Our Population Density Grid Dataset for Western Europe offers detailed, grid-based insights into the distribution of population across cities, towns, and rural areas. Free to explore and visualize, this dataset provides an invaluable resource for businesses and researchers looking to understand demographic patterns and optimize their location-based strategies.

By creating an account, you gain access to advanced tools for leveraging this data in geomarketing applications. Perfect for OOH advertising, retail planning, and more, our platform allows you to integrate population insights with your business intelligence, enabling you to make data-driven decisions for your marketing and expansion strategies.

About the Dataset:

1) Regions : - Western Europe - Eastern Europe - Northern Europe - Southern Europe

2) Birth and Death Rate: are in per 1000 People.

This dataset is about countries per year in Western Europe. It has 576 rows. It features 4 columns: country, male population, and urban population.

This dataset is about countries per year in Western Europe. It has 576 rows. It features 4 columns: country, land area, and urban population.

This dataset contains the modeling results GIS data (maps) of the study “Sustainable Human Population Density in Western Europe between 560.000 and 360.000 years ago” by Rodríguez et al. (2022). The NPP data (npp.zip) was computed using an empirical formula (the Miami model) from palaeo temperature and palaeo precipitation data aggregated for each timeslice from the Oscillayers dataset (Gamisch, 2019), as defined in Rodríguez et al. (2022, in review). The Population densities file (pop_densities.zip) contains the computed minimum and maximum population densities rasters for each of the defined MIS timeslices. With the population density value Dc in logarithmic form log(Dc). The Species Distribution Model (sdm.7z) includes input data (folder /data), intermediate results (folder /work) and results and figures (folder /results). All modelling steps are included as an R project in the folder /scripts. The R project is subdivided into individual scripts for data preparation (1.x), sampling procedure (2.x), and model computation (3.x). The habitat range estimation (habitat_ranges.zip) includes the potential spatial boundaries of the hominin habitat as binary raster files with 1=presence and 0=absence. The ranges rely on a dichotomic classification of the habitat suitability with a threshold value inferred from the 5% quantile of the presence data. The habitat suitability (habitat_suitability.zip) is the result of the Species Distribution Modelling and describes the environmental suitability for hominin presence based on the sites considered in this study. The values range between 0=low and 1=high suitability. The dataset includes the mean (pred_mean) and standard deviation (pred_std) of multiple model runs.

The Country-Level Population and Downscaled Projections Based on Special Report on Emissions Scenarios (SRES) A1, B1, and A2 Scenarios, 1990-2100, were adopted in 2000 from population projections realized at the International Institute for Applied Systems Analysis (IIASA) in 1996. The Intergovernmental Panel on Climate Change (IPCC) SRES A1 and B1 scenarios both used the same IIASA "rapid" fertility transition projection, which assumes low fertility and low mortality rates. The SRES A2 scenario used a corresponding IIASA "slow" fertility transition projection (high fertility and high mortality rates). Both IIASA low and high projections are performed for 13 world regions including North Africa, Sub-Saharan Africa, China and Centrally Planned Asia, Pacific Asia, Pacific OECD, Central Asia, Middle East, South Asia, Eastern Europe, European part of the former Soviet Union, Western Europe, Latin America, and North America. This data set is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

The Global Covenant of Mayors for Climate and Energy (GCoM) is the largest dedicated international initiative to promote climate action at city level, covering globally over 10,000 cities and in the European Union almost half the population by end of March 2020. The present dataset refers to a harmonised, complete and verified dataset of GHG inventories for 6,200 cities, signatories of the GCoM initiative as of end of 2019, in the: European Union, EFTA countries and UK, Western Balkans, Eastern and Southern EU neighbourhoods countries. The methodology and the general approach for the data collection can be found in Bertoldi et. al. 2018. Guidebook: How to develop a Sustainable Energy Climate Action Plan (SECAP). (2018) doi:10.2760/223399.

This dataset is about countries per year in Western Europe. It has 576 rows. It features 4 columns: country, life expectancy at birth, and male population.

This is the supporting data file for the manuscript entitled "Higher rate of tuberculosis in second generation migrants compared to native residents in a metropolitan setting in Western Europe" (Marx et al., PLoS ONE). The dataset includes anonymized, routinely collected notification data (variables labeled as "nd") for 314 individuals and anonymized survey data (i.e. data obtained through interviews; variables labeled as "sd") for a subset of 154 individuals. The data are published open-access, in accordance with the PLoS ONE data policy (2014).

This table contains quarterly and yearly figures on labour participation of young people in the Netherlands. The population of 15 to 24 years of age (excluding the institutionalized population) is divided into the employed labour force, the unemployed labour force and those not in the labour force. The employed labour force is subdivided on the basis of the professional status and the average working hours. A division by sex, age and whether they are in education is available.

Data available from: 2003

Status of the figures: The figures in this table are final.

Changes as of 14 May 2019: The quarterly figures for the 1st quarter 2019 are added.

When will new figures be published? New figures will be published six weeks after the end of a quarter of a year.

This study includes data on regional level for nine Western European countries: election returns, occupation categories, religion, population.

This dataset provides a comprehensive list of countries and other inhabited territories around the world, sorted by total population. The population data is based on estimates published by the United Nations in the 2024 revision of the World Population Prospects. It includes population estimates spanning from 1950 to the present, offering insights into global demographic trends over the past several decades.

Dataset Overview

The dataset contains mid-year population estimates from the United Nations for the years 2022 and 2023, reflecting the latest available data for these years. This dataset can be used to analyze population growth patterns, compare population dynamics between countries, or conduct time series analyses of demographic changes.

Key Features

• Population data for countries and territories from 1950 to the present.

• Estimates based on the 2024 revision of the World Population Prospects.

• Mid-year estimates for the years 2022 and 2023.

Column Information

• Country: Name of the country or inhabited territory.

• Population (1 July 2022): The total estimated population as of July 1, 2022.

• Population (1 July 2023): The total estimated population as of July 1, 2023.

• Change: The population change between 2022 and 2023.

• UN Continental Region: The geographical region to which the country or territory belongs (e.g., Africa, Asia, Europe).

• UN Statistical Subregion: A more specific geographical classification within the region (e.g., Eastern Europe, Western Asia).

**Source ** This dataset was downloaded from Wikipedia: List of countries by population (United Nations).

Usage

This dataset is ideal for researchers, data analysts, and anyone interested in understanding global population dynamics through reliable United Nations estimates.

This round of Euro-Barometer surveys investigated life satisfaction, union membership, smoking habits, knowledge and views regarding cancer, views on the importance of NATO and certain national problems, attitudes toward democracy and individual liberties, attitudes toward immigrants and out-groups (i.e., people of another nationality, race, religion, culture, or social class), and knowledge of and attitudes toward European Community institutions and policies, including the Common Agricultural Policy and the creation of a single European market in 1992. Respondents also were asked to name current topics and events most important for them and to state whether or not certain causes such as the protection of wildlife and the promotion of world peace were worth taking risks and making sacrifices for. Questions on political party preferences asked respondents which party they felt the closest to, how they voted in their country's last general election, how they would vote if a general election were held tomorrow, and how they planned to vote in the June 1989 elections for the European Parliament. The survey also gauged respondents' perceptions of the general attitude of each country's political parties toward the European Community. The inquiry into out-groups asked respondents to identify groups that came to mind when they thought of people of another nationality, race, religion, culture, or social class. Respondents were asked if they counted any out-group members among their friends and if any of these persons worked at their place of employment or lived in their neighborhood. Additional questions asked respondents if they were disturbed by the presence of these out-groups and if they thought that these groups exploited social welfare benefits, increased unemployment, contributed to delinquency and violence, affected property prices, or reduced the level of education in schools. In West Germany, France, Great Britain, and the Netherlands, respondents were queried about their attitudes and feelings toward specific out-groups: Southern Europeans, North Africans, Turks, Black Africans, Asians, Southeast Asians, West Indians, Jews, Surinamers, and Northern Europeans. The section on cancer queried respondents about their knowledge of the causes of cancer and medical recommendations for its early detection and prevention, and asked respondents if they followed or intended to follow those recommendations. Additional information gathered includes family income, home ownership, number of persons and children under 15 residing in the home, size of locality, region of residence, occupation of the head of household, and the respondent's age, sex, occupation, education, religion, religiosity, subjective social class standing, and left-right political self-placement. (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/ICPSR09321.v3. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

Population by country of birth Source: Census 2001 Publisher: Neighbourhood Statistics Geographies: Output Area (OA), Lower Layer Super Output Area (LSOA), Middle Layer Super Output Area (MSOA), Ward, Local Authority District (LAD), Government Office Region (GOR), National Geographic coverage: England and Wales Time coverage: 2001 Type of data: Survey (census) Notes: The country of birth question in the 2001 Census had five tick box responses: one each for the four parts of the UK and one for the Republic of Ireland. Where there was no applicable tick box, people were asked to write in the present name of their country of birth. The written responses were coded using the ONS Geography Classification of Countries. Countries are classified geographically not politically. For example, the Canary Islands are classified as North Africa rather than Western Europe even though they belong to Spain.

Explore detailed global homicide data with this extensive dataset, covering various aspects of intentional homicides. Compiled from multiple reliable sources, including UNODC and WHO, this dataset includes:

• Child homicide rates per 100,000 population
• Distribution of homicide rates
• Female homicide rates and victims
• Age-standardized homicide rates
• Historical homicide rates across Western Europe
• Overall homicide rates and victims

This dataset provides valuable insights for researchers, policymakers, and data scientists interested in crime analysis, public health, and social studies. Analyze trends, identify patterns, and develop predictive models to understand and mitigate the impact of homicides worldwide.

Air pollution globalization, as a combined effect of atmospheric transport and international trade, can lead to notable transboundary health impacts. Life expectancy reduction attribution analysis of transboundary pollution can reveal the effect of pollution globalization on the lives of individuals. This study coupled five state-of-the-art models to link the regional per capita life expectancy reduction to cross-boundary pollution transport attributed to consumption in other regions. Our results revealed that pollution due to consumption in other regions contributed to a global population-weighted PM2.5 concentration of 9 μg/m3 in 2017, thereby causing 1.03 million premature deaths and reducing the global average life expectancy by 0.23 year (≈84 days). Trade-induced transboundary pollution relocation led to a significant reduction in life expectancy worldwide (from 5 to 155 days per person), and even in the least polluted regions, such as North America, Western Europe, and Russia, a 12–61-day life expectancy reduction could be attributed to consumption in other regions. Our results reveal the individual risks originating from air pollution globalization. To protect human life, all regions and residents worldwide should jointly act together to reduce atmospheric pollution and its globalization as soon as possible.

A multitude of smart phone and more traditional tools are used with increasing frequency by volunteers on roads for long-term monitoring of wildlife. Data collected by volunteers on roads has recently indicated large-scale declines of some widespread amphibians in Western Europe. However, it is unclear how representative such data are or not in relation to the actual species distribution. Spatial biases could skew results towards more urbanised areas and consequently produce incorrect or partial trend estimations at regional or national scales. Our objective was to compare and verify potential spatial biases of road based data using distribution datasets of different origins. As a case study, we used the common toad (Bufo bufo), a fast-declining species and the main amphibian targeted by conservation action on roads in Europe. We calculated ecological niche models with the built used Maxent models to compare road survey data obtained from the UK flagship, 35 year-long “Toads on Roads” project, containing almost 2 million amphibian records, in Great Britain with models using national-scale toad distribution records in Great Britain as well as with models using randomly generated points on roads. Road based distribution models that used data collected by volunteers on roads produced similar results to those obtained from overall species distribution, indicating the lack of selection bias and a high spatial coverage of volunteer-collected data on roads. Toads were present in most parts of the country but were generally absent from mountainous areas and, despite the high availability of potential recorders, showed nearly complete absence in large urban areas. To our knowledge, this is the first study that comparatively evaluates species distribution models created using datasets of different origin in order to verify the influence of potential spatial bias of data collected by volunteers on roads. We show that for countries with high road density road network coverage, such as Great Britain, road based data collected by volunteers represent a robust dataset in terms of coverage and a critical citizen science contribution to conservation.

Our Europe Zip Code Database offers comprehensive postal code data for spatial analysis, including postal and administrative areas for numerous European countries. This dataset contains accurate and up-to-date information on all administrative divisions, cities, and zip codes, making it an invaluable resource for various applications such as address capture and validation, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including CSV, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Product features include fully and accurately geocoded data, multi-language support with address names in local and foreign languages, comprehensive city definitions, and the option to combine map data with UNLOCODE and IATA codes, time zones, and daylight saving times. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

Published as part of Health in Ireland: Key Trends 2016 (Department of Health)

Icelandic cattle is believed to have been brought from Norway during the settlement of Iceland around AD 870-930. Previous research on genetic relationships has indicated that Icelandic cattle is most related to northern Nordic indigenous breeds. Using single nucleotide polymorphism genotype data from Icelandic cattle and 29 Northern and Western European cattle breeds, we studied relationships and admixture among these breeds, and assessed population structure in Icelandic cattle. Population structure analysis through principal component analysis, estimation of ancestry, and analysis of patterns of population splitting and mixing revealed that Icelandic cattle are most related to three Finncattle breeds (Eastern, Northern and Western Finncattle), and Swedish Mountain cattle. Icelandic cattle has very low levels of admixture. We observed very limited population structure in Icelandic cattle. The observed structure was due to variable sire contributions. Over 1000 years of almost complete isolation has made Icelandic cattle highly genetically distinct from other cattle breeds.