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Twitterhttps://www.icpsr.umich.edu/web/ICPSR/studies/34/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/34/terms
This study contains selected demographic, social, economic, public policy, and political comparative data for Switzerland, Canada, France, and Mexico for the decades of 1900-1960. Each dataset presents comparable data at the province or district level for each decade in the period. Various derived measures, such as percentages, ratios, and indices, constitute the bulk of these datasets. Data for Switzerland contain information for all cantons for each decennial year from 1900 to 1960. Variables describe population characteristics, such as the age of men and women, county and commune of origin, ratio of foreigners to Swiss, percentage of the population from other countries such as Germany, Austria and Lichtenstein, Italy, and France, the percentage of the population that were Protestants, Catholics, and Jews, births, deaths, infant mortality rates, persons per household, population density, the percentage of urban and agricultural population, marital status, marriages, divorces, professions, factory workers, and primary, secondary, and university students. Economic variables provide information on the number of corporations, factory workers, economic status, cultivated land, taxation and tax revenues, canton revenues and expenditures, federal subsidies, bankruptcies, bank account deposits, and taxable assets. Additional variables provide political information, such as national referenda returns, party votes cast in National Council elections, and seats in the cantonal legislature held by political groups such as the Peasants, Socialists, Democrats, Catholics, Radicals, and others. Data for Canada provide information for all provinces for the decades 1900-1960 on population characteristics, such as national origin, the net internal migration per 1,000 of native population, population density per square mile, the percentage of owner-occupied dwellings, the percentage of urban population, the percentage of change in population from preceding censuses, the percentage of illiterate population aged 5 years and older, and the median years of schooling. Economic variables provide information on per capita personal income, total provincial revenue and expenditure per capita, the percentage of the labor force employed in manufacturing and in agriculture, the average number of employees per manufacturing establishment, assessed value of real property per capita, the average number of acres per farm, highway and rural road mileage, transportation and communication, the number of telephones per 100 population, and the number of motor vehicles registered per 1,000 population. Additional variables on elections and votes are supplied as well. Data for France provide information for all departements for all legislative elections since 1936, the two presidential elections of 1965 and 1969, and several referenda held in the period since 1958. Social and economic data are provided for the years 1946, 1954, and 1962, while various policy data are presented for the period 1959-1962. Variables provide information on population characteristics, such as the percentages of population by age group, foreign-born, bachelors aged 20 to 59, divorced men aged 25 and older, elementary school students in private schools, elementary school students per million population from 1966 to 1967, the number of persons in household in 1962, infant mortality rates per million births, and the number of priests per 10,000 population in 1946. Economic variables focus on the Gross National Product (GNP), the revenue per capita per household, personal income per capita, income tax, the percentage of active population in industry, construction and public works, transportation, hotels, public administration, and other jobs, the percentage of skilled and unskilled industrial workers, the number of doctors per 10,000 population, the number of agricultural cooperatives in 1946, the average hectares per farm, the percentage of farms cultivated by the owner, tenants, and sharecroppers, the number of workhorses, cows, and oxen per 100 hectares of farmland in 1946, and the percentages of automobiles per 1,000 population, radios per 100 homes, and cinema seats per 1,000 population. Data are also provided on the percentage of Communists (PCF), Socialists, Radical Socialists, Conservatives, Gaullists, Moderates, Poujadists, Independents, Turnouts, and other political groups and p
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TwitterData tables on the social and economic conditions in Pre-Confederation Canada from the first census in 1665 to Confederation in 1867. This dataset is one of three that cover the history of the censuses in Quebec. These tables cover New France for the years 1676-1754. For census data for the years 1825-1861, see the Lower Canada dataset; for census data for the years 1765-1790, see the Province of Quebec dataset. The tables were transcribed from the fourth volume of the 1871 Census of Canada: Reprint of the Censuses of Canada, 1665-1871, available online from Statistics Canada, Canadiana, Government of Canada Publications, and the Internet Archive. Note on terminology: Due to the nature of some of the data sources, terminology may include language that is problematic and/or offensive to researchers. Certain vocabulary used to refer to racial, ethnic, religious and cultural groups is specific to the time period when the data were collected. When exploring or using these data do so in the context of historical thinking concepts – analyzing not only the content but asking questions of who shaped the content and why.
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TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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Depicted on this map is the extent of New France at its territorial height circa 1740 prior to its great territorial losses to British North America. Also shown on the map are the territorial claims, administrative divisions, and the distribution of population and settlement (including fur trading posts) circa 1740. This map along with British North America circa 1823 shows the settlement and population in Canada for two important periods in Canadian history prior to Confederation.
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TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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Depicted on this map is the extent of New France at its territorial height circa 1740 prior to its great territorial losses to British North America. Also shown on the map are the territorial claims, administrative divisions, and the distribution of population and settlement (including fur trading posts) circa 1740. This map along with British North America circa 1823 shows the settlement and population in Canada for two important periods in Canadian history prior to Confederation.
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TwitterThis dataset, a product of the Trade Team - Development Research Group, is part of a larger effort in the group to measure the extent of the brain drain as part of the International Migration and Development Program. It measures international skilled migration for the years 1975-2000.
The methodology is explained in: "Tendance de long terme des migrations internationals. Analyse à partir des 6 principaux pays recerveurs", Cécily Defoort.
This data set uses the same methodology as used in the Docquier-Marfouk data set on international migration by educational attainment. The authors use data from 6 key receiving countries in the OECD: Australia, Canada, France, Germany, the UK and the US.
It is estimated that the data represent approximately 77 percent of the world’s migrant population.
Bilateral brain drain rates are estimated based observations for every five years, during the period 1975-2000.
Australia, Canada, France, Germany, UK and US
Aggregate data [agg]
Other [oth]
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
The outbreak of COVID19 pushed Kaggle to launch several competitions to better understand how the new virus spreads.
The data provided by this competition is not only divided by nation (China, US, Canada...), but also sometimes by province/state/dependency/territory (California, Hubei, French Guiana, Saskatchewan...).
Although there are already several Kaggle datasets that provide population estimates by nation, I couldn't find any that provided a population estimate for each one of the constituent states ("provinces/states") included in the data for the 2nd week COVID19 Global Forecasting competition. So here they are, packaged in a super simple two-column CSV file.
Each row in this dataset is a rough estimate of the population in each of the constituent states that appear in the COVID19 Global Forecasting competition. Each row is, of course, one of these inner states. By "constituent state" I mean one of: - the 54 United States of America - the 33 Chinese provinces - 10 Canadian provinces (plus a territory, Northwest Territories) - 11 French overseas territories - 10 British overseas territories - 6 Australian states (plus 2 internal territories) - 5 constituent countries of the Kingdom of the Netherlands - 2 autonomous Danish territories (Faroe Islands and Greenland)
In total, 134 states are listed.
The population estimates were collected from the following sources: - Australia: Wikipedia - Canada: worldpopulationreview.com - China: another Kaggle dataset - Denmark: worldpopulationreview.com - France: worldometers.info (retrieved 2020-04-02, 18:00 UTC) - Netherlands: worldometers.info (retrieved 2020-04-02, 18:00 UTC) - US: worldpopulationreview.com - Guam: worldpopulationreview.com - UK: worldometers.info (retrieved 2020-04-02, 18:00 UTC)
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TwitterThis table contains 25 series, with data for years 1955 - 2013 (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 ...) Last permanent residence (25 items: Total immigrants; France; Great Britain; Total Europe ...).
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TwitterTThe ERS International Macroeconomic Data Set provides historical and projected data for 181 countries that account for more than 99 percent of the world economy. These data and projections are assembled explicitly to serve as underlying assumptions for the annual USDA agricultural supply and demand projections, which provide a 10-year outlook on U.S. and global agriculture. The macroeconomic projections describe the long-term, 10-year scenario that is used as a benchmark for analyzing the impacts of alternative scenarios and macroeconomic shocks.
Explore the International Macroeconomic Data Set 2015 for annual growth rates, consumer price indices, real GDP per capita, exchange rates, and more. Get detailed projections and forecasts for countries worldwide.
Annual growth rates, Consumer price indices (CPI), Real GDP per capita, Real exchange rates, Population, GDP deflator, Real gross domestic product (GDP), Real GDP shares, GDP, projections, Forecast, Real Estate, Per capita, Deflator, share, Exchange Rates, CPI
Afghanistan, Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Congo, Costa Rica, Croatia, Cuba, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe, WORLD Follow data.kapsarc.org for timely data to advance energy economics research. Notes:
Developed countries/1 Australia, New Zealand, Japan, Other Western Europe, European Union 27, North America
Developed countries less USA/2 Australia, New Zealand, Japan, Other Western Europe, European Union 27, Canada
Developing countries/3 Africa, Middle East, Other Oceania, Asia less Japan, Latin America;
Low-income developing countries/4 Haiti, Afghanistan, Nepal, Benin, Burkina Faso, Burundi, Central African Republic, Chad, Democratic Republic of Congo, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Tanzania, Togo, Uganda, Zimbabwe;
Emerging markets/5 Mexico, Brazil, Chile, Czech Republic, Hungary, Poland, Slovakia, Russia, China, India, Korea, Taiwan, Indonesia, Malaysia, Philippines, Thailand, Vietnam, Singapore
BRIICs/5 Brazil, Russia, India, Indonesia, China; Former Centrally Planned Economies
Former centrally planned economies/7 Cyprus, Malta, Recently acceded countries, Other Central Europe, Former Soviet Union
USMCA/8 Canada, Mexico, United States
Europe and Central Asia/9 Europe, Former Soviet Union
Middle East and North Africa/10 Middle East and North Africa
Other Southeast Asia outlook/11 Malaysia, Philippines, Thailand, Vietnam
Other South America outlook/12 Chile, Colombia, Peru, Bolivia, Paraguay, Uruguay
Indicator Source
Real gross domestic product (GDP) World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service all converted to a 2015 base year.
Real GDP per capita U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table and Population table.
GDP deflator World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.
Real GDP shares U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table.
Real exchange rates U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, CPI table, and Nominal XR and Trade Weights tables developed by the Economic Research Service.
Consumer price indices (CPI) International Financial Statistics International Monetary Fund, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.
Population Department of Commerce, Bureau of the Census, U.S. Department of Agriculture, Economic Research Service, International Data Base.
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TwitterThis dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).
For a more detailed description of the dataset and the coding process, see the codebook available in the .zip-file.
Purpose:
This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).
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Twitterhttps://www.spotzi.com/en/about/terms-of-service/https://www.spotzi.com/en/about/terms-of-service/
This dashboard highlights the regions where the Country Kinetic audience is most present in France. These are families who embrace the charm and energy of rural living-enjoying the simplicity of the countryside, strong family connections, and an active lifestyle close to nature. A perfect audience for brands looking to connect with family-oriented consumers beyond the urban landscape.
This demo dataset is part of our premium plans, giving you access to 27 ready-to-use audience segments built from detailed insights into population density, household types, income levels, and age demographics. Designed for global application, these audiences are ideal for powering international marketing campaigns, market entry strategies, and geo-targeted outreach.
With a free Spotzi account, you can explore a selection of audience segments in Canada, the United States, the United Kingdom, Germany, France, and the Netherlands. Use them to analyze consumer profiles or export these segments — ready to be activated in your next campaign.
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TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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Depicted on this map is British North America less than one hundred years after the fall of New France. It also shows the emergence of British influence prior to Confederation. British North America circa 1823 was comprised of Lower Canada, Upper Canada, New Brunswick, Nova Scotia, Prince Edward Island, and Newfoundland (including the Labrador Coast). The Northwest Territories were considered British possessions, while the Hudson’s Bay Company controlled Rupert’s Land. The United States and Britain jointly administered the Oregon Territory. This map along with New France circa 1740 shows the settlement and population in Canada for two important periods in Canadian history prior to Confederation.
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TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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Depicted on this map is British North America less than one hundred years after the fall of New France. It also shows the emergence of British influence prior to Confederation. British North America circa 1823 was comprised of Lower Canada, Upper Canada, New Brunswick, Nova Scotia, Prince Edward Island, and Newfoundland (including the Labrador Coast). The Northwest Territories were considered British possessions, while the Hudson’s Bay Company controlled Rupert’s Land. The United States and Britain jointly administered the Oregon Territory. This map along with New France circa 1740 shows the settlement and population in Canada for two important periods in Canadian history prior to Confederation.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Year refers to the first year in official trials. Empty cells: year unknown. ID refers to ID in PCA-plot (Figure 4). NG refers to no genotype data.*Breeders varieties and lines have not been assigned accession number. Seeds are available from breeders on request. Some varieties were obtained from IPK gene bank (Gene bank Information System of the IPK Gatersleben) and accession-ID is given in brackets.ASpring variety.
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TwitterMonthly mean surface pseudo-stress using variational, subjective, and objective-subjective techniques in the Indian, Pacific, and Atlantic oceans.
Data from the Joint World Meteorological Organization/Intergovernmental Oceanographic Commission Technical Commision for Oceanography and Marine Meteorology (JCOMM) Products Bulletin Data Products. The organization was formally known as the Integrated Global Ocean Services System (IGOSS) Data Products Bulletin.
For further data products see: http://ingrid.ldeo.columbia.edu/SOURCES/.IGOSS/, http://ingrid.ldeo.columbia.edu/SOURCES/.IGOSS/.data_products.html, and http://iri.ldeo.columbia.edu/climate/monitoring/ipb/.
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TwitterThis two-part data collection comprises information for military expenditures and transfer of armaments for 142 countries in the period 1966-1975. Part 1 consists of time series data that provide information for national military expenditures, including the yearly value of weapons exports and imports per capita, per soldier, and as a percentage of the gross national product (GNP), as well as the population per million. The country and the year form one unit, so that each country appears ten times. Part 2 data provide additional information about the current values of the total arms exported by each major supplier and the total arms transferred in the period 1964-1974 by the United States, France, United Kingdom, Canada, Poland, China, West Germany, the Soviet Union, and Czechoslovakia. (Source: downloaded from ICPSR 7/13/10)
Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR07553.v1. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.
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1Chi2 between France and Canada.2PPH per 100 deliveries.PPH: Postpartum Haemorrhage; CI: Confidence Interval.
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Twitterhttps://www.icpsr.umich.edu/web/ICPSR/studies/34/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/34/terms
This study contains selected demographic, social, economic, public policy, and political comparative data for Switzerland, Canada, France, and Mexico for the decades of 1900-1960. Each dataset presents comparable data at the province or district level for each decade in the period. Various derived measures, such as percentages, ratios, and indices, constitute the bulk of these datasets. Data for Switzerland contain information for all cantons for each decennial year from 1900 to 1960. Variables describe population characteristics, such as the age of men and women, county and commune of origin, ratio of foreigners to Swiss, percentage of the population from other countries such as Germany, Austria and Lichtenstein, Italy, and France, the percentage of the population that were Protestants, Catholics, and Jews, births, deaths, infant mortality rates, persons per household, population density, the percentage of urban and agricultural population, marital status, marriages, divorces, professions, factory workers, and primary, secondary, and university students. Economic variables provide information on the number of corporations, factory workers, economic status, cultivated land, taxation and tax revenues, canton revenues and expenditures, federal subsidies, bankruptcies, bank account deposits, and taxable assets. Additional variables provide political information, such as national referenda returns, party votes cast in National Council elections, and seats in the cantonal legislature held by political groups such as the Peasants, Socialists, Democrats, Catholics, Radicals, and others. Data for Canada provide information for all provinces for the decades 1900-1960 on population characteristics, such as national origin, the net internal migration per 1,000 of native population, population density per square mile, the percentage of owner-occupied dwellings, the percentage of urban population, the percentage of change in population from preceding censuses, the percentage of illiterate population aged 5 years and older, and the median years of schooling. Economic variables provide information on per capita personal income, total provincial revenue and expenditure per capita, the percentage of the labor force employed in manufacturing and in agriculture, the average number of employees per manufacturing establishment, assessed value of real property per capita, the average number of acres per farm, highway and rural road mileage, transportation and communication, the number of telephones per 100 population, and the number of motor vehicles registered per 1,000 population. Additional variables on elections and votes are supplied as well. Data for France provide information for all departements for all legislative elections since 1936, the two presidential elections of 1965 and 1969, and several referenda held in the period since 1958. Social and economic data are provided for the years 1946, 1954, and 1962, while various policy data are presented for the period 1959-1962. Variables provide information on population characteristics, such as the percentages of population by age group, foreign-born, bachelors aged 20 to 59, divorced men aged 25 and older, elementary school students in private schools, elementary school students per million population from 1966 to 1967, the number of persons in household in 1962, infant mortality rates per million births, and the number of priests per 10,000 population in 1946. Economic variables focus on the Gross National Product (GNP), the revenue per capita per household, personal income per capita, income tax, the percentage of active population in industry, construction and public works, transportation, hotels, public administration, and other jobs, the percentage of skilled and unskilled industrial workers, the number of doctors per 10,000 population, the number of agricultural cooperatives in 1946, the average hectares per farm, the percentage of farms cultivated by the owner, tenants, and sharecroppers, the number of workhorses, cows, and oxen per 100 hectares of farmland in 1946, and the percentages of automobiles per 1,000 population, radios per 100 homes, and cinema seats per 1,000 population. Data are also provided on the percentage of Communists (PCF), Socialists, Radical Socialists, Conservatives, Gaullists, Moderates, Poujadists, Independents, Turnouts, and other political groups and p