These quick facts use data from the 2011 Employment of Veterans in the Federal Executive Branch to compare Veteran employment in the Federal Government by agency, occupation, and level of disability. Three of the four charts focus on new hires.

This is a link to the United States Federal Government's Open Data Portal. Here you will find data, tools, and resources to conduct research, develop web and mobile applications, design data visualizations.

Check out the attachment in the metadata detailing all the Opioid Related datasets contained in this portal.

Data.gov is the federal government’s open data site, and aims to make government more open and accountable. Opening government data increases citizen participation in government, creates opportunities for economic development, and informs decision making in both the private and public sectors.

Links included for Center for Disease Control and Prevention both the business website and their Data and Statistics website.

Government Payrolls in the United States increased by 73 thousand in June of 2025. This dataset provides the latest reported value for - United States Government Payrolls - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Self-Employment by Occupation by County reports the total population of employed civilian workers aged 16 years and older by occupation. In the Business Type column, individual Business Types are presented as percentages of the Total employed population for the corresponding occupation in the Occupation column. For example, for 2012-2016, there were approximately 320,110 Service employees in Connecticut, 14.6% of those employees worked in Government. 'Self-Employed, Incorporated' includes workers in their own incorporated businesses, 'Self-Employed, Not Incorporated' includes workers in their own non-incorporated businesses and unpaid family workers, 'Government' includes local, state, and federal government workers, 'Private, Profit' includes employees of for-profit private companies, 'Private, Not-for-profit' includes both wage and salary employees of not-for-profit private companies. These data originate from the American Community Survey (ACS) 5-Year estimates, table S2406.

Contains:World HillshadeWorld Street Map (with Relief) - Base LayerLarge Scale International Boundaries (v11.3)World Street Map (with Relief) - LabelsDoS Country Labels DoS Country LabelsCountry (admin 0) labels that have been vetted for compliance with foreign policy and legal requirements. These labels are part of the US Federal Government Basemap, which contains the borders and place names that have been vetted for compliance with foreign policy and legal requirements.Source: DoS Country Labels - Overview (arcgis.com)Large Scale International BoundariesVersion 11.3Release Date: December 19, 2023DownloadFor more information on the LSIB click here: https://geodata.state.gov/ A direct link to the data is available here: https://data.geodata.state.gov/LSIB.zipAn ISO-compliant version of the LSIB metadata (in ISO 19139 format) is here: https://geodata.state.gov/geonetwork/srv/eng/catalog.search#/metadata/3bdb81a0-c1b9-439a-a0b1-85dac30c59b2 Direct inquiries to internationalboundaries@state.govOverviewThe Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. The current edition is version 11.3 (published 19 December 2023). The 11.3 release contains updates to boundary lines and data refinements enabling reuse of the dataset. These data and generalized derivatives are the only international boundary lines approved for U.S. Government use. The contents of this dataset reflect U.S. Government policy on international boundary alignment, political recognition, and dispute status. They do not necessarily reflect de facto limits of control.National Geospatial Data AssetThis dataset is a National Geospatial Data Asset managed by the Department of State on behalf of the Federal Geographic Data Committee's International Boundaries Theme.DetailsSources for these data include treaties, relevant maps, and data from boundary commissions and national mapping agencies. Where available and applicable, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery process involves analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground.Attribute StructureThe dataset uses thefollowing attributes:Attribute NameCC1COUNTRY1CC2COUNTRY2RANKSTATUSLABELNOTES These attributes are logically linked:Linked AttributesCC1COUNTRY1CC2COUNTRY2RANKSTATUS These attributes have external sources:Attribute NameExternal Data SourceCC1GENCCOUNTRY1DoS ListsCC2GENCCOUNTRY2DoS ListsThe eight attributes listed above describe the boundary lines contained within the LSIB dataset in both a human and machine-readable fashion. Other attributes in the release include "FID", "Shape", and "Shape_Leng" are components of the shapefile format and do not form an intrinsic part of the LSIB."CC1" and "CC2" fields are machine readable fields which contain political entity codes. These codes are derived from the Geopolitical Entities, Names, and Codes Standard (GENC) Edition 3 Update 18. The dataset uses the GENC two-character codes. The code ‘Q2’, which is not in GENC, denotes a line in the LSIB representing a boundary associated with an area not contained within the GENC standard.The "COUNTRY1" and "COUNTRY2" fields contain human-readable text corresponding to the name of the political entity. These names are names approved by the U.S. Board on Geographic Names (BGN) as incorporated in the list of Independent States in the World and the list of Dependencies and Areas of Special Sovereignty maintained by the Department of State. To ensure the greatest compatibility, names are presented without diacritics and certain names are rendered using commonly accepted cartographic abbreviations. Names for lines associated with the code ‘Q2’ are descriptive and are not necessarily BGN-approved. Names rendered in all CAPITAL LETTERS are names of independent states. Other names are those associated with dependencies, areas of special sovereignty, or are otherwise presented for the convenience of the user.The following fields are an intrinsic part of the LSIB dataset and do not rely on external sources:Attribute NameMandatoryContains NullsRANKYesNoSTATUSYesNoLABELNoYesNOTESNoYesNeither the "RANK" nor "STATUS" field contains null values; the "LABEL" and "NOTES" fields do.The "RANK" field is a numeric, machine-readable expression of the "STATUS" field. Collectively, these fields encode the views of the United States Government on the political status of the boundary line.Attribute NameValueRANK123STATUSInternational BoundaryOther Line of International Separation Special Line A value of "1" in the "RANK" field corresponds to an "International Boundary" value in the "STATUS" field. Values of "2" and "3" correspond to "Other Line of International Separation" and "Special Line", respectively.The "LABEL" field contains required text necessarily to describe the line segment. The "LABEL" field is used when the line segment is displayed on maps or other forms of cartographic visualizations. This includes most interactive products. The requirement to incorporate the contents of the "LABEL" field on these products is scale dependent. If a label is legible at the scale of a given static product a proper use of this dataset would encourage the application of that label. Using the contents of the "COUNTRY1" and "COUNTRY2" fields in the generation of a line segment label is not required. The "STATUS" field is not a line labeling field but does contain the preferred description for the three LSIB line types when lines are incorporated into a map legend. Using the "CC1", "CC2", or "RANK" fields for labeling purposes is prohibited.The "NOTES" field contains an explanation of any applicable special circumstances modifying the lines. This information can pertain to the origins of the boundary lines, any limitations regarding the purpose of the lines, or the original source of the line. Use of the "NOTES" field for labeling purposes is prohibited.External Data SourcesGeopolitical Entities, Names, and Codes Registry: https://nsgreg.nga.mil/GENC-overview.jspU.S. Department of State List of Independent States in the World: https://www.state.gov/independent-states-in-the-world/U.S. Department of State List of Dependencies and Areas of Special Sovereignty: https://www.state.gov/dependencies-and-areas-of-special-sovereignty/The source for the U.S.—Canada international boundary (NGDAID97) is the International Boundary Commission: https://www.internationalboundarycommission.org/en/maps-coordinates/coordinates.phpThe source for the “International Boundary between the United States of America and the United States of Mexico” (NGDAID82) is the International Boundary and Water Commission: https://catalog.data.gov/dataset?q=usibwcCartographic UsageCartographic usage of the LSIB requires a visual differentiation between the three categories of boundaries. Specifically, this differentiation must be between:- International Boundaries (Rank 1);- Other Lines of International Separation (Rank 2); and- Special Lines (Rank 3).Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary.Additional cartographic information can be found in Guidance Bulletins (https://hiu.state.gov/data/cartographic_guidance_bulletins/) published by the Office of the Geographer and Global Issues.ContactDirect inquiries to internationalboundaries@state.gov.CreditsThe lines in the LSIB dataset are the product of decades of collaboration between geographers at the Department of State and the National Geospatial-Intelligence Agency with contributions from the Central Intelligence Agency and the UK Defence Geographic Centre.Attribution is welcome: U.S. Department of State, Office of the Geographer and Global Issues.Changes from Prior ReleaseThe 11.3 release is the third update in the version 11 series.This version of the LSIB contains changes and accuracy refinements for the following line segments. These changes reflect improvements in spatial accuracy derived from newly available source materials, an ongoing review process, or the publication of new treaties or agreements. Notable changes to lines include:• AFGHANISTAN / IRAN• ALBANIA / GREECE• ALBANIA / KOSOVO• ALBANIA/MONTENEGRO• ALBANIA / NORTH MACEDONIA• ALGERIA / MOROCCO• ARGENTINA / BOLIVIA• ARGENTINA / CHILE• BELARUS / POLAND• BOLIVIA / PARAGUAY• BRAZIL / GUYANA• BRAZIL / VENEZUELA• BRAZIL / French Guiana (FR.)• BRAZIL / SURINAME• CAMBODIA / LAOS• CAMBODIA / VIETNAM• CAMEROON / CHAD• CAMEROON / NIGERIA• CHINA / INDIA• CHINA / NORTH KOREA• CHINA / Aksai Chin• COLOMBIA / VENEZUELA• CONGO, DEM. REP. OF THE / UGANDA• CZECHIA / GERMANY• EGYPT / LIBYA• ESTONIA / RUSSIA• French Guiana (FR.) / SURINAME• GREECE / NORTH MACEDONIA• GUYANA / VENEZUELA• INDIA / Aksai Chin• KAZAKHSTAN / RUSSIA• KOSOVO / MONTENEGRO• KOSOVO / SERBIA• LAOS / VIETNAM• LATVIA / LITHUANIA• MEXICO / UNITED STATES• MONTENEGRO / SERBIA• MOROCCO / SPAIN• POLAND / RUSSIA• ROMANIA / UKRAINEVersions 11.0 and 11.1 were updates to boundary lines. Like this version, they also contained topology fixes, land boundary terminus refinements, and tripoint adjustments. Version 11.2 corrected a few errors in the attribute data and ensured that CC1 and CC2 attributes are in alignment with an updated version of the Geopolitical Entities, Names, and Codes (GENC) Standard, specifically Edition 3 Update 17.LayersLarge_Scale_International_BoundariesTerms of

Content

Source ID: FL313066220.Q

For more information about the Flow of Funds tables, see: https://www.federalreserve.gov/apps/fof/Default.aspx

For a detailed description, including how this series is constructed, see: https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL313066220&t=

Context

This is a dataset from the Federal Reserve hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve using Kaggle and all of the data sources available through the Federal Reserve organization page!

• Update Frequency: This dataset is updated daily.

• Observation Start: 1945-10-01

• Observation End : 2019-04-01

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Michael on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Dataset

This dataset was created by Manuel Juarez

Contents

Jobless Claims - Federal Workers in the United States increased to 561 People in May 31 from 538 People in the previous week. This dataset includes a chart with historical data for the United States Initial Jobless Claims - Federal Workers.

This summary table shows, for Budget Receipts, the total amount of activity for the current month, the current fiscal year-to-date, the comparable prior period year-to-date and the budgeted amount estimated for the current fiscal year for various types of receipts (i.e. individual income tax, corporate income tax, etc.). The Budget Outlays section of the table shows the total amount of activity for the current month, the current fiscal year-to-date, the comparable prior period year-to-date and the budgeted amount estimated for the current fiscal year for functions of the federal government. The table also shows the amounts for the budget/surplus deficit categorized as listed above. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

An Excel export of combined USA Staffing, Monster, Aviator (FAA) Hiring Assessment and Selection Outcome Data from the 24 CFO Act agencies. We believe this data will empower Chief Human Capital Officers and Human Resources staff with the right data to focus on improved hiring outcomes while complying with open data requirements to increase transparency to the millions of applicants who apply for federal positions each year on USAJOBS.

This table shows the gross receipts, refunds and net receipts for the current month, the current fiscal year-to-date and the prior fiscal year-to-date for the various receipts of the federal government. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

The Survey of Federal Employees is the Office of Personnel Management's first major survey of the work force since 1983. The questionnaire was designed to provide policy-makers with information that was not available from existing sources. Questions covered various personnel areas such as employee characteristics, employees' satisfaction with their jobs, supervisors, and organizations, performance management, training, work schedule arrangements, leave benefits, and dependent care responsibilities and the ways employees fulfill these responsibilities. (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/ICPSR09983.v2. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

This table is a subsidiary table for Means of Financing the Deficit or Disposition of Surplus by the U.S. Government providing a detailed view of federal funds and trust funds that are invested in Government Account Series (GAS) securities. Federal funds include general funds, special funds, and revolving funds (public enterprise revolving funds, intragovernmental revolving funds, and credit financing accounts). A trust fund is a type of account, designated by law, for receipts or offsetting receipts dedicated to specific purposes and the expenditure of these receipts. This table includes total and subtotal rows that should be excluded when aggregating data. Some rows represent elements of the dataset's hierarchy, but are not assigned values. The classification_id for each of these elements can be used as the parent_id for underlying data elements to calculate their implied values. Subtotal rows are available to access this same information.

The below reference files provide current and historical small business size standards effective during the provided reference periods. Size standards for reference periods prior to August 2019 are provided based on the size standards in effect on January 1 of each CFR reference year, and thus, may not provide the entire history of SBA’s changes to size standards that occurred after January 1 of the CFR reference year. As such, changes that occur after January 1 of the CFR reference year are reflected in the Table of Small Business Size Standards for the next CFR reference year. Legal requirements related to size standards are governed by SBA’s size regulations actually in effect during the applicable period. Size standards for reference periods after August 2019 are provided based on the actual effective dates of the size standards. The Small Business Size Standards APIs, also provided below, power the following application: https://fanyv88.com:443/https/www.sba.gov/size-standards/, which can be used to determine if a business qualifies as small for purposes of Federal government contracting.

Context

NYC Open Data is an opportunity to engage New Yorkers in the information that is produced and used by City government. We believe that every New Yorker can benefit from Open Data, and Open Data can benefit from every New Yorker. Source: https://opendata.cityofnewyork.us/overview/

Content

Thanks to NYC Open Data, which makes public data generated by city agencies available for public use, and Citi Bike, we've incorporated over 150 GB of data in 5 open datasets into Google BigQuery Public Datasets, including:

• Over 8 million 311 service requests from 2012-2016

• More than 1 million motor vehicle collisions 2012-present

• Citi Bike stations and 30 million Citi Bike trips 2013-present

• Over 1 billion Yellow and Green Taxi rides from 2009-present

• Over 500,000 sidewalk trees surveyed decennially in 1995, 2005, and 2015

This dataset is deprecated and not being updated.

Fork this kernel to get started with this dataset.

Acknowledgements

https://opendata.cityofnewyork.us/

https://cloud.google.com/blog/big-data/2017/01/new-york-city-public-datasets-now-available-on-google-bigquery

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - https://data.cityofnewyork.us/ - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

By accessing datasets and feeds available through NYC Open Data, the user agrees to all of the Terms of Use of NYC.gov as well as the Privacy Policy for NYC.gov. The user also agrees to any additional terms of use defined by the agencies, bureaus, and offices providing data. Public data sets made available on NYC Open Data are provided for informational purposes. The City does not warranty the completeness, accuracy, content, or fitness for any particular purpose or use of any public data set made available on NYC Open Data, nor are any such warranties to be implied or inferred with respect to the public data sets furnished therein.

The City is not liable for any deficiencies in the completeness, accuracy, content, or fitness for any particular purpose or use of any public data set, or application utilizing such data set, provided by any third party.

Banner Photo by @bicadmedia from Unplash.

Inspiration

On which New York City streets are you most likely to find a loud party?

Can you find the Virginia Pines in New York City?

Where was the only collision caused by an animal that injured a cyclist?

What’s the Citi Bike record for the Longest Distance in the Shortest Time (on a route with at least 100 rides)?

https://cloud.google.com/blog/big-data/2017/01/images/148467900588042/nyc-dataset-6.png" alt="enter image description here"> https://cloud.google.com/blog/big-data/2017/01/images/148467900588042/nyc-dataset-6.png

This dataset contains Iowa civilian employed population estimate for individuals 16 years or older by by sex and class of worker for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B24080. Sex includes the following: Both, Male, and Female. Class of Worker includes the following: All Classes; Private-for-Profit Wage and Salary Workers; Private-for-Profit Wage and Salary Workers, Employee; Private-for-Profit Wage and Salary Workers, Self-Employed in Own INC; Private Not-for-Profit Wage and Salary Workers; Local Government Workers; State Government Workers; Federal Government Workers; Self-Employed; and Unpaid Family Workers.

Context

This dataset expands on my earlier New York City Census Data dataset. It includes data from the entire country instead of just New York City. The expanded data will allow for much more interesting analyses and will also be much more useful at supporting other data sets.

Content

The data here are taken from the DP03 and DP05 tables of the 2015 American Community Survey 5-year estimates. The full datasets and much more can be found at the American Factfinder website. Currently, I include two data files:

1. acs2015_census_tract_data.csv: Data for each census tract in the US, including DC and Puerto Rico.
2. acs2015_county_data.csv: Data for each county or county equivalent in the US, including DC and Puerto Rico.

The two files have the same structure, with just a small difference in the name of the id column. Counties are political subdivisions, and the boundaries of some have been set for centuries. Census tracts, however, are defined by the census bureau and will have a much more consistent size. A typical census tract has around 5000 or so residents.

The Census Bureau updates the estimates approximately every year. At least some of the 2016 data is already available, so I will likely update this in the near future.

Acknowledgements

The data here were collected by the US Census Bureau. As a product of the US federal government, this is not subject to copyright within the US.

Inspiration

There are many questions that we could try to answer with the data here. Can we predict things such as the state (classification) or household income (regression)? What kinds of clusters can we find in the data? What other datasets can be improved by the addition of census data?

This table contains 14 series, with data for years 1999 - 2011 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) Federal public sector employment (14 items: Federal public sector employees, as per Statistics Canada's statistical universe; Federal government business enterprise employees, as per Statistics Canada's statistical universe; Federal government employees, as per Statistics Canada's statistical universe; Employees common to Treasury Board of Canada Secretariat, Public Service Commission of Canada and Statistics Canada statistical universes; ...).