88 datasets found
  1. d

    Washington DC Boundary

    • catalog.data.gov
    • opendata.dc.gov
    • +2more
    Updated Feb 4, 2025
    + more versions
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    D.C. Office of the Chief Technology Officer (2025). Washington DC Boundary [Dataset]. https://catalog.data.gov/dataset/washington-dc-boundary
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    D.C. Office of the Chief Technology Officer
    Area covered
    Washington
    Description

    District of Columbia boundary. The dataset is a polygon representing the District of Columbia boundary, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. The boundary was identified from public records and heads-up digitized using a combination of the 1995 orthophotographs, planimetric roads features, and the USGS digital raster graphic quad sheets, and 1999 planimetrics for the Potomac River boundary.Also see the District's Boundary Stone markers.

  2. d

    DC COVID-19 Metropolitan Police Department

    • datasets.ai
    • opendata.dc.gov
    • +2more
    15, 21, 3, 8
    Updated Mar 2, 2022
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    District of Columbia (2022). DC COVID-19 Metropolitan Police Department [Dataset]. https://datasets.ai/datasets/dc-covid-19-metropolitan-police-department
    Explore at:
    15, 3, 21, 8Available download formats
    Dataset updated
    Mar 2, 2022
    Dataset authored and provided by
    District of Columbia
    Area covered
    Washington
    Description

    On March 2, 2022 DC Health announced the District’s new COVID-19 Community Level key metrics and reporting. COVID-19 cases are now reported on a weekly basis. District of Columbia Metropolitan Police Department testing for the number of positive tests, quarantined, returned to work and lives lost. Due to rapidly changing nature of COVID-19, data for March 2020 is limited.

    General Guidelines for Interpreting Disease Surveillance Data

    During a disease outbreak, the health department will collect, process, and analyze large amounts of information to understand and respond to the health impacts of the disease and its transmission in the community. The sources of disease surveillance information include contact tracing, medical record review, and laboratory information, and are considered protected health information. When interpreting the results of these analyses, it is important to keep in mind that the disease surveillance system may not capture the full picture of the outbreak, and that previously reported data may change over time as it undergoes data quality review or as additional information is added. These analyses, especially within populations with small samples, may be subject to large amounts of variation from day to day. Despite these limitations, data from disease surveillance is a valuable source of information to understand how to stop the spread of COVID19.

  3. d

    Post Offices

    • catalog.data.gov
    • datasets.ai
    • +3more
    Updated May 7, 2025
    + more versions
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    City of Washington, DC (2025). Post Offices [Dataset]. https://catalog.data.gov/dataset/post-offices-41d22
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    Dataset updated
    May 7, 2025
    Dataset provided by
    City of Washington, DC
    Description

    The dataset contains locations and attributes of Post Offices, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Information provided by the United States Postal Service (USPS) and DC GIS staff geo-processed the data.

  4. N

    Washington, DC Population Breakdown by Gender Dataset: Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
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    Neilsberg Research (2025). Washington, DC Population Breakdown by Gender Dataset: Male and Female Population Distribution // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/b25ac960-f25d-11ef-8c1b-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Washington
    Variables measured
    Male Population, Female Population, Male Population as Percent of Total Population, Female Population as Percent of Total Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the population of Washington by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Washington across both sexes and to determine which sex constitutes the majority.

    Key observations

    There is a slight majority of female population, with 52.39% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Scope of gender :

    Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

    Variables / Data Columns

    • Gender: This column displays the Gender (Male / Female)
    • Population: The population of the gender in the Washington is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each gender as a proportion of Washington total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Washington Population by Race & Ethnicity. You can refer the same here

  5. N

    Washington, DC Census Bureau Gender Demographics and Population Distribution...

    • neilsberg.com
    Updated Feb 19, 2024
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    Neilsberg Research (2024). Washington, DC Census Bureau Gender Demographics and Population Distribution Across Age Datasets [Dataset]. https://www.neilsberg.com/research/datasets/e1afc537-52cf-11ee-804b-3860777c1fe6/
    Explore at:
    Dataset updated
    Feb 19, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Washington
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the Washington population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of Washington.

    Content

    The dataset constitues the following two datasets across these two themes

    • Washington, DC Population Breakdown by Gender
    • Washington, DC Population Breakdown by Gender and Age

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

  6. d

    Crashes in DC

    • visionzero.dc.gov
    • datasets.ai
    • +4more
    Updated Jun 9, 2017
    + more versions
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    City of Washington, DC (2017). Crashes in DC [Dataset]. https://visionzero.dc.gov/datasets/crashes-in-dc/about
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    Dataset updated
    Jun 9, 2017
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    Crashes on the roadway blocks network of Washington, DC maintained by the District Department of Transportation (DDOT). In addition to locations, a related table consisting of crash details is available for each crash. This table provides some anonymized information about each of the persons involved in the crash (linked by CRASHID). These crash data are derived from the Metropolitan Police Department's (MPD) crash data management system (COBALT) and represent DDOT's attempt to summarize some of the most requested elements of the crash data. Further, DDOT has attempted to enhance this summary by locating each crash location along the DDOT roadway block line, providing a number of location references for each crash. In the event that location data is missing or incomplete for a crash, it is unable to be published within this dataset. Location points with some basic summary statistics,The DC ward the crash occurredSummary totals for: injuries (minor, major, fatal) by type (pedestrian, bicycle, car), mode of travel involved (pedestrian, bicycle, car), impaired participants (pedestrian, bicyclist, car passengers)If speeding was involvedNearest intersecting street nameDistance from nearest intersectionCardinal direction from the intersectionRead more at https://ddotwiki.atlassian.net/wiki/spaces/GIS0225/pages/2053603429/Crash+Data. Questions on the contents of these layers should be emailed to Metropolitan Police Department or the DDOT Traffic Safety Division. Questions regarding the Open Data DC can be sent to @OpenDataDC

  7. ABC News/Washington Post Education Poll, September 1981

    • icpsr.umich.edu
    ascii, sas, spss
    Updated Feb 16, 1992
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    Inter-university Consortium for Political and Social Research [distributor] (1992). ABC News/Washington Post Education Poll, September 1981 [Dataset]. http://doi.org/10.3886/ICPSR08018.v1
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    sas, spss, asciiAvailable download formats
    Dataset updated
    Feb 16, 1992
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/8018/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/8018/terms

    Time period covered
    Sep 1981
    Area covered
    United States
    Description

    This special-topic poll is part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. This data collection focuses on perceptions of education in the United States. The poll consisted of interviews with school principals and the general population. The data are contained in two datasets. Part 1, Principals Survey, contains data on the number and racial mix of students in the respondents' schools. Respondents were also questioned about discipline problems, competency tests, busing to achieve integration, television and homework, parental involvement in school decision-making, budget cutbacks, school performance, and their personal occupational history. Part 2, General Public Survey, contains information on the respondents' confidence levels in public institutions, perceived problems in their local high school, the value of school programs, functions of schools, educational discipline, the education of their children, and their opinions of President Ronald Reagan. Demographic information was collected, including respondents' sex, age, race, occupation, education and income levels, marital status, number of children, political party identification, and voting behavior.

  8. N

    Dataset for Washington, DC Census Bureau Income Distribution by Gender

    • neilsberg.com
    Updated Jan 9, 2024
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    Neilsberg Research (2024). Dataset for Washington, DC Census Bureau Income Distribution by Gender [Dataset]. https://www.neilsberg.com/research/datasets/b3dae6b9-abcb-11ee-8b96-3860777c1fe6/
    Explore at:
    Dataset updated
    Jan 9, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Washington
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the Washington household income by gender. The dataset can be utilized to understand the gender-based income distribution of Washington income.

    Content

    The dataset will have the following datasets when applicable

    Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

    • Washington, DC annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
    • Washington, DC annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2022)

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Interested in deeper insights and visual analysis?

    Explore our comprehensive data analysis and visual representations for a deeper understanding of Washington income distribution by gender. You can refer the same here

  9. a

    Stop Data

    • private-demo-dcdev.opendata.arcgis.com
    • s.cnmilf.com
    • +3more
    Updated Oct 13, 2023
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    City of Washington, DC (2023). Stop Data [Dataset]. https://private-demo-dcdev.opendata.arcgis.com/maps/DCGIS::stop-data
    Explore at:
    Dataset updated
    Oct 13, 2023
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    The accompanying data cover all MPD stops including vehicle, pedestrian, bicycle, and harbor stops for the period from January 1, 2023 – June 30, 2024. A stop may involve a ticket (actual or warning), investigatory stop, protective pat down, search, or arrest.If the final outcome of a stop results in an actual or warning ticket, the ticket serves as the official documentation for the stop. The information provided in the ticket include the subject’s name, race, gender, reason for the stop, and duration. All stops resulting in additional law enforcement actions (e.g., pat down, search, or arrest) are documented in MPD’s Record Management System (RMS). This dataset includes records pulled from both the ticket (District of Columbia Department of Motor Vehicles [DMV]) and RMS sources. Data variables not applicable to a particular stop are indicated as “NULL.” For example, if the stop type (“stop_type” field) is a “ticket stop,” then the fields: “stop_reason_nonticket” and “stop_reason_harbor” will be “NULL.”Each row in the data represents an individual stop of a single person, and that row reveals any and all recorded outcomes of that stop (including information about any actual or warning tickets issued, searches conducted, arrests made, etc.). A single traffic stop may generate multiple tickets, including actual, warning, and/or voided tickets. Additionally, an individual who is stopped and receives a traffic ticket may also be stopped for investigatory purposes, patted down, searched, and/or arrested. If any of these situations occur, the “stop_type” field would be labeled “Ticket and Non-Ticket Stop.” If an individual is searched, MPD differentiates between person and property searches. Please note that the term property in this context refers to a person’s belongings and not a physical building. The “stop_location_block” field represents the block-level location of the stop and/or a street name. The age of the person being stopped is calculated based on the time between the person’s date of birth and the date of the stop.There are certain locations that have a high prevalence of non-ticket stops. These can be attributed to some centralized processing locations. Additionally, there is a time lag for data on some ticket stops as roughly 20 percent of tickets are handwritten. In these instances, the handwritten traffic tickets are delivered by MPD to the DMV, and then entered into data systems by DMV contractors.On August 1, 2021, MPD transitioned to a new version of its current records management system, Mark43 RMS.Beginning January 1, 2023, fields pertaining to the bureau, division, unit, and PSA (if applicable) of the officers involved in events where a stop was conducted were added to the dataset. MPD’s Records Management System (RMS) captures all members associated with the event but cannot isolate which officer (if multiple) conducted the stop itself. Assignments are captured by cross-referencing officers’ CAD ID with MPD’s Timesheet Manager Application. These fields reflect the assignment of the officer issuing the Notice of Infraction (NOIs) and/or the responding officer(s), assisting officer(s), and/or arresting officer(s) (if an investigative stop) as of the end of the two-week pay period for January 1 – June 30, 2023 and as of the date of the stop for July 1, 2023 and forward. The values are comma-separated if multiple officers were listed in the report.For Stop Type = Harbor and Stop Type = Ticket Only, the officer assignment information will be in the NOI_Officer fields. For Stop Type = Ticket and Non-Ticket the officer assignments will be in both NOI Officer (for the officer that issued the NOI) and RMS_Officer fields (for any other officer involved in the event, which may also be the officer who issued the NOI). For Stop Type = Non-Ticket, the officer assignment information will be in the RMS_Officer fields.Null values in officer assignment fields reflect either Reserve Corps members, who’s assignments are not captured in the Timesheet Manager Application, or members who separated from MPD between the time of the stop and the time of the data extraction.Finally, MPD is conducting on-going data audits on all data for thorough and complete information. Figures are subject to change due to delayed reporting, on-going data quality audits, and data improvement processes.

  10. d

    DC COVID-19 Department of Corrections

    • datasets.ai
    • catalog.midasnetwork.us
    • +2more
    15, 21, 3, 8
    Updated Mar 2, 2022
    + more versions
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    District of Columbia (2022). DC COVID-19 Department of Corrections [Dataset]. https://datasets.ai/datasets/dc-covid-19-department-of-corrections
    Explore at:
    3, 15, 21, 8Available download formats
    Dataset updated
    Mar 2, 2022
    Dataset authored and provided by
    District of Columbia
    Area covered
    Washington
    Description

    On March 2, 2022 DC Health announced the District’s new COVID-19 Community Level key metrics and reporting. COVID-19 cases are now reported on a weekly basis. More information available at https://coronavirus.dc.gov. District of Columbia Department of Correction, both personnel and resident, testing for the number of positive tests, quarantined, returned to work, recovery and lives lost. Due to rapidly changing nature of COVID-19, data for March 2020 is limited.

    General Guidelines for Interpreting Disease Surveillance Data

    During a disease outbreak, the health department will collect, process, and analyze large amounts of information to understand and respond to the health impacts of the disease and its transmission in the community. The sources of disease surveillance information include contact tracing, medical record review, and laboratory information, and are considered protected health information. When interpreting the results of these analyses, it is important to keep in mind that the disease surveillance system may not capture the full picture of the outbreak, and that previously reported data may change over time as it undergoes data quality review or as additional information is added. These analyses, especially within populations with small samples, may be subject to large amounts of variation from day to day. Despite these limitations, data from disease surveillance is a valuable source of information to understand how to stop the spread of COVID19.

  11. U

    Digital elevation model and derivative datasets to support the integration...

    • data.usgs.gov
    • datasets.ai
    • +2more
    Updated Sep 3, 2024
    + more versions
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    Michelle Katoski; Peter Steeves; George Onyullo (2024). Digital elevation model and derivative datasets to support the integration of stormwater drainage into the Washington, D.C. Stormwater StreamStats application [Dataset]. http://doi.org/10.5066/P9AJLI3I
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    Dataset updated
    Sep 3, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Michelle Katoski; Peter Steeves; George Onyullo
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Time period covered
    Oct 3, 2023
    Area covered
    Washington
    Description

    This dataset was created to support the Washington D.C. StreamStats project funded by the Washington D.C. Department of Energy and Environment (DOEE). The dataset contains digital elevation model (DEM), flow direction and catchment layers that were conditioned using Washingtons D.C.’s stormwater network layer. The data are hosted online as a component of the USGS StreamStats web application (https://streamstats.usgs.gov), where users can interact with a map of Washington D.C.’s stormwater pipe system and National Hydrography Dataset (NHD) “best resolution” blue lines to delineate drainage basins that account for pipe flow. This project utilized 1-meter (high resolution) terrain products, which improves upon existing 10 meter resolution data products traditionally used in StreamStats. Following work completed for Boston’s Mystic River Basin, Washington, D.C. is the second jurisdiction to incorporate storm-drain-network data into StreamStats. The pipe-network-informed hydro-geomorp ...

  12. Crime Incident Data for Selected HOPE VI Sites in Milwaukee, Wisconsin,...

    • icpsr.umich.edu
    • catalog.data.gov
    ascii, delimited, sas +2
    Updated Jul 6, 2011
    + more versions
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    Cahill, Meagan Elizabeth (2011). Crime Incident Data for Selected HOPE VI Sites in Milwaukee, Wisconsin, 2002-2010, and Washington, DC, 2000-2009 [Dataset]. http://doi.org/10.3886/ICPSR29981.v1
    Explore at:
    delimited, sas, ascii, stata, spssAvailable download formats
    Dataset updated
    Jul 6, 2011
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Cahill, Meagan Elizabeth
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/29981/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/29981/terms

    Area covered
    Wisconsin, Milwaukee, Washington, United States
    Description

    The purpose of this project was to conduct an evaluation of the impact on crime of the closing, renovation, and subsequent reopening of selected public housing developments under the United States Department of Housing and Urban Development's (HUD) Housing Opportunities for People Everywhere (HOPE VI) initiative. The study examined crime displacement and potential diffusion of benefits in and around five public housing developments that, since 2000, had been redeveloped using funds from HUD's HOPE VI initiative and other sources. In Milwaukee, Wisconsin, three sites were selected for inclusion in the study. However, due to substantial overlap between the various target sites and displacement zones, the research team ultimately decided to aggregate the three sites into a single target area. A comparison area was then chosen based on recommendations from the Housing Authority of the City of Milwaukee (HACM). In Washington, DC, two HOPE VI sites were selected for inclusion in the study. Based on recommendations from the District of Columbia Housing Authority (DCHA), the research team selected a comparison site for each of the two target areas. Displacement areas were then drawn as concentric rings ("buffers") around the target areas in both Milwaukee, Wisconsin and Washington, DC. Address-level incident data were collected for the city of Milwaukee from the Milwaukee Police Department for the period January 2002 through February 2010. Incident data included all "Group A" offenses as classified under National Incident Based Reporting System (NIBRS). The research team classified the offenses into personal and property offenses. The offenses were aggregated into monthly counts, yielding 98 months of data (Part 1: Milwaukee, Wisconsin Data). Address-level data were also collected for Washington, DC from the Metropolitan Police Department for the time period January 2000 through September 2009. Incident data included all Part I offenses as classified under the Uniform Crime Report (UCR) system. The data were classified by researchers into personal and property offenses and aggregated by month, yielding 117 months of data (Part 2: Washington, DC Data). Part 1 contains 15 variables, while Part 2 contains a total of 27 variables. Both datasets include variables on the number of personal offenses reported per month, the number of property offenses reported per month, and the total number of incidents reported per month for each target site, buffer zone area (1000 feet or 2000 feet), and comparison site. Month and year indicators are also included in each dataset.

  13. d

    Data from: Parks and Recreation Areas

    • datasets.ai
    • adoptablock.dc.gov
    • +2more
    0, 15, 21, 25, 3, 57 +1
    Updated Sep 2, 2024
    + more versions
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    District of Columbia (2024). Parks and Recreation Areas [Dataset]. https://datasets.ai/datasets/parks-and-recreation-areas-ecd39
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    21, 25, 3, 57, 15, 8, 0Available download formats
    Dataset updated
    Sep 2, 2024
    Dataset authored and provided by
    District of Columbia
    Description

    Department of Parks and Recreation (DPR) properties identified as polygons. The dataset contains general locations and amenity information about the properties under the jurisdiction of the DC Department of Parks and Recreation. It has been created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. This data is provided by the Department of Parks and Recreation.

  14. d

    Historic Data on DC Buildings

    • catalog.data.gov
    • opendata.dc.gov
    • +2more
    Updated Feb 5, 2025
    + more versions
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    Office of Planning (2025). Historic Data on DC Buildings [Dataset]. https://catalog.data.gov/dataset/historic-data-on-dc-buildings
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    Office of Planning
    Area covered
    Washington
    Description

    Historical Data on the Buildings of Washington DC, collected over 15 years by Brian Kraft, with support from JMT Inc., for the DC Historic Preservation Office. Most of the data comes from the building permits issued by the city, especially from 1877 to 1949. Sources are named for all buildings and other sources include real estate maps, tax assessments, newspaper reports, and the DC Office of Tax and Revenue, mostly for buildings after 1949. Work on this data is ongoing but we feel that this will be a valuable and enjoyable research tool as it is.

  15. d

    DC COVID-19 Department of Motor Vehicles

    • catalog.data.gov
    • opendata.dc.gov
    • +2more
    Updated Feb 5, 2025
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    City of Washington, DC (2025). DC COVID-19 Department of Motor Vehicles [Dataset]. https://catalog.data.gov/dataset/dc-covid-19-department-of-motor-vehicles
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

    On March 2, 2022 DC Health announced the District’s new COVID-19 Community Level key metrics and reporting. COVID-19 cases are now reported on a weekly basis. District of Columbia Department of Motor Vehicles testing for the number of positive tests, quarantined, returned to work and deaths. Due to rapidly changing nature of COVID-19, data for March 2020 is limited.General Guidelines for Interpreting Disease Surveillance DataDuring a disease outbreak, the health department will collect, process, and analyze large amounts of information to understand and respond to the health impacts of the disease and its transmission in the community. The sources of disease surveillance information include contact tracing, medical record review, and laboratory information, and are considered protected health information. When interpreting the results of these analyses, it is important to keep in mind that the disease surveillance system may not capture the full picture of the outbreak, and that previously reported data may change over time as it undergoes data quality review or as additional information is added. These analyses, especially within populations with small samples, may be subject to large amounts of variation from day to day. Despite these limitations, data from disease surveillance is a valuable source of information to understand how to stop the spread of COVID19.

  16. d

    DC COVID-19 Office of Unified Communications

    • opendata.dc.gov
    • catalog.data.gov
    Updated Apr 27, 2020
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    City of Washington, DC (2020). DC COVID-19 Office of Unified Communications [Dataset]. https://opendata.dc.gov/datasets/328c5c920b6a4bdbbe7d3f4d7f9c1132
    Explore at:
    Dataset updated
    Apr 27, 2020
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Area covered
    Description

    On March 2, 2022 DC Health announced the District’s new COVID-19 Community Level key metrics and reporting. COVID-19 cases are now reported on a weekly basis. District of Columbia Office of Unified Communications testing for the number of positive tests, quarantined, returned to work and lives lost. Due to rapidly changing nature of COVID-19, data for March 2020 is limited.General Guidelines for Interpreting Disease Surveillance DataDuring a disease outbreak, the health department will collect, process, and analyze large amounts of information to understand and respond to the health impacts of the disease and its transmission in the community. The sources of disease surveillance information include contact tracing, medical record review, and laboratory information, and are considered protected health information. When interpreting the results of these analyses, it is important to keep in mind that the disease surveillance system may not capture the full picture of the outbreak, and that previously reported data may change over time as it undergoes data quality review or as additional information is added. These analyses, especially within populations with small samples, may be subject to large amounts of variation from day to day. Despite these limitations, data from disease surveillance is a valuable source of information to understand how to stop the spread of COVID19.

  17. N

    Dataset for Washington, DC Census Bureau Racial Data

    • neilsberg.com
    Updated Aug 18, 2023
    + more versions
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    Neilsberg Research (2023). Dataset for Washington, DC Census Bureau Racial Data [Dataset]. https://www.neilsberg.com/research/datasets/1a58ad66-4181-11ee-9cce-3860777c1fe6/
    Explore at:
    Dataset updated
    Aug 18, 2023
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Washington
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the Washington population by race and ethnicity. The dataset can be utilized to understand the racial distribution of Washington.

    Content

    The dataset will have the following datasets when applicable

    Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)

    • Washington, DC Population Breakdown by Race
    • Washington, DC Non-Hispanic Population Breakdown by Race
    • Washington, DC Hispanic or Latino Population Distribution by Their Ancestries

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

  18. d

    ParkDC

    • opendata.dc.gov
    • datasets.ai
    • +3more
    Updated Feb 21, 2019
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    City of Washington, DC (2019). ParkDC [Dataset]. https://opendata.dc.gov/content/73b890d5b83c4220ad41cf0378290929
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    Dataset updated
    Feb 21, 2019
    Dataset authored and provided by
    City of Washington, DC
    License

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

    Description

    ParkDC.com provides information on the District Department of Transportation's (DDOT) parking and curbside programs. On this site, you can learn about residential parking (and permits), meters, parking signs, and new curbside programs! These programs are managed by DDOT's Parking and Ground Transportation Division (PGTD).

  19. F

    Civilian Labor Force in Washington-Arlington-Alexandria, DC-VA-MD-WV (MSA)

    • fred.stlouisfed.org
    json
    Updated Jul 2, 2025
    + more versions
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    (2025). Civilian Labor Force in Washington-Arlington-Alexandria, DC-VA-MD-WV (MSA) [Dataset]. https://fred.stlouisfed.org/series/WASH911LF
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 2, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    West Virginia, Washington Metropolitan Area
    Description

    Graph and download economic data for Civilian Labor Force in Washington-Arlington-Alexandria, DC-VA-MD-WV (MSA) (WASH911LF) from Jan 1990 to May 2025 about DC, Washington, MD, WV, civilian, VA, labor force, labor, and USA.

  20. A

    ‘Police Killings US’ analyzed by Analyst-2

    • analyst-2.ai
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com), ‘Police Killings US’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-police-killings-us-57e7/latest
    Explore at:
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Police Killings US’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/azizozmen/police-killings-us on 13 February 2022.

    --- Dataset description provided by original source is as follows ---

    "In 2015, The Washington Post began to log every fatal shooting by an on-duty police officer in the United States. In that time there have been more than 5,000 such shootings recorded by The Post. After Michael Brown, an unarmed Black man, was killed in 2014 by police in Ferguson, Mo., a Post investigation found that the FBI undercounted fatal police shootings by more than half. This is because reporting by police departments is voluntary and many departments fail to do so. The Washington Post’s data relies primarily on news accounts, social media postings, and police reports. Analysis of more than five years of data reveals that the number and circumstances of fatal shootings and the overall demographics of the victims have remained relatively constant..." SOURCE ==> Washington Post Article

    For more information about this story

    This dataset has been prepared by The Washington Post (they keep updating it on runtime) with every fatal shooting in the United States by a police officer in the line of duty since Jan. 1, 2015.

    2016 PoliceKillingUS DATASET
    2017 PoliceKillingUS DATASET
    2018 PoliceKillingUS DATASET
    2019 PoliceKillingUS DATASET
    2020 PoliceKillingUS DATASET

    Features at the Dataset:

    The file fatal-police-shootings-data.csv contains data about each fatal shooting in CSV format. The file can be downloaded at this URL. Each row has the following variables:

    • id: a unique identifier for each victim
    • name: the name of the victim
    • date: the date of the fatal shooting in YYYY-MM-DD format
    • manner_of_death: shot, shot and Tasered
    • armed: indicates that the victim was armed with some sort of implement that a police officer believed could inflict harm
      • undetermined: it is not known whether or not the victim had a weapon
      • unknown: the victim was armed, but it is not known what the object was
      • unarmed: the victim was not armed
    • age: the age of the victim
    • gender: the gender of the victim. The Post identifies victims by the gender they identify with if reports indicate that it differs from their biological sex.
      • M: Male
      • F: Female
      • None: unknown
    • race:
      • W: White, non-Hispanic
      • B: Black, non-Hispanic
      • A: Asian
      • N: Native American
      • H: Hispanic
      • O: Other
      • None: unknown
    • city: the municipality where the fatal shooting took place. Note that in some cases this field may contain a county name if a more specific municipality is unavailable or unknown.
    • state: two-letter postal code abbreviation
    • signs of mental illness: News reports have indicated the victim had a history of mental health issues, expressed suicidal intentions or was experiencing mental distress at the time of the shooting.
    • threat_level: The threat_level column was used to flag incidents for the story by Amy Brittain in October 2015. http://www.washingtonpost.com/sf/investigative/2015/10/24/on-duty-under-fire/ As described in the story, the general criteria for the attack label was that there was the most direct and immediate threat to life. That would include incidents where officers or others were shot at, threatened with a gun, attacked with other weapons or physical force, etc. The attack category is meant to flag the highest level of threat. The other and undetermined categories represent all remaining cases. Other includes many incidents where officers or others faced significant threats.
    • flee: News reports have indicated the victim was moving away from officers
      • Foot
      • Car
      • Not fleeing

    The threat column and the fleeing column are not necessarily related. For example, there is an incident in which the suspect is fleeing and at the same time turns to fire at gun at the officer. Also, attacks represent a status immediately before fatal shots by police while fleeing could begin slightly earlier and involve a chase. - body_camera: News reports have indicated an officer was wearing a body camera and it may have recorded some portion of the incident.

    SOURCE

    --- Original source retains full ownership of the source dataset ---

Share
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D.C. Office of the Chief Technology Officer (2025). Washington DC Boundary [Dataset]. https://catalog.data.gov/dataset/washington-dc-boundary

Washington DC Boundary

Explore at:
34 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Feb 4, 2025
Dataset provided by
D.C. Office of the Chief Technology Officer
Area covered
Washington
Description

District of Columbia boundary. The dataset is a polygon representing the District of Columbia boundary, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. The boundary was identified from public records and heads-up digitized using a combination of the 1995 orthophotographs, planimetric roads features, and the USGS digital raster graphic quad sheets, and 1999 planimetrics for the Potomac River boundary.Also see the District's Boundary Stone markers.

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