9 datasets found
  1. M

    Los Angeles Metro Area Population 1950-2025

    • macrotrends.net
    csv
    Updated Feb 28, 2025
    + more versions
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    MACROTRENDS (2025). Los Angeles Metro Area Population 1950-2025 [Dataset]. https://www.macrotrends.net/global-metrics/cities/23052/los-angeles/population
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    csvAvailable download formats
    Dataset updated
    Feb 28, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1950 - Mar 18, 2025
    Area covered
    Greater Los Angeles, United States
    Description

    Chart and table of population level and growth rate for the Los Angeles metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

  2. Toronto Neighborhood Data

    • kaggle.com
    Updated Jul 5, 2021
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    Sidharth Kumar Mohanty (2021). Toronto Neighborhood Data [Dataset]. https://www.kaggle.com/sidharth178/toronto-neighborhood-data/tasks
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 5, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Sidharth Kumar Mohanty
    Area covered
    Toronto
    Description

    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.

  3. n

    Coronavirus (Covid-19) Data in the United States

    • nytimes.com
    • openicpsr.org
    • +3more
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html
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    Dataset provided by
    New York Times
    Description

    The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

    Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

    We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

    The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

  4. w

    Directory Of Unsheltered Street Homeless To General Population Ratio 2010

    • data.wu.ac.at
    • data.cityofnewyork.us
    • +2more
    csv, json, rdf, xml
    Updated Jan 31, 2018
    + more versions
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    City of New York (2018). Directory Of Unsheltered Street Homeless To General Population Ratio 2010 [Dataset]. https://data.wu.ac.at/schema/data_gov/ODNjNmNkMDEtNmQ5Yi00YjliLTg0ZGYtMWI5MThhNzdiY2M5
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    xml, csv, json, rdfAvailable download formats
    Dataset updated
    Jan 31, 2018
    Dataset provided by
    City of New York
    Description

    "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."

  5. Data from: Rapid evolutionary divergence of a songbird population following...

    • data.niaid.nih.gov
    zip
    Updated Apr 3, 2022
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    Guillermo Friis; Jonathan Atwell; Adam Fudickar; Timothy Greives; Pamela Yeh; Trevor Price; Ellen Ketterson; Borja Milá (2022). Rapid evolutionary divergence of a songbird population following recent colonization of an urban area [Dataset]. http://doi.org/10.5061/dryad.gf1vhhmpv
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    zipAvailable download formats
    Dataset updated
    Apr 3, 2022
    Dataset provided by
    University of California, Los Angeles
    Indiana University
    Consejo Superior de Investigaciones Científicas
    New York University Abu Dhabi
    North Dakota State University
    University of Chicago
    Authors
    Guillermo Friis; Jonathan Atwell; Adam Fudickar; Timothy Greives; Pamela Yeh; Trevor Price; Ellen Ketterson; Borja Milá
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    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.

  6. Evaluation of Hung Juries in Bronx County, New York, Los Angeles County,...

    • icpsr.umich.edu
    • catalog.data.gov
    ascii, sas, spss +1
    Updated Mar 30, 2006
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    Hannaford-Agor, Paula L.; Hans, Valerie P.; Mott, Nicole L.; Munsterman, G. Thomas (2006). Evaluation of Hung Juries in Bronx County, New York, Los Angeles County, California, Maricopa County, Arizona, and Washington, DC, 2000-2001 [Dataset]. http://doi.org/10.3886/ICPSR03689.v1
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    sas, spss, stata, asciiAvailable download formats
    Dataset updated
    Mar 30, 2006
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Hannaford-Agor, Paula L.; Hans, Valerie P.; Mott, Nicole L.; Munsterman, G. Thomas
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/3689/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/3689/terms

    Time period covered
    2000 - 2001
    Area covered
    California, Washington, United States, Arizona, New York (state)
    Description

    This study was undertaken for the purpose of providing an empirical picture of hung juries. Researchers were able to secure the cooperation of four courts: (1) Bronx County Supreme Court in New York, (2) Los Angeles County Superior Court in California, (3) Maricopa County Superior Court in Arizona, and (4) District of Columbia Superior Court in Washington, DC. The four sites were responsible for distributing and collecting questionnaire packets to all courtrooms hearing non-capital felony jury cases. Each packet contained a case data form requesting information about case characteristics (Part 1) and outcomes (Part 2), as well as survey questionnaires for the judges (Part 3), attorneys (Part 4), and jurors (Part 5). The case data form requested type of charge, sentence range, jury's decision, demographic information about the defendant(s) and the victim(s), voir dire (jury selection process), trial evidence and procedures, and jury deliberations. The judge questionnaire probed for evaluation of the evidence, case complexity, attorney skill, likelihood that the jury would hang, reaction to the verdict, opinions regarding the hung jury rate in the jurisdiction, and experience on the bench. The attorney questionnaire requested information assessing the voir dire, case complexity, attorney skill, evaluation of the evidence, reaction to the verdict, opinions regarding the hung jury rate in the jurisdiction, and experience in legal practice. If the jury hung, attorneys also provided their views about why the jury was unable to reach a verdict. Finally, the juror questionnaire requested responses regarding case complexity, attorney skill, evaluation of the evidence, formation of opinions, dynamics of the deliberations including the first and final votes, juror participation, conflict, reaction to the verdict, opinions about applicable law, assessment of criminal justice in the community, and demographic information.

  7. d

    Use of Force department data

    • data.world
    csv, zip
    Updated Mar 8, 2024
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    NJ Advance Data Team (2024). Use of Force department data [Dataset]. https://data.world/njdotcom/use-of-force-department-data
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    csv, zipAvailable download formats
    Dataset updated
    Mar 8, 2024
    Authors
    NJ Advance Data Team
    Description

    This is five years of police use of force data for all 468 New Jersey municipal police departments and the New Jersey State Police compiled by NJ Advance Media for The Force Report.

    When police punch, pepper spray or use other force against someone in New Jersey, they are required to fill out a form detailing what happened. NJ Advance Media filed 506 public records requests and received 72,607 forms covering 2012 through 2016. For more data collection details, see our Methodology here. Data cleaning details can be found here.

    We then cleaned, analyzed and compiled the data by department to get a better look at what departments were using the most force, what type of force they were using, and who they were using it on. The result, our searchable database, can be found at NJ.com/force. But we wanted to make department-level results — our aggregate data — available in another way to the broader public.

    Below you'll find two files:

    • UOF_BY_DEPARTMENTS.csv, with every department's summary data, including the State Police. (This is important to note because the State Police patrols multiple towns and may not be comparable to other departments.)
    • UOF_STATEWIDE.csv, a statewide summary of the same data.

    For more details on individual columns, see the data dictionary for UOF_BY_DEPARTMENTS. We have also created sample SQL queries to make it easy for users to quickly find their town or county.

    It's important to note that these forms were self-reported by police officers, sometimes filled out by hand, so even our data cleaning can't totally prevent inaccuracies from cropping up. We've also included comparisons to population data (from the Census) and arrest data (from the FBI Uniform Crime Report), to try to help give context to what you're seeing.

    What about the form-level data?

    We have included individual incidents on each department page, but we are not publishing the form-level data freely to the public. Not only is that data extremely dirty and difficult to analyze — at least, it took us six months — but it contains private information about subjects of force, including minors and people with mental health issues. However, we are planning to make a version of that file available upon request in the future.

    Data analysis FAQ

    What are rows? What are incidents?
    Every time any police officer uses force against a subject, they must fill out a form detailing what happened and what force they used. But sometimes multiple police officers used force against the same subject in the same incident. "Rows" are individual forms officers filled out, "incidents" are unique incidents based on the incident number and date.

    What are the odds ratios, and how did you calculate them?
    We wanted a simple way of showing readers the disparity between black and white subjects in a particular town. So we used an odds ratio, a statistical method often used in research to compare the odds of one thing happening to another. For population, the calculation was (Number of black subjects/Total black population of area)/(Number of white subjects/Total white population of area). For arrests, the calculation was (Number of black subjects/Total number of black arrests in area)/(Number of white subjects/Total number of white arrests in area). In addition, when we compared anything to arrests, we took out all incidents where the subject was an EDP (emotionally disturbed person).

    What are the NYC/LA/Chicago warning systems?
    Those three departments each look at use of force to flag officers if they show concerning patterns, as way to select those that could merit more training or other action by the department. We compared our data to those three systems to see how many officers would trigger the early warning systems for each. Here are the three systems: - In New York City, officers are flagged for review if they use higher levels of force — including a baton, Taser or firearm, but not pepper spray — or if anyone was injured or hospitalized. We calculated this number by identifying every officer who met one or more of the criteria. - In Los Angeles, officers are compared with one another based on 14 variables, including use of force. If an officer ranks significantly higher than peers for any of the variables — technically, 3 standards of deviation from the norm — supervisors are automatically notified. We calculated this number conservatively by using only use of force as a variable over the course of a calendar year. - In Chicago, officers are flagged for review if force results in an injury or hospitalization, or if the officer uses any level of force above punches or kicks. We calculated this number by identifying every officer who met one or more of the criteria.

    What are the different levels of force?
    Each officer was required to include in the form what type of force they used against a subject. We cleaned and standardized the data to major categories, although officers could write-in a different type of force if they wanted to. Here are the major categories: - Compliance hold: A compliance hold is a painful maneuver using pressure points to gain control over a suspect. It is the lowest level of force and the most commonly used. But it is often used in conjunction with other types of force. - Takedown: This technique is used to bring a suspect to the ground and eventually onto their stomach to cuff them. It can be a leg sweep or a tackle. - Hands/fist: Open hands or closed fist strikes/punches. - Leg strikes: Leg strikes are any kick or knee used on a subject. - Baton: Officers are trained to use a baton when punches or kicks are unsuccessful. - Pepper spray: Police pepper spray, a mist derived from the resin of cayenne pepper, is considered “mechanical force” under state guidelines. - Deadly force: The firing of an officer's service weapon, regardless of whether a subject was hit. “Warning shots” are prohibited, and officers are instructed not to shoot just to maim or subdue a suspect.

  8. f

    Site Descriptions—Biogeophysical variables for the seven study cities.

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Kirsten Schwarz; Michail Fragkias; Christopher G. Boone; Weiqi Zhou; Melissa McHale; J. Morgan Grove; Jarlath O’Neil-Dunne; Joseph P. McFadden; Geoffrey L. Buckley; Dan Childers; Laura Ogden; Stephanie Pincetl; Diane Pataki; Ali Whitmer; Mary L. Cadenasso (2023). Site Descriptions—Biogeophysical variables for the seven study cities. [Dataset]. http://doi.org/10.1371/journal.pone.0122051.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Kirsten Schwarz; Michail Fragkias; Christopher G. Boone; Weiqi Zhou; Melissa McHale; J. Morgan Grove; Jarlath O’Neil-Dunne; Joseph P. McFadden; Geoffrey L. Buckley; Dan Childers; Laura Ogden; Stephanie Pincetl; Diane Pataki; Ali Whitmer; Mary L. Cadenasso
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Population and demographics from American FactFinder (factfinder.census.gov). Climate data from NOAA 1980–2010 Climate Normals: http://cdo.ncdc.noaa.gov/cgi-bin/climatenormals/climatenormals.plhttp://www.ncdc.noaa.gov/oa/climate/normals/usnormals.html*Calculated as the number of days in between the median freeze days in fall and spring for each location.Site Descriptions—Biogeophysical variables for the seven study cities.

  9. Data from: Uniform Crime Reports: Monthly Weapon-Specific Crime and Arrest...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
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    Bureau of Justice Statistics (2025). Uniform Crime Reports: Monthly Weapon-Specific Crime and Arrest Time Series, 1975-1993 [National, State, and 12-City Data] [Dataset]. https://catalog.data.gov/dataset/uniform-crime-reports-monthly-weapon-specific-crime-and-arrest-time-series-1975-1993-natio-09efd
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Description

    These data were prepared in conjunction with a project using Bureau of Labor Statistics data (not provided with this collection) and the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program data to examine the relationship between unemployment and violent crime. Three separate time-series data files were created as part of this project: a national time series (Part 1), a state time series (Part 2), and a time series of data for 12 selected cities: Baltimore, Buffalo, Chicago, Columbus, Detroit, Houston, Los Angeles, Newark, New York City, Paterson (New Jersey), and Philadelphia (Part 3). Each data file was constructed to include 82 monthly time series: 26 series containing the number of Part I (crime index) offenses known to police (excluding arson) by weapon used, 26 series of the number of offenses cleared by arrest or other exceptional means by weapon used in the offense, 26 series of the number of offenses cleared by arrest or other exceptional means for persons under 18 years of age by weapon used in the offense, a population estimate series, and three date indicator series. For the national and state data, agencies from the 50 states and Washington, DC, were included in the aggregated data file if they reported at least one month of information during the year. In addition, agencies that did not report their own data (and thus had no monthly observations on crime or arrests) were included to make the aggregated population estimate as close to Census estimates as possible. For the city time series, law enforcement agencies with jurisdiction over the 12 central cities were identified and the monthly data were extracted from each UCR annual file for each of the 12 agencies. The national time-series file contains 82 time series, the state file contains 4,083 time series, and the city file contains 963 time series, each with 228 monthly observations per time series. The unit of analysis is the month of observation. Monthly crime and clearance totals are provided for homicide, negligent manslaughter, total rape, forcible rape, attempted forcible rape, total robbery, firearm robbery, knife/cutting instrument robbery, other dangerous weapon robbery, strong-arm robbery, total assault, firearm assault, knife/cutting instrument assault, other dangerous weapon assault, simple nonaggravated assault, assaults with hands/fists/feet, total burglary, burglary with forcible entry, unlawful entry-no force, attempted forcible entry, larceny-theft, motor vehicle theft, auto theft, truck and bus theft, other vehicle theft, and grand total of all actual offenses.

  10. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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MACROTRENDS (2025). Los Angeles Metro Area Population 1950-2025 [Dataset]. https://www.macrotrends.net/global-metrics/cities/23052/los-angeles/population

Los Angeles Metro Area Population 1950-2025

Los Angeles Metro Area Population 1950-2025

Explore at:
csvAvailable download formats
Dataset updated
Feb 28, 2025
Dataset authored and provided by
MACROTRENDS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Dec 31, 1950 - Mar 18, 2025
Area covered
Greater Los Angeles, United States
Description

Chart and table of population level and growth rate for the Los Angeles metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

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