Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.

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

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Toronto by race. It includes the distribution of the Non-Hispanic population of Toronto across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Toronto across relevant racial categories.

Key observations

Of the Non-Hispanic population in Toronto, the largest racial group is White alone with a population of 65 (100% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the Toronto
• Population: The population of the racial category (for Non-Hispanic) in the Toronto is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Toronto total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Toronto Population by Race & Ethnicity. You can refer the same here

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.

Context

With a population just short of 3 million people, the city of Toronto is the largest in Canada, and one of the largest in North America (behind only Mexico City, New York and Los Angeles). Toronto is also one of the most multicultural cities in the world, making life in Toronto a wonderful multicultural experience for all. More than 140 languages and dialects are spoken in the city, and almost half the population Toronto were born outside Canada.It is a place where people can try the best of each culture, either while they work or just passing through. Toronto is well known for its great food.

Content

This dataset was created by doing webscraping of Toronto wikipedia page . The dataset contains the latitude and longitude of all the neighborhoods and boroughs with postal code of Toronto City,Canada.

For Reference Period 2008: Martin Prosperity Institute, Year 2010 data. The Cultural Location Index (CLI) is an economic indicator that shows the intersection of where people who work in culture occupations live and work, and cultural facilities. This indicator was developed to provide a quantifiable city-wide view of the geographic concentration of Toronto's cultural sector. This indicator is positively influenced in part by the physical presence of cultural facilities, and the concentration of the people who live and work in the cultural sector. The indicator does not capture culture as a set of community values or beliefs. As such a community could have a very active cultural life, and be lower on the Cultural Location Index. The Cultural Location Index (CLI) was produced by the Martin Prosperity Institute for the City of Toronto in 2010. For Reference Period 2011: Data not yet available. For Reference Period 2008: Data not available. For Reference Period 2011: Statistics Canada, 2011 Census, language tables; calculations performed by City of Toronto, Social Policy Analysis & Research (contact spar@toronto.ca). The Linguistic Diversity Index (LDI) is the probability that any two people selected at random would have different mother tongues. Calculated using Greenberg's Linguistic Diversity Index. Lower values mean less diversity, higher values mean more diversity. The Linguistic Diversity Index (LDI) was developed by the City of Toronto, Social Policy Analysis & Research, based on Census 2011 data.

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.

* Percentages depicted as 0 may not always be 0 values as in certain situations the values have been randomly rounded down or there are no reported results at a school for the respective indicator. * Percentages depicted as 100 are not always 100, in certain situations the values have been randomly rounded up.

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.

"Toronto’s 158 neighbourhoods are a microcosm of the city’s inhabitants, cultures and life. The primary purpose of the City-designated social planning neighbourhoods is to help City staff collect data, plan, analyze and forecast City services. While these neighbourhoods may not fully encompass every historical neighbourhood area, they do provide a way for planners and researchers to track information about them over time. The neighbourhood profiles were developed to help government and community agencies with their local planning, by providing socio-economic data at a meaningful geographic area. Unlike other geographies like wards or dissemination blocks, the boundaries of these social planning neighbourhoods change very infrequently over time, allowing researchers to perform longitudinal studies to see the changes in each area. Not all people define neighbourhoods the same way, but for the purposes of statistical reporting these neighbourhoods were defined based on Statistics Canada census tracts. For more information visit our About Toronto's Neighbourhoods page."

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

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.

Annual population estimates by marital status or legal marital status, age and sex, Canada, provinces and territories.

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.

Please see "Readme" file. This dataset contains a list of the participating businesses, their locations and their special offers for Live Green Toronto Membership Card holders. This data was collected to facilitate connecting cardholders and businesses participating in the Live Green Toronto Membership Card program. The Live Green Toronto Membership Card is available to people who live, work, and shop in the City of Toronto - and it's FREE! There are currently over 26,000 cardholders and over 450 participating businesses. Please note that online only businesses are included in the list but they do not have a location to publish. We are actively recruiting new business members who are committed to supporting the environment. To be eligible, the business must be located in the City of Toronto. We welcome suggestions for new businesses - email livegreencard@toronto.ca The Membership Card program is one more way that Live Green Toronto supports and inspires residents and businesses who want to do something right now to make Toronto an even greener city.

Differences in the number and proportion of persons with and without disabilities, aged 15 years and over, by census metropolitan areas.

Toronto Neighbourhoods Boundary File includes Crime Data by Neighbourhood. Counts are available at the offence and/or victim level for Assault, Auto Theft, Bike Theft, Break and Enter, Robbery, Theft Over, Homicide, Shootings and Theft from Motor Vehicle. Data also includes crime rates per 100,000 people by neighbourhood based on each year's Projected Population by Environics Analytics.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario..In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

Families of tax filers; Census families with children by age of children and children by age groups (final T1 Family File; T1FF).

Data on the number and assessment value of selected residential property types owned solely by individuals who are Canadian residents, by immigrant status, period of immigration, and selected places of birth in the census metropolitan areas (CMAs) of Toronto and Vancouver.

This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).

Status of COVID-19 cases in Ontario

This dataset compiles daily snapshots of publicly reported data on 2019 Novel Coronavirus (COVID-19) testing in Ontario.

Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak.

Effective April 13, 2023, this dataset will be discontinued. The public can continue to access the data within this dataset in the following locations updated weekly on the Ontario Data Catalogue:

• Ontario COVID-19 testing percent positive by age group
• Confirmed positive cases of COVID-19 in Ontario
• Ontario COVID-19 testing metrics by Public Health Unit (PHU)
• Ontario COVID-19 testing percent positive by age group
• COVID-19 cases in hospital and ICU, by Ontario Health (OH) region
• Cumulative deaths (new methodology)
• Deaths Involving COVID-19 by Fatality Type

For information on Long-Term Care Home COVID-19 Data, please visit: Long-Term Care Home COVID-19 Data.

Data includes:

• reporting date
• daily tests completed
• total tests completed
• test outcomes
• total case outcomes (resolutions and deaths)
• current tests under investigation
• current hospitalizations
  • current patients in Intensive Care Units (ICUs) due to COVID-related critical Illness
  • current patients in Intensive Care Units (ICUs) testing positive for COVID-19
  • current patients in Intensive Care Units (ICUs) no longer testing positive for COVID-19
  • current patients in Intensive Care Units (ICUs) on ventilators due to COVID-related critical illness
  • current patients in Intensive Care Units (ICUs) on ventilators testing positive for COVID-19
  • current patients in Intensive Care Units (ICUs) on ventilators no longer testing positive for COVID-19
• Long-Term Care (LTC) resident and worker COVID-19 case and death totals
• Variants of Concern case totals
• number of new deaths reported (occurred in the last month)
• number of historical deaths reported (occurred more than one month ago)
• change in number of cases from previous day by Public Health Unit (PHU).

This dataset is subject to change. Please review the daily epidemiologic summaries for information on variables, methodology, and technical considerations.

Cumulative Deaths

**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 **

The methodology used to count COVID-19 deaths has changed to exclude deaths not caused by COVID. This impacts data captured in the columns “Deaths”, “Deaths_Data_Cleaning” and “newly_reported_deaths” starting with data for March 11, 2022. A new column has been added to the file “Deaths_New_Methodology” which represents the methodological change.

The method used to count COVID-19 deaths has changed, effective December 1, 2022. Prior to December 1, 2022, deaths were counted based on the date the death was updated in the public health unit’s system. Going forward, deaths are counted on the date they occurred.

On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. A small number of COVID deaths (less than 20) do not have recorded death date and will be excluded from this file.

CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags.

Related dataset(s)

• Confirmed positive cases of COVID-19 in Ontario

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.