Graph and download economic data for All Employees, Federal, Except U.S. Postal Service (CES9091100001) from Jan 1939 to May 2025 about establishment survey, federal, government, services, employment, and USA.

The data contain records of arrests and bookings for federal offenses in the United States during fiscal year 2018. The data were constructed from the United States Marshals Service (USMS) Prisoner Tracking System database. Records include arrests made by federal law enforcement agencies (including the USMS), state and local agencies, and self-surrenders. Offenders arrested for federal offenses are transferred to the custody of the USMS for processing, transportation, and detention. The Prisoner Tracking System contains data on all offenders within the custody of the USMS. The data file contains variables from the original USMS files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt and the Bureau of Justice Statistics. Data and documentation were prepared by Abt.

Graph and download economic data for All Employees: Government: Federal Government in Nebraska (SMS31000009091000001) from Jan 1990 to Apr 2025 about NE, federal, government, employment, and USA.

These data contain records of criminal defendants who were sentenced pursuant to provisions of the Sentencing Reform Act (SRA) of 1984 and reported to the United States Sentencing Commission (USSC) during fiscal year 2022. It is estimated that over 90 percent of felony defendants in the federal criminal justice system are sentenced pursuant to the SRA of 1984. The data were obtained from the United States Sentencing Commission's Office of Policy Analysis' (OPA) Standardized Research Data File. The Standardized Research Data File consists of variables from the Monitoring Department's database, which is limited to those defendants whose records have been furnished to the USSC by United States district courts and United States magistrates, as well as variables created by the OPA specifically for research purposes. The data include variables from the Judgment and Conviction (J and C) order submitted by the court, background and guideline information collected from the Presentencing Report (PSR), and the report on sentencing hearing in the Statement of Reasons (SOR). These data contain detailed information such as the guideline base offense level, offense level adjustments, criminal history, departure status, statement of reasons given for departure, and basic demographic information. These data are the primary analysis file and include only statute, guideline computation, and adjustment variables for the most serious offense of conviction. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.

The data contain records of sentenced offenders in the custody of the Bureau of Prisons (BOP) at year-end of fiscal year 2017. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt and the Bureau of Justice Statistics. Data and documentation were prepared by Abt.

This statistic depicts the distribution of federal drug control spending in the United States as requested for the fiscal year 2025, by function. The largest share of federal drug control spending is around 49 percent, which was requested for treatments.

About this dataset

Context

The dataset tabulates the Federal Way population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Federal Way. The dataset can be utilized to understand the population distribution of Federal Way by age. For example, using this dataset, we can identify the largest age group in Federal Way.

Key observations

The largest age group in Federal Way, WA was for the group of age 10-14 years with a population of 7,284 (7.30%), according to the 2021 American Community Survey. At the same time, the smallest age group in Federal Way, WA was the 80-84 years with a population of 1,424 (1.43%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Federal Way is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Federal Way 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 Federal Way Population by Age. You can refer the same here

Graph and download economic data for All Employees: Government: Federal Government in Ames, IA (MSA) (SMU19111809091000001) from Jan 1990 to May 2025 about Ames, IA, federal, government, employment, and USA.

The data contain records of defendants in federal criminal cases terminated in United States District Court during fiscal year 2016. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central System file. According to the EOUSA, the United States attorneys conduct approximately 95 percent of the prosecutions handled by the Department of Justice. The Central Charge and Central System data contain variables from the original EOUSA files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt and the Bureau of Justice Statistics. Data and documentation were prepared by Abt.

The 2019 Census of State and Federal Adult Correctional Facilities (CCF) was the ninth enumeration of state institutions and the sixth enumeration of federal institutions sponsored by the Bureau of Justice Statistics and its predecessors. Earlier censuses were completed in 1979 (ICPSR 7852), 1984 (ICPSR 8444), 1990 (ICPSR 9908), 1995 (ICPSR 6953), 2000 (ICPSR 4021), 2005 (ICPSR 24642), and 2012 (ICPSR 37294). The 2019 CCF consisted of two data collection instruments - one for confinement facilities and one for community-based facilities. For each facility, information was provided on facility operator; sex of prisoners authorized to be housed by facility; facility functions; percentage of prisoners authorized to leave the facility; one-day counts of prisoners by sex, race/ethnicity, special populations, and holding authority; number of walkaways occurring over a one-year period; and educational and other special programs offered to prisoners. Additional information was collected from confinement facilities, including physical security level; housing for special populations; capacity; court orders for specific conditions; one-day count of correctional staff by payroll status and sex; one-day count of security staff by sex and race/ethnicity; assaults and incidents caused by prisoners; number of escapes occurring over a one-year period; and work assignments available to prisoners. Late in the data collection to avoid complete nonresponse from facilities, BJS offered the option of providing critical data elements from the two data collection instruments. These elements included facility operator; sex of prisoners authorized to be housed by facility; facility functions; percentage of prisoners authorized to leave the facility; one-day counts of prisoners by sex, and holding authority. Physical security level was an additional critical data element for confinement facilities. The census counted prisoners held in the facilities, a custody count. Some prisoners who are held in the custody of one jurisdiction may be under the authority of a different jurisdiction. The custody count is distinct from a count of prisoners under a correctional authority's jurisdiction, which includes all prisoners over whom a correctional authority exercises control, regardless of where the prisoner is housed. A jurisdictional count is more inclusive than a prison custody count and includes state and federal prisoners housed in local jails or other non-correctional facilities.

The data contain records of suspects in federal criminal matters received by United States attorneys or filed before the United States magistrates during fiscal year 2022. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central System file. Records include suspects in criminal matters, and are limited to suspects whose matters were not declined immediately by the United States attorneys. According to the EOUSA, the United States attorneys conduct approximately 95 percent of the prosecutions handled by the Department of Justice. The Central Charge and Central System data contain variables from the original EOUSA files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.

Annual workforce population statistics on the federal public service from March 2010 to March 2024 which includes the core public administration and separate agencies. The datasets included are: - Population of the federal public service - by department or agency - and by tenure - and by province or territory of work - and by age band - and average age - and by executive level - and by first official language - and by sex - by province or territory of work and tenure - by province or territory of work - in the National Capital Region - by tenure - by first official language - by age band

The data contain records of defendants in criminal cases terminated in United States District Court during fiscal year 2017. The data were constructed from the Administrative Office of the United States District Courts' (AOUSC) criminal file. Defendants in criminal cases may be either individuals or corporations. There is one record for each defendant in each case filed. Included in the records are data from court proceedings and offense codes for up to five offenses charged at the time the case was filed. (The most serious charge at termination may differ from the most serious charge at case filing, due to plea bargaining or action of the judge or jury.) In a case with multiple charges against the defendant, a "most serious" offense charge is determined by a hierarchy of offenses based on statutory maximum penalties associated with the charges. The data file contains variables from the original AOUSC files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt and the Bureau of Justice Statistics. Data and documentation were prepared by Abt.

These data show the geographic representation of Federal and State Waters for the purpose of display in the MarineCadastre.gov OceanReports application. The boundary between state and federal waters was determined by consulting The Submerged Lands Act (43 U.S.C. §§ 1301 et seq.), 48 U.S.C. §§ 1705 and The Abandoned Shipwreck Act (43 U.S.C. §§ 2101). Some boundary delineations based on the SLA were approximated in this data set, including areas in Hawaii, Alaska, and Washington State. Although state boarders do not extend over water, it was necessary to approximate these borders to produce this data set. The boundaries depicted in this data set are for visual purposes only. The placement of these boundaries was extrapolated from the Federal Outer Continental Shelf (OCS) Administrative Boundaries as described here http://edocket.access.gpo.gov/2006/pdf/05-24659.pdf. The delineation between waters under US sovereign territory jurisdiction and that of federal governance is also approximate. Although based upon legislation, these data do not represent legal boundaries, especially in the case of Navassa Island, The Northern Mariana Islands, Baker Island, Howland Island, Johnston Atoll, Kingman Reef, Palmyra Atoll, Wake Islands and Jarvis Island.The seaward limit of this data set is the boundary of the 200nm US Exclusive Economic Zone. The EEZ is measured from the US baseline, recognized as the low-water line along the coast as marked on NOAA's nautical charts in accordance with articles of the Laws of the Sea. These limits are ambulatory and subject to revision based on changes in coastline geometry. This dataset was produced based on an update to the Maritime Limits published in September, 2013. To view the most up-to-date Maritime Limits, please see http://www.nauticalcharts.noaa.gov/csdl/mbound.htm. Navassa Island does not have an EEZ around it, so the seaward extent of the federal waters surrounding it were based on the 12 mile offshore boundary of the USFWS National Wildlife Refuge established on the island. All data is displayed in WGS_1984_World_Mercator. Area calculations for all states except Alaska were completed in the same projection. Area calculations for Alaska were completed in Alaska Albers Equal Area Conic.

This dataset summarizes the impact of federal policy and funding changes on nonprofits, municipalities, and businesses in Connecticut, as reported in the Connecticut Office of Policy and Management's Federal Impact Reporting Tool: https://www.appsvcs.opm.ct.gov/FedImpact This dataset shows the count of reported incidents grouped by state agency and is based on the main Federal Impact Reporting dataset here: https://data.ct.gov/Government/Federal-Impact-Reporting/cyas-fb55/about_data Impacts reported include funding reductions, pauses and delays in accessing funds, as well as employment reductions, and impacts from tariffs. Duplicate responses to the survey have been removed from this dataset. More information on the Federal Impact Reporting Tool can be found here: https://portal.ct.gov/governor/news/press-releases/2025/04-2025/governor-lamont-launches-reporting-tool-for-entities-impacted-by-recent-federal-actions

Banking Cards Statistics: Omsk Region: Personal: No of Transactions: Payment data was reported at 34,089.400 Unit th in Dec 2016. This records an increase from the previous number of 32,178.900 Unit th for Sep 2016. Banking Cards Statistics: Omsk Region: Personal: No of Transactions: Payment data is updated quarterly, averaging 1,548.606 Unit th from Mar 2001 (Median) to Dec 2016, with 64 observations. The data reached an all-time high of 34,089.400 Unit th in Dec 2016 and a record low of 97.220 Unit th in Mar 2001. Banking Cards Statistics: Omsk Region: Personal: No of Transactions: Payment data remains active status in CEIC and is reported by The Central Bank of the Russian Federation. The data is categorized under Russia Premium Database’s Monetary and Banking Statistics – Table RU.KAI008: Banking Cards Statistics: Siberian Federal District.

The data contain records of charges filed against defendants whose cases were terminated by United States attorneys in United States district court during fiscal year 2016. The data are charge-level records, and more than one charge may be filed against a single defendant. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central Charge file. The charge-level data may be linked to defendant-level data (extracted from the EOUSA Central System file) through the CS_SEQ variable, and it should be noted that some defendants may not have any charges other than the lead charge appearing on the defendant-level record. The Central Charge and Central System data contain variables from the original EOUSA files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt and the Bureau of Justice Statistics. Data and documentation were prepared by Abt.

The data contain records of criminal appeals cases filed in United States Courts of Appeals during fiscal year 2003. The data were constructed from the Administrative Office of the United States Courts' (AOUSC) Court of Appeals file. These contain variables on the nature of the criminal appeal, the underlying offense, and the disposition of the appeal. An appeal can be filed by the government or the offender, and the appellant can appeal the sentence, the verdict, or both sentence and verdict. The data file contains variables from the original AOUSC files as well as additional analysis variables, or "SAF" variables, that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 6.1-6.5. Variables containing information (e.g., name, Social Security number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.

United States - Federal Government; Statistical Discrepancy (IMA), Transactions was -19775.00000 Mil. of $ in July of 2024, according to the United States Federal Reserve. Historically, United States - Federal Government; Statistical Discrepancy (IMA), Transactions reached a record high of 204166.00000 in January of 2023 and a record low of -417916.00000 in April of 2022. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Federal Government; Statistical Discrepancy (IMA), Transactions - last updated from the United States Federal Reserve on June of 2025.

Banking Cards Statistics: NC: Republic of Kabardino Balkaria: Personal: No of Transactions: Payment data was reported at 29,452.759 Unit th in Sep 2023. This records an increase from the previous number of 27,899.099 Unit th for Jun 2023. Banking Cards Statistics: NC: Republic of Kabardino Balkaria: Personal: No of Transactions: Payment data is updated quarterly, averaging 3,212.003 Unit th from Mar 2008 (Median) to Sep 2023, with 63 observations. The data reached an all-time high of 29,452.759 Unit th in Sep 2023 and a record low of 63.395 Unit th in Mar 2008. Banking Cards Statistics: NC: Republic of Kabardino Balkaria: Personal: No of Transactions: Payment data remains active status in CEIC and is reported by Bank of Russia. The data is categorized under Russia Premium Database’s Monetary and Banking Statistics – Table RU.KAI005: Banking Cards Statistics: North Caucasian Federal District.