Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.

2018-2023 Statistics on the work of the Legal Department

1. The number of full-time faculty in various departments of colleges and universities.2. The data is the same as that on the "Teaching 1-1. Number of Full-time Faculty - Statistics by Department (Institute)" and "Teaching 1-2. Number of Full-time Faculty - Statistics by School" of the college and university affairs information open platform.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_e24eb88daad6743854009265c61ee0d8/view

Link to the Open Data site for the United States Census Bureau.

Internet use in the UK annual estimates by age, sex, disability, ethnic group, economic activity and geographical location, including confidence intervals.

The National Hospital Ambulatory Medical Care Survey (NHAMCS), conducted by the National Center for Health Statistics (NCHS), collects annual data on visits to emergency departments to describe patterns of utilization and provision of ambulatory care delivery in the United States. Data are collected from nonfederal, general, and short-stay hospitals from all 50 U.S. states and the District of Columbia, and are used to develop nationally representative estimates. The data include counts and rates of emergency department visits from 2016-2022 for the 10 leading primary diagnoses and reasons for visit, stratified by selected patient and hospital characteristics. Rankings for the 10 leading categories were identified using weighted data from 2022 and were then assessed in prior years.

Medicaid enrollment by state for all 50 states and DC.

Statistics of foreign full-time faculty in Taiwanese colleges and universities - categorized by institution, country, gender, and rank.

Context

This is a dataset that I built by scraping the United States Department of Labor's Bureau of Labor Statistics. I was looking for county-level unemployment data and realized that there was a data source for this, but the data set itself hadn't existed yet, so I decided to write a scraper and build it out myself.

Content

This data represents the Local Area Unemployment Statistics from 1990-2016, broken down by state and month. The data itself is pulled from this mapping site:

https://data.bls.gov/map/MapToolServlet?survey=la&map=county&seasonal=u

Further, the ever-evolving and ever-improving codebase that pulled this data is available here:

https://github.com/jayrav13/bls_local_area_unemployment

Acknowledgements

Of course, a huge shoutout to bls.gov and their open and transparent data. I've certainly been inspired to dive into US-related data recently and having this data open further enables my curiosities.

Inspiration

I was excited about building this data set out because I was pretty sure something similar didn't exist - curious to see what folks can do with it once they run with it! A curious question I had was surrounding Unemployment vs 2016 Presidential Election outcome down to the county level. A comparison can probably lead to interesting questions and discoveries such as trends in local elections that led to their most recent election outcome, etc.

Next Steps

Version 1 of this is as a massive JSON blob, normalized by year / month / state. I intend to transform this into a CSV in the future as well.

The Bureau of Transportation Statistics (BTS), part of the Department of Transportation (DOT) is the preeminent source of statistics on commercial aviation, multimodal freight activity, and transportation economics, and provides context to decision makers and the public for understanding statistics on transportation. BTS assures the credibility of its products and services through rigorous analysis, transparent data quality, and independence from political influence. BTS promotes innovative methods of data collection, analysis, visualization, and dissemination to improve operational efficiency, to examine emerging topics, and to create relevant and timely information products that foster understanding of transportation and its transformational role in society. The Bureau’s National Transportation Library (NTL) is the permanent, publicly accessible home for research publications from throughout the transportation community; the gateway to all DOT data; and the help line for the Congress, researchers, and the public for information about transportation.

Singapore Revenue: Customs and Excise Dept: Total data was reported at 271.700 SGD mn in Oct 2018. This records an increase from the previous number of 246.600 SGD mn for Sep 2018. Singapore Revenue: Customs and Excise Dept: Total data is updated monthly, averaging 166.800 SGD mn from Jun 1994 (Median) to Oct 2018, with 293 observations. The data reached an all-time high of 602.700 SGD mn in Jul 2003 and a record low of -0.600 SGD mn in May 2003. Singapore Revenue: Customs and Excise Dept: Total data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Singapore – Table SG.F003: Government Revenue: Customs and Excise Department.

Abstract

This dataset includes economic statistics on inflation, prices, unemployment, and pay & benefits provided by the Bureau of Labor Statistics (BLS)

Documentation

Update frequency: Monthly Dataset source: U.S. Bureau of Labor Statistics Terms of use: This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - 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. See the GCP Marketplace listing for more details and sample queries: https://console.cloud.google.com/marketplace/details/bls-public-data/bureau-of-labor-statistics

DOS Projection: Population: Non-Malaysian Citizens data was reported at 4,152.400 Person th in 2040. This records an increase from the previous number of 3,971.300 Person th for 2035. DOS Projection: Population: Non-Malaysian Citizens data is updated yearly, averaging 3,767.300 Person th from Dec 2020 (Median) to 2040, with 5 observations. The data reached an all-time high of 4,152.400 Person th in 2040 and a record low of 3,297.600 Person th in 2020. DOS Projection: Population: Non-Malaysian Citizens data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Malaysia – Table MY.G002: Population: Projection: Department of Statistics.

The Quarterly Census of Employment and Wages (QCEW) Program is a Federal-State cooperative program between the U.S. Department of Labor’s Bureau of Labor Statistics (BLS) and the California EDD’s Labor Market Information Division (LMID). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by California Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit industry codes from the North American Industry Classification System (NAICS) at the national, state, and county levels. At the national level, the QCEW program publishes employment and wage data for nearly every NAICS industry. At the state and local area level, the QCEW program publishes employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. In accordance with the BLS policy, data provided to the Bureau in confidence are used only for specified statistical purposes and are not published. The BLS withholds publication of Unemployment Insurance law-covered employment and wage data for any industry level when necessary to protect the identity of cooperating employers. Data from the QCEW program serve as an important input to many BLS programs. The Current Employment Statistics and the Occupational Employment Statistics programs use the QCEW data as the benchmark source for employment. The UI administrative records collected under the QCEW program serve as a sampling frame for the BLS establishment surveys. In addition, the data serve as an input to other federal and state programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses the QCEW data as the base for developing the wage and salary component of personal income. The U.S. Department of Labor’s Employment and Training Administration (ETA) and California's EDD use the QCEW data to administer the Unemployment Insurance program. The QCEW data accurately reflect the extent of coverage of California’s UI laws and are used to measure UI revenues; national, state and local area employment; and total and UI taxable wage trends. The U.S. Department of Labor’s Bureau of Labor Statistics publishes new QCEW data in its County Employment and Wages news release on a quarterly basis. The BLS also publishes a subset of its quarterly data through the Create Customized Tables system, and full quarterly industry detail data at all geographic levels.

Annual UK and constituent country figures for births, deaths, marriages, divorces, civil partnerships and civil partnership dissolutions.

Financial overview and grant giving statistics of Echelon No 31 Department of Texas the Twenty and Four