to abide by Statistics Canada privacy standards), the overall total may be undercounted. Population Total (2016 Census Data) The data refers to Total Population from the 2016 Census, aggregated by the City of Toronto to the City's 140 Neighbourhood Planning Areas. Although Statistics Canada makes a great effort to count every person, in each Census a notable number of people are left out for a variety of reasons. For Census 2016: Population and Dwellings example, people may be travelling, some dwellings are hard to find, and some people simply refuse to participate. Statistics Canada takes this into account and for each Census estimates a net 'undercoverage' rate for the urban region, the Toronto Census Metropolitan Area (CMA), but not for the city. The 2011 rate for the Toronto CMA was 3.72% plus or minus 0.53%. The 2016 rate is not yet available
Within two decades, the female population of the city of Toronto, in the Canadian province of Ontario, increased by around ** percent, and the male population by more than ** percent. Indeed, there were about **** million women and *** million men in Toronto in 2001, and four million women and **** million men in 2022. In 2022, Toronto was the largest metropolitan area in Canada in terms of population, ahead of Montreal, Quebec, and Vancouver, British Columbia.
Demographics (2006 and 2011 Census Data) This dataset contains three worksheets. The full description for each column of data is available in the first worksheet called "IndicatorMetaData". The data came from the 2006 and 2011 Census. Some of the data from the 2011 Census was not available at the time of publishing. Refer to the descriptions in worksheet 1 for more information. Users should note that the data for each neighbourhood are based on the mathematical aggregation of smaller sub-areas (in this case Census Tracts) that when combined, define the entire neighbourhood. Since smaller areas may have their values rounded or suppressed (to abide by Statistics Canada privacy standards), the overall total may be undercounted. Population Total (2016 Census Data) The data refers to Total Population from the 2016 Census, aggregated by the City of Toronto to the City's 140 Neighbourhood Planning Areas. Although Statistics Canada makes a great effort to count every person, in each Census a notable number of people are left out for a variety of reasons. For Census 2016: Population and Dwellings example, people may be travelling, some dwellings are hard to find, and some people simply refuse to participate. Statistics Canada takes this into account and for each Census estimates a net 'undercoverage' rate for the urban region, the Toronto Census Metropolitan Area (CMA), but not for the city. The 2011 rate for the Toronto CMA was 3.72% plus or minus 0.53%. The 2016 rate is not yet available
Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.
In 2022, the median age of the population of the city of Toronto, in the province of Ontario, Canada, was **** years, just over three years higher than in 2001. The median age of the population actually increased relatively steadily between 2001 and 2015, from **** to **** years, and then declined, after a plateau period, between 2017 and 2020. It increases again since 2020. The median age is the age that divides the population into two numerically equal groups: half are younger than this age and half are older.
In 2022, the average age of the population of the city of Toronto, in the province of Ontario, Canada, was **** years, just over four years higher than in 2001. The average age of the population actually increased relatively steadily between 2001 and 2022. The average age of a population is the mean age of the people in that population. It is different from the median age, which divides the population into two numerically equal groups (one half of the population is younger than the median age, the other is older). In 2022, the median age in Toronto was **** years.
This data set shows the following indicators: population breakdown by ethnicity, household income, education level, employment, age and sex. Data is broken down by the different Toronto neighbourhoods. CITY OF TORONTO NATIONAL HOUSEHOLD SURVEY METHODOLOGY NOTATION There were changes in the way information was collected for portions of the 2011 Census. This will impact the extent to which comparisons can be made with other Census periods on some Census variables. In general, 2011 Census data on population, dwelling counts, age, sex, families, household living arrangements, marital status, structural types of dwellings types and language can be compared to the data from other Censuses, with due regard for changing definitions of individual variables. Information on Aboriginal peoples, immigration, ethnocultural diversity, education, labour, income and housing was collected differently in 2011 as part of a voluntary National Household Survey (NHS) by Statistics Canada. In general, the 2011 NHS data is less comparable to that of the other Censuses due to non-response bias inherent in voluntary surveys. The risk of a voluntary survey is that the results may only reflect the kinds of individuals who are inclined to participate in a survey in the first place. As the National Household Survey User Guide notes, "because non-respondents tend to have different characteristics from respondents. As a result, there is a risk that the results will not be representative of the actual population." Comparisons between the 2011 NHS and other Censuses should not be considered fully reliable.
In 2022, in Toronto, in the Canadian province of Ontario, 11.6 percent of the population with employment income earned less than 5,000 Canadian dollars, while those earning more than 100,000 Canadian dollars represented 16.6 percent of the population.In 2023, there were more than 3.7 million people employed in Toronto, and the industry that employed the largest number of people was wholesale and retail trade.
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
The data set contains registered vehicle population count by various criteria such as vehicle class, vehicle status, vechicle make, vehicle model, vehicle year, plate class, plate declaration, county, weight related class and other vehicle decriptors.
https://www.usa.gov/government-works/https://www.usa.gov/government-works/
This dataset is used to find the best neighborhood to open a new gym in Toronto city. The data was collected the neighborhood profile data https://open.toronto.ca/dataset/neighbourhood-profiles/ and the crime data https://open.toronto.ca/dataset/neighbourhood-crime-rates/ and the venues information was obtained from Foursquare API.
Total population: The population for each neighborhood of Toronto city during 2016. number of educated people: The number of educated people per neighborhood. number of 15-45: The number of population aged from 15 to 45. number of employers: The number of employers per neighborhood. long_latt: The longitudes and latitudes for each neighborhood. number of gyms: The number of gyms in each neighborhood. number of venues: The number of venues in each neighborhood.
Statistics Canada publishes monthly labour force statistics for all Canadian Census Metropolitan Areas (CMAs) and provinces. In addition, the City of Toronto purchases a special run from Statistics Canada of Labour Force Survey (LFS) data for city of Toronto residents (i.e. separate from the rest of the Toronto CMA). LFS data are collected by place of residence, and therefore city of Toronto's "employment" represents "employed residents" and not "jobs" in the city of Toronto. There are more jobs in the city of Toronto than employed city of Toronto residents. In this LFS database, you will find 22 monthly tables and 28 annual tables. Most of the tables contain data for five geographies: city of Toronto, Toronto CMA, Toronto/Hamilton/Oshawa CMAs, Ontario and Canada ( see attachment Table of Contents below a full description ). LFS data in the IVT tables are not seasonally adjusted. Top level seasonally adjusted LFS data are available in our monthly Toronto Economic Bulletin on Open Data. LFS is based on a monthly sample of approximately 2,800 households in the Toronto CMA, about half of the sample is from the city of Toronto; therefore, estimates will vary from the results of a complete census. LFS follows a rotating panel sample design, in which households remain in the sample for six consecutive months. The total sample consists of six representative sub-samples of panels, and each month a panel is replaced after completing its six month stay in the survey. Outgoing households are replaced by households in the same or similar area. This results in a five-sixths month-to-month sample overlap, which makes the design efficient for estimating month-to-month changes. The rotation after six months prevents undue respondent burden for households that are selected for the survey ( see attachment Guide to the Labour Force Survey for more information). Upon reviewing the data, you will see that at least some cells in the IVT tables have been suppressed. For confidentiality reasons, Statistics Canada suppresses Labour Force Survey data for any cell that corresponds to less than 1,500 persons. At the beginning of 2015, Statistics Canada substantially changed the methodology used to produce LFS population estimates for the city of Toronto. These changes have resulted in large and inexplicable swings in population and related counts, which are not real. However, the unemployment and participation rates for city residents showed very little change in this revision. The red dots in the chart above represents Statistics Canada's Annual Demographics estimates for the populations of the city of Toronto, age 15 and over. These are only estimates, but they are generally accepted as the most accurate estimates for the city's population. (Source: https://www150.statcan.gc.ca/n1/pub/91-214-x/91-214-x2018000-eng.htm). The most recent Statistics Canada population estimate for the city of Toronto is for July 1, 2015; therefore, we have to use projections thereafter. There are several population projections for the city. The projection that EDC staff has chosen to use for rebasing city of Toronto LFS data is the Ontario Ministry of Finance Population Projections 2017-2041 and downloaded June, 2017 from http://www.fin.gov.on.ca/en/economy/demographics/projections/ Please see attachment Rebased Labour Force Survey for City of Toronto below for annual adjustment factors, monthly adjustment factors and an example of how to rebase the absolute numbers for the city of Toronto.
This table of Income profile information for dissemination area was downloaded from the Statistics Canada website and joined with bndDisseminationAreaGTHA2016 in DEM. It contains the information gathered during the 2016 Census with respect to the population within a dissemination area and the population breakdown of income and earnings by family, individuals, people in economic families, and the prevalence of low income and household income. This data covers the dissemination area in the Greater Toronto Hamilton Area.Statistics Canada has suppressed the profiles for certain areas due to very low population count. Suppressed areas will appear as NULL values in the attribute table.For more information regarding this data, please refer to the reference document here: http://www12.statcan.gc.ca/census-recensement/2016/ref/98-501/98-501-x2016006-eng.cfm
The Census of Population is held across Canada every 5 years and collects data about age and sex, families and households, language, immigration and internal migration, ethnocultural diversity, Aboriginal peoples, housing, education, income, and labour. City of Toronto Neighbourhood Profiles use this Census data to provide a portrait of the demographic, social and economic characteristics of the people and households in each City of Toronto neighbourhood. The profiles present selected highlights from the data, but these accompanying data files provide the full data set assembled for each neighbourhood. For an interactive visualization of this data, visit the Neighbourhood Profiles webpage. In these profiles, "neighbourhood" refers to the City of Toronto's 158 social planning neighbourhoods. These social planning neighbourhoods were developed in the late 1990s by the City of Toronto to help government and community organizations with local planning by providing socio-economic data at a meaningful geographic area. The boundaries of these social planning neighbourhoods are consistent over time, allowing for comparison between Census years. Neighbourhood level indicators from sources other than the Census of Population are also available through the City's Wellbeing Toronto mapping application and here on the Open Data portal. Each data point in this file is presented for the City's 158 neighbourhoods or 140 neighbourhoods prior to April 2021. The data is sourced from a number of Census tables released by Statistics Canada. The general Census Profile is the main source table for this data. Data tables are available for the Census years of 2001, 2006, 2011, 2016, and 2021. For definitions of terms and concepts referenced in this data set, as well as limitations imposed by rounding, data suppression standards, and geometry, users should consult the reference materials produced by Statistics Canada for the 2016 Census or the 2021 Census. Please note that social planning neighbourhoods are not an official standard geography produced by Statistics Canada and the data herein is compiled by special request through the Community Data Program.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
U.S. Census Bureau QuickFacts statistics for Toronto city, Ohio. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
This data set contains three worksheets. The full description for each column of data is available in the first worksheet called "Legend". Caveat Emptor: Discrepancies in taxfiler submissions and disaggregation of multiple taxfilers from a single family unit may result in over- or under-counting of low income taxfilers within certain geographies.
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 Toronto by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Toronto. The dataset can be utilized to understand the population distribution of Toronto by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Toronto. 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 Toronto.
Key observations
Largest age group (population): Male # 5-9 years (307) | Female # 30-34 years (311). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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 Toronto Population by Gender. You can refer the same here