We revisit Fair's (1978) theory of extramarital affairs using robust nonparametric methods developed for the analysis of categorical data. We find evidence suggesting that the number of years married is not a relevant predictor of the propensity to engage in extramarital affairs having controlled for other factors. This finding runs counter to the prevailing wisdom gleaned from misspecified parametric models.

This dataset is about books. It has 4 rows and is filtered where the book is After the affair : how to build trust and love again. It features 7 columns including author, publication date, language, and book publisher.

This dataset contains allegations brought to the attention of the Internal Affairs Division either through external complaints or internal complaint or recognition. Any information that can be used to uniquely identify the complainant or the involved employee will not be published. Update Frequency : Weekly.

This project includes a pdf capture of a webpage and the underlying data for the visualizations.State Summaries capture major facts about the Veteran population, including gender, age, population projections etc., and VA's presence in each state, including facilities and expenditures. The reports are produced by VA's National Center for Veterans Analysis and Statistics.

Public Affairs is responsible for the open data effort at DOE.

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The posted information shows opioid-dispensing rates for each facility and how those rates have changed over time. It is important to note that because the needs and conditions of Veterans may be different at each facility, the rates of the use of opioids may also be different for that reason, and cannot be compared directly. This information will be updated periodically.

This project includes a pdf capture of a webpage and the underlying data for the visualizations.State Summaries capture major facts about the Veteran population, including gender, age, population projections etc., and VA's presence in each state, including facilities and expenditures. The reports are produced by VA's National Center for Veterans Analysis and Statistics.

This dataset is about book series. It has 1 row and is filtered where the books is An affair with genius. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

Contains roughly 1200 datasets from the VA Open Data catalog, as made available through the data.json. Excludes datasets that have no public downloads. Also includes a _failures.csv for download links that lead to 404 errors, for posterity. About Open Data (from site): Open data is VA data that is freely available to the public. It is a by-product of the work the VA does for Veterans, and is not personal data (names, addresses, birthplace, etc…). The idea of open data is that public data should be easily accessible and usable by anyone to create products like web or mobile apps, infographics, or stories - the sky is really the limit. For years, government data has made it possible for innovators and entrepreneurs to create products of value for the American people (if you have ever used a GPS you have benefited from one of these products). We want to keep this tradition going. Packed with experimental SciOp CLI Pack command.

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Description of INSPIRE Download Service (predefined Atom): State Office for Social Affairs, Youth and Care – The link(s) for downloading the datasets is/are dynamically generated from GetFeature requests to a WFS 1.1.0

Comprehensive dataset of 6 Veterans affairs departments in New Hampshire, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 6 Veterans affairs departments in Vermont, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

NOTE: This dataset is no longer supported and is provided as-is. Any historical knowledge regarding meta data or it's creation is no longer available. All known information is proved as part of this data set. The Veteran Health Administration, in support of the Open Data Initiative, is providing the Veterans Affairs Suicide Prevention Synthetic Dataset (VASPSD). The VASPSD was developed using a real, record-level dataset provided through the VA Office of Suicide Prevention. The VASPSD contains no real Veteran information, however, it reflects similar characteristics of the real dataset. NOTICE: This data is intended to appear similar to actual VASPSD data but it does not have any real predictive modeling value. It should not be used in any real world application.

Comprehensive dataset of 28 Veterans affairs departments in Ohio, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Provide government data open platform download and browse statistics for each dataset

IntroductionUK Power Network maintains the 132kV voltage level network and below. An important part of the distribution network is the stepping down of voltage as it is moved towards the household; this is achieved using transformers. Transformers have a maximum rating for the utilisation of these assets based upon protection, overcurrent, switch gear, etc. This dataset contains the Grid Substation Transformers, also known as Bulk Supply Points, that typically step-down voltage from 132kV to 33kV (occasionally down to 66 or more rarely 20-25). These transformers can be viewed on the single line diagrams in our Long-Term Development Statements (LTDS) and the underlying data is then found in the LTDS tables.Care is taken to protect the private affairs of companies connected to the 33kV network, resulting in the redaction of certain transformers. Where redacted, we provide monthly statistics to continue to add value where possible. Where monthly statistics exist but half-hourly is absent, this data has been redacted.This dataset provides monthly statistics data across these named transformers from 2021 through to the previous month across our license areas. The data are aligned with the same naming convention as the LTDS for improved interoperability.To find half-hourly current and power flow data for a transformer, use the ‘tx_id’ that can be cross referenced in the Grid Transformers Half Hourly Dataset.If you want to download all this data, it is perhaps more convenient from our public sharepoint: Open Data Portal Library - Grid Transformers - All Documents (sharepoint.com)This dataset is part of a larger endeavour to share more operational data on UK Power Networks assets. Please visit our Network Operational Data Dashboard for more operational datasets.Methodological ApproachThe dataset is not derived, it is the measurements from our network stored in our historian.The measurement devices are taken from current transformers attached to the cable at the circuit breaker, and power is derived combining this with the data from voltage transformers physically attached to the busbar. The historian stores datasets based on a report-by-exception process, such that a certain deviation from the present value must be reached before logging a point measurement to the historian. We extract the data following a 30-min time weighted averaging method to get half-hourly values. Where there are no measurements logged in the period, the data provided is blank; due to the report-by-exception process, it may be appropriate to forward fill this data for shorter gaps.We developed a data redactions process to protect the privacy or companies according to the Utilities Act 2000 section 105.1.b, which requires UK Power Networks to not disclose information relating to the affairs of a business. For this reason, where the demand of a private customer is derivable from our data and that data is not already public information (e.g., data provided via Elexon on the Balancing Mechanism), we redact the half-hourly time series, and provide only the monthly averages. This redaction process considers the correlation of all the data, of only corresponding periods where the customer is active, the first order difference of all the data, and the first order difference of only corresponding periods where the customer is active. Should any of these four tests have a high linear correlation, the data is deemed redacted. This process is not simply applied to only the circuit of the customer, but of the surrounding circuits that would also reveal the signal of that customer.The directionality of the data is not consistent within this dataset. Where directionality was ascertainable, we arrange the power data in the direction of the LTDS "from node" to the LTDS "to node". Measurements of current do not indicate directionality and are instead positive regardless of direction. In some circumstances, the polarity can be negative, and depends on the data commissioner's decision on what the operators in the control room might find most helpful in ensuring reliable and secure network operation.Quality Control StatementThe data is provided "as is". In the design and delivery process adopted by the DSO, customer feedback and guidance is considered at each phase of the project. One of the earliest steers was that raw data was preferable. This means that we do not perform prior quality control screening to our raw network data. The result of this decision is that network rearrangements and other periods of non-intact running of the network are present throughout the dataset, which has the potential to misconstrue the true utilisation of the network, which is determined regulatorily by considering only by in-tact running arrangements. Therefore, taking the maximum or minimum of these transformers are not a reliable method of correctly ascertaining the true utilisation. This does have the intended added benefit of giving a realistic view of how the network was operated. The critical feedback was that our customers have a desire to understand what would have been the impact to them under real operational conditions. As such, this dataset offers unique insight into that.Assurance StatementCreating this dataset involved a lot of human data imputation. At UK Power Networks, we have differing software to run the network operationally (ADMS) and to plan and study the network (PowerFactory). The measurement devices are intended to primarily inform the network operators of the real time condition of the network, and importantly, the network drawings visible in the LTDS are a planning approach, which differs to the operational. To compile this dataset, we made the union between the two modes of operating manually. A team of data scientists, data engineers, and power system engineers manually identified the LTDS transformer from the single line diagram, identified the line name from LTDS Table 2a/b, then identified the same transformer in ADMS to identify the measurement data tags. This was then manually inputted to a spreadsheet. Any influential customers to that circuit were noted using ADMS and the single line diagrams. From there, a python code is used to perform the triage and compilation of the datasets. There is potential for human error during the manual data processing. These issues can include missing transformers, incorrectly labelled transformers, incorrectly identified measurement data tags, incorrectly interpreted directionality. Whilst care has been taken to minimise the risk of these issues, they may persist in the provided dataset. Any uncertain behaviour observed by using this data should be reported to allow us to correct as fast as possible.Additional informationDefinitions of key terms related to this dataset can be found in the Open Data Portal Glossary.Download dataset information: Metadata (JSON)We would be grateful if you find this dataset useful to submit a “reuse” case study to tell us what you did and how you used it. This enables us to drive our direction and gain better understanding for how we improve our data offering in the future. Click here for more information: Open Data Portal Reuses — UK Power Networks

Hunan: Govt Expenditure: Urban and Rural Community Affair data was reported at 102,340.000 RMB mn in 2024. This records a decrease from the previous number of 121,686.000 RMB mn for 2023. Hunan: Govt Expenditure: Urban and Rural Community Affair data is updated yearly, averaging 59,596.000 RMB mn from Dec 2007 (Median) to 2024, with 18 observations. The data reached an all-time high of 121,686.000 RMB mn in 2023 and a record low of 9,016.040 RMB mn in 2007. Hunan: Govt Expenditure: Urban and Rural Community Affair data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under China Premium Database’s Government and Public Finance – Table CN.FB: Local Government: Hunan.

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