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TwitterHydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).
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TwitterHistorical 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.
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TwitterThis release presents immigration statistics from Home Office administrative sources, covering the period up to the end of September 2024. It includes data on the topics of:
User guide to Home Office Immigration statistics
Policy and legislative changes affecting migration to the UK: timeline
Developments in migration statistics
Publishing detailed datasets in Immigration statistics
Migration analysis at the Home Office collection page
A range of key input and impact indicators are currently published by the Home Office on the Migration transparency data webpage.
If you have feedback or questions, our email address is MigrationStatsEnquiries@homeoffice.gov.uk.
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Twitterhttps://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/
This dataset is the definitive set of statistical area 2 (SA2) boundaries for 2020 as defined by Stats NZ. This version contains 2,255 SA2 categories.
SA2s were introduced as part of the Statistical Standard for Geographic Areas 2018 (SSGA2018) which replaced the New Zealand Standard Areas Classification (NZSAC1992). The SA2 geography replaces the (NZSAC1992) area unit geography.
SA2 is an output geography that provides higher aggregations of population data than can be provided at the statistical area 1 (SA1) level. The SA2 geography aims to reflect communities that interact together socially and economically. In populated areas, SA2s generally contain similar sized populations.
SA2s are built from SA1s and either define or aggregate to define urban rural areas, territorial authorities, and regional councils. SA2s in city council areas generally have a population of 2,000–4,000 residents while SA2s in district council areas generally have a population of 1,000–3,000 residents. In rural areas, many SA2s have fewer than 1,000 residents because they are in conservation areas or contain sparse populations that cover a large area.
Names are provided with and without tohutō/macrons. The name field without macrons is suffixed ‘ascii’.
This generalised version has been simplified for rapid drawing and is designed for thematic or web mapping purposes.
Digital boundary data became freely available on 1 July 2007.
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TwitterThese economic estimates are used to provide an estimate of the contribution of DCMS sectors to the UK economy, measured by employment (number of filled jobs). These estimates are calculated based on the Office for National Statistics (ONS) Annual Population Survey (APS).
The statistics in this series (including this release) will be classed as official statistics in development until further review. On 4 August 2025, the Office for Statistics Regulation (OSR) https://osr.statisticsauthority.gov.uk/correspondence/ed-humpherson-to-sarah-alloway-lasher-suspension-of-official-statistics-accreditation/">temporarily suspended the accreditation from this employment series, at https://osr.statisticsauthority.gov.uk/correspondence/sarah-alloway-lasher-to-ed-humpherson-suspension-of-official-statistics-accreditation/">our request, following ONS https://osr.statisticsauthority.gov.uk/correspondence/michael-keoghan-to-siobhan-tuohy-smith-request-to-suspend-aps-accreditation/">reporting concerns with the quality of estimates for smaller segments of the APS population, which the DCMS Sector Economic Estimates: Employment series depends on.
Due to ongoing challenges with response rates, response levels and weighting, the accreditation of ONS statistics based on Annual Population Survey (APS) was https://osr.statisticsauthority.gov.uk/correspondence/michael-keoghan-to-siobhan-tuohy-smith-request-to-suspend-aps-accreditation/">temporarily suspended on 9 October 2024. Because of the increased volatility of both Labour Force Survey (LFS) and APS estimates, the ONS advises that estimates produced using these datasets should be treated with additional caution. ONS statistics based on both the APS and LFS will be considered official statistics in development until further review.
Following the ONS reporting concerns regarding the quality of the APS estimates, particularly for smaller segments of the population, we conducted analysis to understand the quality of DCMS employment estimates. Consequently, we have concerns regarding increased volatility due to low APS sample sizes and its impact on the reliability and quality of our estimates. The statistics in this series will be classified as official statistics in development until further review. Previous releases in the series have been classified as accredited official statistics, meaning that they have been independently assessed by the OSR as complying with the standards of trustworthiness, quality and value in the Code of Practice for Statistics.
These statistics cover the contributions of the following DCMS sectors to the UK economy;
Tourism estimates are available up to 2023 only due to data availability. We have made some revisions to employment estimates for the tourism sector and DCMS sectors overall for the years 2016 to 2019, following revisions made by the ONS to the underlying https://www.ons.gov.uk/economy/nationalaccounts/satelliteaccounts/datasets/uktourismsatelliteaccounttsatables">Tourism Satellite Account data.
The release also includes estimates for the audio visual sector, computer games sector and art and antiques market.
Users should note that there is overlap between DCMS sector definitions. In particular, several cultural sector industries are simultaneously creative industries.
A definition for each sector is available in the tables published alongside this release. Further information on all these sectors is available in the associated technical report along with details of methods and data limitations.
Alongside these calendar year employment estimates, we would usually publish APS earnings estimates to provide detailed demographic information about earnings in DCMS sectors. Due to ongoing challenges with the quality of APS data, we have not published these estimates in this release. We will explore producing these estimates in future as the quality of APS data improves.
Estimates of the number of filled jobs in the included DCMS sectors in 2024 show that:
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TwitterThis dataset includes economic statistics on inflation, prices, unemployment, and pay & benefits provided by the Bureau of Labor Statistics (BLS)
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
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Twitterhttps://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/
Dataset contains counts and measures for individuals from the 2013, 2018, and 2023 Censuses. Data is available by statistical area 2.
The variables included in this dataset are for the census usually resident population count (unless otherwise stated). All data is for level 1 of the classification (unless otherwise stated).
The variables for part 1 of the dataset are:
Download lookup file for part 1 from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.
Footnotes
Te Whata
Under the Mana Ōrite Relationship Agreement, Te Kāhui Raraunga (TKR) will be publishing Māori descent and iwi affiliation data from the 2023 Census in partnership with Stats NZ. This will be available on Te Whata, a TKR platform.
Geographical boundaries
Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.
Subnational census usually resident population
The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.
Population counts
Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts.
Caution using time series
Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).
Study participation time series
In the 2013 Census study participation was only collected for the census usually resident population count aged 15 years and over.
About the 2023 Census dataset
For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.
Data quality
The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.
Concept descriptions and quality ratings
Data quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.
Disability indicator
This data should not be used as an official measure of disability prevalence. Disability prevalence estimates are only available from the 2023 Household Disability Survey. Household Disability Survey 2023: Final content has more information about the survey.
Activity limitations are measured using the Washington Group Short Set (WGSS). The WGSS asks about six basic activities that a person might have difficulty with: seeing, hearing, walking or climbing stairs, remembering or concentrating, washing all over or dressing, and communicating. A person was classified as disabled in the 2023 Census if there was at least one of these activities that they had a lot of difficulty with or could not do at all.
Using data for good
Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.
Confidentiality
The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.
Measures
Measures like averages, medians, and other quantiles are calculated from unrounded counts, with input noise added to or subtracted from each contributing value during measures calculations. Averages and medians based on less than six units (e.g. individuals, dwellings, households, families, or extended families) are suppressed. This suppression threshold changes for other quantiles. Where the cells have been suppressed, a placeholder value has been used.
Percentages
To calculate percentages, divide the figure for the category of interest by the figure for 'Total stated' where this applies.
Symbol
-997 Not available
-999 Confidential
Inconsistencies in definitions
Please note that there may be differences in definitions between census classifications and those used for other data collections.
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TwitterThis layer contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values. The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: August 2025 (preliminary values at the state and county level) The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor force Data obtained from the U.S. Bureau of Labor Statistics. Data downloaded: October 1, 2025Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNation Data Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS"s county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2023 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.As of the January 2022 estimates released on March 18th, 2022, BLS is reporting new data for the two new census areas in Alaska - Copper River and Chugach - and historical data for the previous census area - Valdez Cordova.As of the March 17th, 2025 release, BLS now reports data for 9 planning regions in Connecticut rather than the 8 previous counties. To better understand the different labor force statistics included in this map, see the diagram below from BLS:
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TwitterThis dataset includes New York State historical shoreline positions represented as digital vector polylines from 1880 to 2015. Shorelines were compiled from topographic survey sheets from the National Oceanic and Atmospheric Administration (NOAA). Historical shoreline positions can be used to assess the movement of shorelines through time. Rates of shoreline change were calculated in ArcMap 10.5.1 using the Digital Shoreline Analysis System (DSAS) version 5.0. DSAS uses a measurement baseline method to calculate rate of change statistics. Transects are cast from the reference baseline to intersect each shoreline, establishing measurement points used to calculate shoreline change rates. For wetland shorelines these rates can be interpreted as accretion or erosion.
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TwitterMonthly data on federally administered Supplemental Security Income payments.
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Twitter2018-2023 Statistics on the work of the Legal Department
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TwitterThis dataset reflects is for the Individual Shelter & Rescue Statistics that were reported in 2018 for the 2017 Calendar year. Although PACFA requires this data to be submitted and takes all care possible to ensure the validity of this data, we do not control, and therefore guarantee, the complete accuracy, completeness and availability of data. PACFA believes this information to be within ± 4% margin of error. The CDA-PACFA is not responsible for any issues that may arise from the use of this data.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset contains data from California resident tax returns filed with California adjusted gross income and self-assessed tax listed by zip code. This dataset contains data for taxable years 1992 to the most recent tax year available.
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Twitterhttps://data.gov.tw/licensehttps://data.gov.tw/license
Demographic statistics of each township and city..
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TwitterThis dataset presents statistics on: the number of establishments; sales, value of shipments, or revenue; annual payroll; and number of employees whose NAICS classification has changed between the current and the previous economic censuses. Data are shown for 6-digit previous economic census NAICS industries and their 8-digit current economic census NAICS components for the U.S. Includes only establishments of firms with paid employees.
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TwitterThis dataset contains information about circulation (checkouts) by item type for each Norfolk Public Library branch location by month. The data begins July 2016 and is updated monthly.
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Figures at the Northern Ireland level, N I Civil Service staff numbers by department disaggregated by headcount, full-time equivalents, permanent, temporary/casual, gender and by analogous grade level for permanent staff. These are collated from the relevant electronic Human Resource (HR) systems on a quarterly basis and an accompanying statistical report is published on the NISRA website.https://www.nisra.gov.uk/statistics/ni-civil-service-human-resource-statistics/employment-statistics
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TwitterAnnual statistics of the number of ships and types of goods (on each dock)
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Twitterhttps://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
This guidance note sets out the recommended standard presentation of statistics for electoral areas within the countries and regions of the UK and is now available in accessible format. (File Size 125 KB)
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Characteristics of usual residents by whether they have previously served in the UK armed forces, with adjusted estimates for the non-veteran population, Census 2021.
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TwitterHydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).