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2010 Salary Data
data.vermont.gov | Last Updated 2024-01-23T18:24:20.000ZState employee salary information for the years 2009 through 2013
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RSBS SMO: Kitchen Appliances, New York State Residential Statewide Baseline Study: Single and Multifamily Occupant Telephone or Web Survey
data.ny.gov | Last Updated 2019-11-15T22:21:25.000ZHow does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. The New York State Energy Research and Development Authority (NYSERDA), in collaboration with the New York State Department of Public Service (DPS), conducted a statewide residential baseline study (study) from 2011 to 2014 of the single-family and multifamily residential housing segments, including new construction, and a broad range of energy uses and efficiency measures. This dataset includes 2,982 single-family and 379 multifamily occupant survey completes for a total of 3,361 responses. The survey involved 2,285 Web, 1,041 telephone, and 35 mini-inspection surveys. The survey collected information on the following building characteristics: building shell, kitchen appliances, heating and cooling equipment, water heating equipment, clothes washing and drying equipment, lighting, pool and spa equipment, small household appliances, miscellaneous energy consuming equipment, as well as behaviors and characteristics of respondents.
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Budget - 2013 Budget Ordinance - Appropriations
data.cityofchicago.org | Last Updated 2012-11-29T17:02:34.000ZThe Annual Appropriation Ordinance is the final City operating budget as approved by the City Council. It reflects the City’s operating budget at the beginning of the fiscal year on January 1. This dataset details the budgeted expenditures in the Ordinance and identifies them by department, appropriation account, and funding type: Local, Community Development Block Grant Program (CDBG), and other Grants. “Local” funds refer to those line items that are balanced with locally generated revenue sources, including but not limited to the Corporate Fund, Water Fund, Midway and O’Hare Airport funds, Vehicle Tax Fund, Library Fund and General Obligation Bond funds. Owner: Budget and Management. Frequency: Data is updated annually. For more information about the budget process, visit the Budget Documents page: http://j.mp/lPotWf.
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Trips by Distance - Daily Average by Month
data.bts.gov | Last Updated 2024-04-30T19:08:37.000ZHow many people are staying at home? How far are people traveling when they don’t stay home? Which states and counties have more people taking trips? The Bureau of Transportation Statistics (BTS) now provides answers to those questions through our new mobility statistics. The Trips by Distance data and number of people staying home and not staying home are estimated for the Bureau of Transportation Statistics by the Maryland Transportation Institute and Center for Advanced Transportation Technology Laboratory at the University of Maryland. The travel statistics are produced from an anonymized national panel of mobile device data from multiple sources. All data sources used in the creation of the metrics contain no personal information. Data analysis is conducted at the aggregate national, state, and county levels. A weighting procedure expands the sample of millions of mobile devices, so the results are representative of the entire population in a nation, state, or county. To assure confidentiality and support data quality, no data are reported for a county if it has fewer than 50 devices in the sample on any given day. Trips are defined as movements that include a stay of longer than 10 minutes at an anonymized location away from home. Home locations are imputed on a weekly basis. A movement with multiple stays of longer than 10 minutes before returning home is counted as multiple trips. Trips capture travel by all modes of transportation. including driving, rail, transit, and air. The daily travel estimates are from a mobile device data panel from merged multiple data sources that address the geographic and temporal sample variation issues often observed in a single data source. The merged data panel only includes mobile devices whose anonymized location data meet a set of data quality standards, which further ensures the overall data quality and consistency. The data quality standards consider both temporal frequency and spatial accuracy of anonymized location point observations, temporal coverage and representativeness at the device level, spatial representativeness at the sample and county level, etc. A multi-level weighting method that employs both device and trip-level weights expands the sample to the underlying population at the county and state levels, before travel statistics are computed. These data are experimental and may not meet all of our quality standards. Experimental data products are created using new data sources or methodologies that benefit data users in the absence of other relevant products. We are seeking feedback from data users and stakeholders on the quality and usefulness of these new products. Experimental data products that meet our quality standards and demonstrate sufficient user demand may enter regular production if resources permit.
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U.S. State and Territorial Stay-At-Home Orders: March 15, 2020 – August 15, 2021 by County by Day
healthdata.gov | Last Updated 2023-07-26T01:25:18.000ZState and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance. Data were collected to determine when individuals in states and territories were subject to executive orders, administrative orders, resolutions, and proclamations for COVID-19 that require or recommend people stay in their homes. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level. These data are derived from the publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly require or recommend individuals stay at home found by the CDC, COVID-19 Community Intervention and At-Risk Task Force, Monitoring and Evaluation Team & CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 15, 2020 through August 15, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. These data do not include mandatory business closures, curfews, or limitations on public or private gatherings. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.
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Iowa Pandemic Recovery Reporting: State Expenditures
mydata.iowa.gov | Last Updated 2024-06-05T22:04:16.000ZThis dataset provides information on all expenditures made by the State of Iowa associated with Federal awards considered covered funds under Section 15011 of the Coronavirus Aid, Relief, and Economic Security (CARES) Act. Covered funds are federal funds appropriated through one of the following: The Coronavirus Preparedness and Response Supplemental Appropriations Act, 2020 (Public Law 116-123); The Families First Coronavirus Response Act (Public Law 116-127); The Coronavirus Aid, Relief, and Economic Security Act (Public Law 116-136); The Paycheck Protection Program and Health Care Enhancement Act (Public Law 116-139); The Consolidated Appropriations Act, 2021 (Public Law 116-260); or The American Rescue Plan Act, 2021 (Public Law 117-2).
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Insurance Producers Licensed in Iowa - Accident and Health
mydata.iowa.gov | Last Updated 2024-05-17T13:40:41.000ZThis filtered view provides a listing of resident and non-resident insurance producers licensed to sell to accident and health insurance to Iowans.
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Total Food Assistance Allotments, and Average Households and Recipients by Year and County
mydata.iowa.gov | Last Updated 2024-05-21T22:00:16.000ZThe Food Assistance Program provides Electronic Benefit Transfer (EBT) cards that can be used to buy groceries at supermarkets, grocery stores and some Farmers Markets. This dataset provides data on the number of households, recipients and cash assistance provided through the Food Assistance Program participation by month and county starting in January 2011 and updated monthly.
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Iowa Median Earnings in Past 12 Months for the Civilian Employed Population 16 Years and Over by Sex and Industry (ACS 5-Year Estimates)
mydata.iowa.gov | Last Updated 2023-08-30T17:20:14.000ZThis dataset provides median earnings in past 12 months for civilian employed population 16 years and older by sex and industry 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 B24032. Sex categories include Male and Female. The dataset includes the following industries: Agriculture forestry fishing and hunting, Mining quarrying and oil and gas extraction, Construction, Manufacturing, Wholesale trade, Retail trade, Transportation and warehousing, Utilities, Information, Finance and insurance, Real estate and rental and leasing, Professional scientific and technical services, Management of companies and enterprises, Administrative and support and waste management services, Educational services, Health care and social assistance, Arts entertainment and recreation, Accommodation and food services, Other services except public administration, and Public administration. Some industries roll up into a broader industry group.
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Vital Signs: Life Expectancy – by ZIP Code
data.bayareametro.gov | Last Updated 2018-07-06T18:05:06.000ZVITAL SIGNS INDICATOR Life Expectancy (EQ6) FULL MEASURE NAME Life Expectancy LAST UPDATED April 2017 DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time. DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ U.S. Census Bureau: Decennial Census ZCTA Population (2000-2010) http://factfinder.census.gov U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2013) http://factfinder.census.gov CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population that can be compared across time and populations. More information about the determinants of life expectancy that may lead to differences in life expectancy between neighborhoods can be found in the Bay Area Regional Health Inequities Initiative (BARHII) Health Inequities in the Bay Area report at http://www.barhii.org/wp-content/uploads/2015/09/barhii_hiba.pdf. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and ZIP Codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population. Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential ZIP Code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality. For the ZIP Code-level life expectancy calculation, it is assumed that postal ZIP Codes share the same boundaries as ZIP Code Census Tabulation Areas (ZCTAs). More information on the relationship between ZIP Codes and ZCTAs can be found at http://www.census.gov/geo/reference/zctas.html. ZIP Code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 ZIP Code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for ZIP Codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest ZIP Code with population. ZIP Code population for 2000 estimates comes from the Decennial Census. ZIP Code population for 2013 estimates are from the American Community Survey (5-Year Average). ACS estimates are adjusted using Decennial Census data for more accurate population estimates. An adjustment factor was calculated using the ratio between the 2010 Decennial Census population estimates and the 2012 ACS 5-Year (with middle year 2010) population estimates. This adjustment factor is particularly im