This dataset contains a small sample of demographic information including names, ages, and cities. It is designed as a demonstration dataset for educational purposes, showcasing basic demographic data structure with three individuals from different major US cities. The dataset includes:

• Name: Individual names (John, Jane, Bob)
• Age: Ages ranging from 20-30 years
• City: Major US cities (New York, Los Angeles, Chicago)

This synthetic dataset can be used for learning basic data analysis techniques, practicing data visualization, or as a starting point for demographic analysis tutorials.

"Ratio of Homeless Population to General Population in major US Cities in 2010. *This represents a list of large U.S. cities for which DHS was able to confirm a recent estimate of the unsheltered population. A 2010 result is only available for Seattle, WA. Other cities either did not conduct a count in 2010, or their 2010 results are not yet available. 2009 unsheltered census figures were used for Los Angeles, San Francisco, Miami, and Washington, DC, and Boston; the 2007 estimate is used for Chicago. General population figures are the latest estimates from the U.S. Census Bureau."

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DAY ~17,000 (January 1976 to December 2022)

This is a dataset that tracks relevant population statistics and employment rates per US state since 1976.

All data are official figures from the Bureau of Labor Statistics that have been compiled and structured by myself. Besides the 50 US states, the unemployment data of three other areas are also being tracked in order to increase the analytical potential of the dataset: the District of Columbia, the Los Angeles-Long Beach-Glendale metropolitan division, and New York City.

Why did I create this dataset? Employment continues to be a significant issue in America today and contributes to other predicaments such as the homelessness crisis. By uploading time-series data regarding American unemployment over the past four decades, I hope that the community is able to determine the various statistical trends offered. In my personal opinion, achieving a quantitative yet objective viewpoint of a subject such as unemployment is crucial to understanding the issues at hand.

Data Sources

The primary data source used was the Bureau of Labor Statistics's official website, which publishes employment data pertaining to America. Considering the meticulous documentation of federal statistics by such a accredited government agency, no other authority is more equipped to provide insight on US unemployment.

1. The Bureau of Labor Statistics's Economic News Release on (Monthly) State Employment and Unemployment - The Bureau of Labor Statistics has published monthly updates on unemployment rates since January 1976.
2. The Bureau of Labor Statistics's State Employment and Unemployment Technical Note - The Bureau of Labor Statistics released a detailed overview of their unemployment data, the methodology behind their data, and the proper definitions and terminologies for the variables tracked. The guide mainly provided essential contextual knowledge needed to create a meaningful dataset.

Statistics Being Tracked

• FIPS Code of State/Area
• Year/Month of Statistic
• Total Civilian Non-Institutional Population in State/Area
• Total Civilian Labor Force in State/Area
• Percent (%) of State/Area's Population
• Total Employment in State/Area
• Percent (%) of Labor Force Employed in State/Area
• Total Unemployment in State/Area
• Percent (%) of Labor Force Unemployed in State/Area

Dataset History

2023-03-01 - Dataset is created (17,227 days after temporal coverage start date).

GitHub Repository - The same data but on GitHub.

Code Starter

Link to Notebook

Datasets supporting findings and visualizations behind McManamay et al. (2024) Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways. Environmental Research Letters, DOI: 10.1088/1748-9326/ad2eec Using a spatial modeling experiment at high resolution (1-km), this study compared how two alternative US population projections, varying in the spatially explicit nature of demographic patterns and migration, affect urban land dynamics simulated by the Spatially Explicit, Long-term, Empirical City development (SELECT) model for SSP2, SSP3, and SSP5. The numerical experiment, inputs and outputs are fully described in McManamay et al. (2024). The datasets summarize SELECT model simulations within urban areas and rural areas of the conterminous United States. For code to reproduce the results, please refer to https://github.com/IMMM-SFA/mcmanamay_etal_2024_erl Please refer to the README file provided in Files for more details. Descriptions of the datasets are provided below. Dataset(s) Descriptions: Urban_Land_delta_UA_County.csv: Urban land area for original (default) population, updated population, and urban land delta (difference between the two) according to Shared Socioeconomic Pathways (SSPs) and year. Urban land is summarized for U.S. counties (FIPS code) and urban areas (GEOID) as unique areas within various counties. JO_Gao_pop_ufdelta.csv: Comparison of population differences and urban land differences between the origial (default) and updated population projections. City_Case_studies.csv: Differences in urban land areas arising from different population projections summarized for selected cities (Atlanta, Los Angeles, Houston, and New York) and their surrounding rural areas UA_county_FID.zip: Zipped folder of .tiff file depicting unique combination of urban areas and US counties used for summarizing urban land differences in urban and rural areas based on different population projections. ULD_clusters.zip: Zipped folder of .csv files depicting normalized changes in urban land delta (difference in urban land arising from population projections) and the respective Ward's hierarchical clusters, which group urban and rural areas based on similarities in temporal trends. Urban_Percent_change_2100.zip: Zipped folder of .csv files depicting percent changes in urban land area for year 2100 based on differences in the original (default) population and updated population. Each file is for SSPs and urban or rural areas.

Dataset with average and minimum Effectiveness scores and light exposure data for hypothetical work and school schedules in autumn, winter, spring and summer months in the cities of: New York City, NY; Chicago, IL; El Paso, TX; Los Angeles, CA; Anchorage, AK, as well as information about latitude, longitude, population, highway fatality rate, and sunrise/sunset times per city.

This dataset supports the manuscript Lawful Handgun Licensing, Population Density, Poverty, Police Staffing, and Violent Crime: A Two-Cohort Comparison of U.S. Jurisdictions (2023–2024). It contains processed violent crime counts, rates per 100,000, population denominators, poverty statistics, and police staffing levels for two cohorts of U.S. jurisdictions. Cohort A includes counties with high levels of licensed handgun ownership (Brevard FL, Macomb MI, Genesee MI, Sumner TN, Sullivan TN, Pierce WA). Cohort B includes restrictive licensing jurisdictions (New York City, Los Angeles, San Francisco, Washington DC, Boston). The package includes: County/city-level violent crime counts for homicide, rape, robbery, and aggravated assault (2023–2024). Population denominators (2024 Census estimates). Derived violent crime rates per 100,000. Poverty measures and law enforcement officer staffing rates. Python replication script to regenerate tables and figures used in the study. Accessed data sources: FBI Crime Data Explorer, Major Cities Chiefs Association, NYPD annual tables, FDLE FIBRS, Michigan MICR, Tennessee Bureau of Investigation, Washington Association of Sheriffs and Police Chiefs, and U.S. Census QuickFacts. Data pulled on August 27, 28, and 30, 2025.

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.

Colonization of a novel environment by a small group of individuals can lead to rapid evolutionary change, yet evidence of the relative contributions of neutral and selective factors in promoting divergence during the early stages of colonization remain scarce. Here, we use genome-wide SNP data to test the role of neutral and selective forces in driving the divergence of a unique urban population of the Oregon junco (Junco hyemalis oreganus), which became established on the campus of the University of California at San Diego (UCSD) in the early 1980s. Previous studies based on microsatellite loci documented significant genetic differentiation of the urban population as well as divergence in sexual signaling and life-history traits relative to nearby montane populations. However, the geographic origin of the colonization and the factors involved in the onset of the differentiation process remained uncertain. Our genome-wide SNP dataset confirmed the marked genetic differentiation of the UCSD population, and phylogenomic analysis identified the coastal subspecies pinosus from central California as its sister group instead of the neighboring mountain population. Demographic inference based on site frequency spectra recovered a time of separation from pinosus as recent as 20 to 32 generations, and a strong bottleneck at the time of colonization, suggesting a relevant role of founder effects and drift in the genetic differentiation of the UCSD population. However, we also found significant associations between environmental parameters characterizing the urban habitat of UCSD and genome-wide variants linked to functional genes. Some of the identified gene functions, like heavy metal detoxification and high-pitched hearing, have been reported as potentially adaptive in birds inhabiting urban environments. These results suggest that the interplay between founder events and directional selection may result in rapid shifts in both neutral and adaptive loci across the genome, and reveal the UCSD population of juncos as an ongoing case of divergence following the colonization of an anthropic environment. Methods All methods and protocols are described in detail in the article.

Integral projection models (IPMs) can estimate the population dynamics of species for which both discrete life stages and continuous variables influence demographic rates. Stochastic IPMs for imperiled species, in turn, can facilitate population viability analyses (PVAs) to guide conservation decision-making. Biphasic amphibians are globally distributed, often highly imperiled, and ecologically well-suited to the IPM approach. Herein, we present the first stochastic size- and stage-structured IPM for a biphasic amphibian, the U.S. federally threatened California tiger salamander (Ambystoma californiense; CTS). This Bayesian model reveals that CTS population dynamics show the greatest elasticity to changes in juvenile and metamorph growth and that populations are likely to experience rapid growth at low density. We integrated this IPM with climatic drivers of CTS demography to develop a PVA and examined CTS extinction risk under the primary threats of habitat loss and climate change. The PVA indicates that long-term viability is possible with surprisingly high (20–50%) terrestrial mortality, but simultaneously identified likely minimum terrestrial buffer requirements of 600–1000 m while accounting for numerous parameter uncertainties through the Bayesian framework. These analyses underscore the value of stochastic and Bayesian IPMs for understanding both climate-dependent taxa and those with cryptic life histories (e.g., biphasic amphibians) in service of ecological discovery and biodiversity conservation. In addition to providing guidance for CTS recovery, the contributed IPM and PVA supply a framework for applying these tools to investigations of ecologically-similar species. Methods Please see the associated manuscript for full methodological details.