Canada CA: Population in Urban Agglomerations of More Than 1 Million data was reported at 18,139,786.000 Person in 2024. This records an increase from the previous number of 17,958,253.000 Person for 2023. Canada CA: Population in Urban Agglomerations of More Than 1 Million data is updated yearly, averaging 11,427,441.000 Person from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 18,139,786.000 Person in 2024 and a record low of 5,390,421.000 Person in 1960. Canada CA: Population in Urban Agglomerations of More Than 1 Million data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the country's population living in metropolitan areas that in 2018 had a population of more than one million people.;United Nations, World Urbanization Prospects.;;

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.

Canada CA: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data was reported at 44.799 % in 2024. This records an increase from the previous number of 44.786 % for 2023. Canada CA: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data is updated yearly, averaging 40.278 % from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 45.994 % in 2021 and a record low of 30.098 % in 1960. Canada CA: Population in Urban Agglomerations of More Than 1 Million: as % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Population and Urbanization Statistics. Population in urban agglomerations of more than one million is the percentage of a country's population living in metropolitan areas that in 2018 had a population of more than one million people.;United Nations, World Urbanization Prospects.;Weighted average;

Canada CA: Population Density: People per Square Km data was reported at 4.350 Person/sq km in 2021. This records an increase from the previous number of 4.239 Person/sq km for 2020. Canada CA: Population Density: People per Square Km data is updated yearly, averaging 3.127 Person/sq km from Dec 1961 (Median) to 2021, with 61 observations. The data reached an all-time high of 4.350 Person/sq km in 2021 and a record low of 2.038 Person/sq km in 1961. Canada CA: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.;Food and Agriculture Organization and World Bank population estimates.;Weighted average;

Components of population growth, annual: births, deaths, immigrants, emigrants, returning emigrants, net temporary emigrants, net interprovincial migration, net non-permanent residents, residual deviation.

This table presents the 2021 and 2016 population and dwelling counts, land area and population density for Canada, the provinces and the territories. It also shows the percentage change in the population and dwelling counts between 2016 and 2021.

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.

The CCRI microdata are based on a five percent sample of the Canadian population as recorded in the 1911 census. The basic sample unit is the dwelling, as defined by the census. The sample includes all responses recorded on the population schedule for all individuals residing in each sampled dwelling. For each census, the main sample covers smaller dwellings with no more than thirty residents. The CCRI microdata facilitate research on individuals, families, households, and communities caught up in the complex transformation of Canadian society which took place during the first half of the twentieth century. Ultimately, these data represent the raw materials with which census statistics can be produced. Confidential data from subsequent census enumerations are available from Statistics Canada's Research Data Centres.

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...

Canada CA: Proportion of Population Spending More Than 10% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data was reported at 3.500 % in 2019. This records a decrease from the previous number of 3.800 % for 2017. Canada CA: Proportion of Population Spending More Than 10% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data is updated yearly, averaging 3.500 % from Dec 2000 (Median) to 2019, with 15 observations. The data reached an all-time high of 4.400 % in 2009 and a record low of 2.900 % in 2001. Canada CA: Proportion of Population Spending More Than 10% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Social: Poverty and Inequality. Proportion of population spending more than 10% of household consumption or income on out-of-pocket health care expenditure. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).;Global Health Observatory. Geneva: World Health Organization; 2023. (https://www.who.int/data/gho/data/themes/topics/financial-protection);Weighted average;This is the Sustainable Development Goal indicator 3.8.2[https://unstats.un.org/sdgs/metadata/].

This table contains 336672 series, with data for years 2003 - 2003 (not all combinations necessarily have data for all years), and was last released on 2007-08-13. This table contains data described by the following dimensions (Not all combinations are available): Geography (167 items: Canada; Newfoundland and Labrador; Health and Community Services St. John's Region; Newfoundland and Labrador; Health and Community Services Eastern Region; Newfoundland and Labrador ...) Age group (14 items: Total; 12 years and over; 15 to 19 years; 12 to 14 years; 12 to 19 years ...) Sex (3 items: Both sexes; Males; Females ...) Dietary practices (6 items: Total population for the variable dietary practices; Consume fruits and vegetables less than 5 times per day; Consume fruits and vegetables more than 10 times per day; Consume fruits and vegetables 5 to 10 times per day ...) Characteristics (8 items: Number of persons; Coefficient of variation for number of persons; High 95% confidence interval; number of persons; Low 95% confidence interval; number of persons ...).

Canada CA: Age Dependency Ratio: % of Working-Age Population: Old data was reported at 29.628 % in 2023. This records an increase from the previous number of 28.912 % for 2022. Canada CA: Age Dependency Ratio: % of Working-Age Population: Old data is updated yearly, averaging 16.946 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 29.628 % in 2023 and a record low of 12.743 % in 1971. Canada CA: Age Dependency Ratio: % of Working-Age Population: Old data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Population and Urbanization Statistics. Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.;World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2024 Revision.;Weighted average;

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

Canada, with 3.33 people per square kilometre, has one of the lowest population densities in the world. In 2001, most of Canada's population of 30,007,094 lived within 200 kilometres of the United States (along Canada's south). In fact, the inhabitants of our three biggest cities -- Toronto, Montréal and Vancouver -- can drive to the border in less than two hours. Thousands of kilometres to the north, our polar region -- the Yukon, the Northwest Territories and Nunavut -- is relatively empty, embracing 41% of our land mass but only 0.3% of our population. An inset map shows in greater detail the Windsor-Québec Corridor where a high concentration of Canadians live.

Note: The data release is complete as of August 14th, 2023. 1. (Added April 4th) Canada and Census Divisions = Early April 2023 2. (Added May 1st) Ontario, British Columbia, and Alberta Census Subdivisions (CSDs) = Late April 2023 3a. (Added June 8th) Manitoba and Saskatchewan CSDs 3b. (Added June 12th) Quebec CSDs = June 12th 2023 4. (Added June 30th) Newfoundland and Labrador, Prince Edward Island, New Brunswick, and Nova Scotia CSDs = Early July 2023 5. (Added August 14th) Yukon, Northwest Territories, and Nunavut CSDs = Early August 2023. For more information, please visit HART.ubc.ca. Housing Assessment Resource Tools (HART) This dataset contains 18 tables which draw upon data from the 2021 Census of Canada. The tables are a custom order and contains data pertaining to core housing need and characteristics of households. 17 of the tables each cover a different geography in Canada: one for Canada as a whole, one for all Canadian census divisions (CD), and 15 for all census subdivisions (CSD) across Canada. The last table contains the median income for all geographies. Statistics Canada used these median incomes as the "area median household income (AMHI)," from which they derived some of the data fields within the Shelter Costs/Household Income dimension. Included alongside the data tables is a guide to HART's housing need assessment methodology. This guide is intended to support independent use of HART's custom data both to allow for transparent verification of our analysis, as well as supporting efforts to utilize the data for analysis beyond what HART did. There are many data fields in the data order that we did not use that may be of value for others. 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, all CDs & Country as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia), all CSDs & each Province as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), all CSDs & each Territory as a whole 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 greater than 10 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. Counts of 10 or less are rounded to a base of 10, meaning they will be rounded to either 10 or zero. Universe: Full Universe: Private Households in Non-farm Non-band Off-reserve Occupied Private Dwellings with Income Greater than zero. 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...

Canada CA: Age Dependency Ratio: % of Working-Age Population: Young data was reported at 23.682 % in 2023. This records a decrease from the previous number of 23.822 % for 2022. Canada CA: Age Dependency Ratio: % of Working-Age Population: Young data is updated yearly, averaging 30.454 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 58.088 % in 1962 and a record low of 23.682 % in 2023. Canada CA: Age Dependency Ratio: % of Working-Age Population: Young data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Population and Urbanization Statistics. Age dependency ratio, young, is the ratio of younger dependents--people younger than 15--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.;World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2022 Revision.;Weighted average;

This table contains 2800 series, with data for years 1994 - 1998 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (not all combinations are available): Geography (5 items: Territories; Yukon; Northwest Territories including Nunavut; Northwest Territories ...), Age group (10 items: Total; 18-69 years; 18-19 years; 20-34 years; 20-24 years ...), Pap smear (7 items: Total population for the variable Pap smear; Pap smear; 1 year to less than 3 years ago; Pap smear; 3 or more years ago; Pap smear; less than 1 year ago ...), Characteristics (8 items: Number of persons; Low 95% confidence interval - number of persons; High 95% confidence interval - number of persons; Coefficient of variation for number of persons ...).

Canada Population: 100 Years & Over data was reported at 11.672 Person th in 2024. This records an increase from the previous number of 11.493 Person th for 2023. Canada Population: 100 Years & Over data is updated yearly, averaging 6.603 Person th from Jun 2000 (Median) to 2024, with 25 observations. The data reached an all-time high of 11.672 Person th in 2024 and a record low of 3.393 Person th in 2000. Canada Population: 100 Years & Over data remains active status in CEIC and is reported by Statistics Canada. The data is categorized under Global Database’s Canada – Table CA.G001: Population.

Context

The Canadian Disaster Database The Canadian Disaster Database (CDD) contains detailed disaster information on more than 1000 natural, technological and conflict events (excluding war) that have happened since 1900 at home or abroad and that have directly affected Canadians.

Content

Data description copied from: https://www.publicsafety.gc.ca/cnt/rsrcs/cndn-dsstr-dtbs/index-en.aspx

Dataset date range: 1900 - present

The CDD tracks "significant disaster events" which conform to the Emergency Management Framework for Canada definition of a "disaster" and meet one or more of the following criteria:

• 10 or more people killed
• 100 or more people affected/injured/infected/evacuated or homeless
• an appeal for national/international assistance
• historical significance
• significant damage/interruption of normal processes such that the community affected cannot recover on its own

The database describes where and when a disaster occurred, the number of injuries, evacuations, and fatalities, as well as a rough estimate of the costs. As much as possible, the CDD contains primary data that is valid, current and supported by reliable and traceable sources, including federal institutions, provincial/territorial governments, non-governmental organizations and media sources.

Data is updated and reviewed on a semi-annual basis.

Data Field Description

Disaster Type The type of disaster (e.g. flood, earthquake, etc.) that occurred.
Date of Event The date a specific event took place.
Specific Location The city, town or region where a specific event took place.
Description of Event A brief description of a specific event, including pertinent details that may not be captured in other data fields (e.g. amount of precipitation, temperatures, neighbourhoods, etc.)
Fatalities The number of people killed due to a specific event.
Injured/Infected The number of people injured or infected due to a specific event.
Evacuees The number of individuals evacuated by the government of Canada due to a specific event.
Latitude & Longitude The exact geographic location of a specific event.
Province/Territory The province or territory where a specific event took place.
Estimated Total Cost A roll-up of all the costs listed within the financial data fields for a specific event.
DFAA Payments The amount, in dollars, paid out by Disaster Financial Assistance Arrangements (Public Safety Canada) due to a specific event.
Insurance Payments The amount, in dollars, paid out by insurance companies due to a specific event.
Provincial/Territorial Costs/Payments The amount, in dollars, paid out by a Province or Territory due to a specific event.
Utility Costs/Losses The amount of people whose utility services (power, water, etc.) were interrupted/affected by a specific event.
Magnitude A measure of the size of an earthquake, related to the amount of energy released.
Other Federal Institution Costs The amount, in dollars, paid out by other federal institutions.

Acknowledgements

Data gathered from: http://cdd.publicsafety.gc.ca Terms of use for commercial and non-comerical reproduction: https://www.publicsafety.gc.ca/cnt/ntcs/trms-en.aspx

Inspiration

This dataset provides valuable insight to natural and non-natrual disasters which have affected Canada.

Possible explorations: * Where do different types of disasters occur more frequently? * Which Province / Location in Canada has been hit the hardest in terms of fatalities, number of injuries, estimated total cost, etc.?

Spatial-temporal correlations between natural/artifical distasters *

I think that this can be used to produce some interesting data visualizations. Some of the questions I look forward to answering include:

• Can any spatial-temporal correlations between disasters be found in this dataset?
• Which locations in Canada have been hit the hardest, in terms of people injured, fatalities, financial impact, etc.