The Department of Licenses & Inspections reviews construction plans and conducts building inspections to ensure the safety of the workers and the public. Zoning permits are issued to authorize new construction or additions to a building or to authorize the change of use in a building or ground. Building permits are required before the start of a specific construction activity to enlarge, repair, change, add to or demolish a structure, and to install equipment or systems in a structure. Depending on the scale or type of construction activity, it may need to be first authorized via a zoning permit. Permit contractors are also available as a dataset. Plumbing and electrical permits, among others, may also be required for new or existing buildings. Please note that this is a very large dataset. If you are comfortable with APIs, you can also use the API links to access this data. You can learn more about how to use the API at Carto’s SQL API site and in the Carto guide in the section on making calls to the API.

View metadata for key information about this dataset.The Department of Licenses & Inspections reviews construction plans and conducts building inspections to ensure the safety of the workers and the public.Zoning permits are issued to authorize new construction or additions to a building or to authorize the change of use in a building or ground.Building permits are required before the start of a specific construction activity to enlarge, repair, change, add to or demolish a structure, and to install equipment or systems in a structure. Depending on the scale or type of construction activity, it may need to be first authorized via a zoning permit. Permit contractors are also available as a dataset. Plumbing and electrical permits, among others, may also be required for new or existing buildings.Please note that this is a very large dataset.If you are comfortable with APIs, you can also use the API links to access this data. You can learn more about how to use the API at Carto’s SQL API site and in the CARTO guide in the section on making calls to the API.For questions about this dataset, contact ligisteam@phila.gov. For technical assistance, email maps@phila.gov.

Nursing homes with residents positive for COVID-19 from 4/22/2020 to 6/19/2020. Starting in July 2020, this dataset will no longer be updated and will be replaced by the CMS COVID-19 Nursing Home Dataset, available at the following link: https://data.ct.gov/Health-and-Human-Services/CMS-COVID-19-Nursing-Home-Dataset/w8wc-65i5. Methods: 1) Laboratory-confirmed case counts are based upon data reported via the FLIS web portal. Nursing homes were asked to provide cumulative totals of residents with laboratory confirmed covid. This includes residents currently in-house, in the hospital, or who are deceased. Residents were excluded if they tested positive prior to initial admission to the nursing home. 2) The cumulative number of deaths among nursing home residents is based upon data reported by the Office of the Chief Medical Examiner. For public health surveillance, COVID-19-associated deaths include persons who tested positive for COVID-19 around the time of death (laboratory-confirmed) and persons whose death certificate lists COVID-19 disease as a cause of death or a significant condition contributing to death (probable). Limitations: 1) As of the week of 5/10/20, Point Prevalence Survey testing is being offered to all asymptomatic nursing home residents to inform infection prevention efforts. Point prevalence surveys will be conducted over a period of several weeks. Some nursing homes had adequate testing resources available to conduct surveys prior to this date. Differences in survey timing will impact the number of positive results that a nursing home reports. 2) Cumulative totals of residents testing positive are being collected rather than individual resident data. Thus we cannot verify the counts, de-duplicate, and/or verify whether there is a record of a positive lab test. This may result in either under- or over-counting. 3) The number of COVID-19 positive residents and the number of confirmed deaths among residents are tabulated from different data sources. Due to the timing of availability of test results for deceased residents, it is not appropriate to calculate the percent of cases who died due to COVID-19 at any particular facility based upon this data. 4) The count of deaths reported for 4/14 are not included in this dataset, as they were not broken out by laboratory-confirmed or probable. They can be viewed in the DPH Report here: https://portal.ct.gov/-/media/Coronavirus/CTDPHCOVID19summary4162020.pdf?la=en

This dataset has been deprecated and replaced by two new building permit datasets:

Building Permits: Addition/Alteration https://data.cambridgema.gov/Inspectional-Services/Building-Permits-Addition-Alteration/qu2z-8suj/data

New Building Permits https://data.cambridgema.gov/Inspectional-Services/New-Building-Permits/9qm7-wbdc/data

Description for Deprecated Dataset: Approved building permits for 1 and 2 family homes. Building permits are issued to licensed construction supervisors and enable recipients to construct, alter, or demolish a structure or install a sign. The building permit must be obtained from Cambridge's Inspectional Services Department before the start of any work and must be prominently posted at the job site. This dataset includes building permits for the construction of renovation of 1 and 2 family homes.

Analysis of ‘Nursing Homes with Residents Positive for COVID-19, April - June 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/8e9967f5-6ac9-44f7-8687-02fd436c3316 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Nursing homes with residents positive for COVID-19 from 4/22/2020 to 6/19/2020. Starting in July 2020, this dataset will no longer be updated and will be replaced by the CMS COVID-19 Nursing Home Dataset, available at the following link: https://data.ct.gov/Health-and-Human-Services/CMS-COVID-19-Nursing-Home-Dataset/w8wc-65i5.

Methods: 1) Laboratory-confirmed case counts are based upon data reported via the FLIS web portal. Nursing homes were asked to provide cumulative totals of residents with laboratory confirmed covid. This includes residents currently in-house, in the hospital, or who are deceased. Residents were excluded if they tested positive prior to initial admission to the nursing home. 2) The cumulative number of deaths among nursing home residents is based upon data reported by the Office of the Chief Medical Examiner. For public health surveillance, COVID-19-associated deaths include persons who tested positive for COVID-19 around the time of death (laboratory-confirmed) and persons whose death certificate lists COVID-19 disease as a cause of death or a significant condition contributing to death (probable).

Limitations: 1) As of the week of 5/10/20, Point Prevalence Survey testing is being offered to all asymptomatic nursing home residents to inform infection prevention efforts. Point prevalence surveys will be conducted over a period of several weeks. Some nursing homes had adequate testing resources available to conduct surveys prior to this date. Differences in survey timing will impact the number of positive results that a nursing home reports. 2) Cumulative totals of residents testing positive are being collected rather than individual resident data. Thus we cannot verify the counts, de-duplicate, and/or verify whether there is a record of a positive lab test. This may result in either under- or over-counting. 3) The number of COVID-19 positive residents and the number of confirmed deaths among residents are tabulated from different data sources. Due to the timing of availability of test results for deceased residents, it is not appropriate to calculate the percent of cases who died due to COVID-19 at any particular facility based upon this data. 4) The count of deaths reported for 4/14 are not included in this dataset, as they were not broken out by laboratory-confirmed or probable. They can be viewed in the DPH Report here: https://portal.ct.gov/-/media/Coronavirus/CTDPHCOVID19summary4162020.pdf?la=en

--- Original source retains full ownership of the source dataset ---

This dataset consists in 22 JSON files representing a season of the Spanish Football League ("La Liga").

The dataset represents several hierarchically related elements, however, only the Match, Event and Player elements contain relevant information for analysis. The rest of the elements simply serve to keep the data structured, by seasons and matchdays. The dataset collects information from several seasons between the years 2000 and 2022. The attributes of each of the elements that make up the dataset are described below:

Season: JSON documents represent a season, their root contains the following information:

competition: Name by which the competition is known

country: Country where the competition is held

season_id: Identifier of the season, example: Season 2021/22

season_url: Relative URL of the season's web page

rounds: List of Round elements, the days into which the championship is divided

Rounds: (or matchdays) Collection of matches:

number: Name of the matchday, e.g.: Matchday 1.

matches: List of Match elements, matches that are played on the same day/s of the championship.

Match: contains relevant match information.

id: Match identifier used at BeSoccer.com

status: Code representing the status of the match: Played (1), Not Played (0)

home_team: Name of the home team

away_team: Name of the away team

result: List of two integers representing the match score

date_time: Date and time at which the match started

referee: First and last name of the referee of the match

href: URL relative to the match page

home_tactic: Tactical arrangement of the home team, e.g.: 4-3-3

home_lineup: List of players in the starting lineup of the home team

home_bench: List of the home team's substitute players

away_tactic: Tactical arrangement of the away team, e.g. 4-3-3

away_lineup: List of players in the home team's starting lineup

away_bench: List of substitute players of the away team

Event: contains information that defines each of the relevant actions that occur during a soccer match. Events can be described by the following attributes:

player: Player identifier. Relative URL

team: Team of the player who participates in the event

minute: Minute of the match in which the event occurs

type: Event type (Enumeration)

Players: Player information:

name: First name

fullname: Player's full name

dob: Date of birth

country: Nationality

position: Position the player usually occupies: GOA (GoalKeeper), DF (Defender), MID (Midfielder), STR (Striker)

foot: Dominant Foot: Right-footed, Left-footed, Two-footed, Unknown

weight: Weight of player in kilograms

height: Player height in centimeters

elo: Measurement of the player's skills on a scale of 1 to 100

potential: Estimate of the maximum ELO that a player can reach on a scale of 1 to 100.

href: Relative URL of the player's record

This table provides an overview of the key figures on health and care available on StatLine. All figures are taken from other tables on StatLine, either directly or through a simple conversion. In the original tables, breakdowns by characteristics of individuals or other variables are possible. The period after the year of review before data become available differs between the data series. The number of exam passes/graduates in year t is the number of persons who obtained a diploma in school/study year starting in t-1 and ending in t.

Data available from: 2001

Status of the figures: 2024: The available figures are definite. 2023: Most available figures are definite Figures are provisional for: - perinatal mortality at pregnancy duration at least 24 weeks; - diagnoses known to the general practitioner; - supplied drugs; - AWBZ/Wlz-funded long term care; - persons employed in health and welfare; - persons employed in healthcare; - Mbo health care graduates; - Hbo nursing graduates / medicine graduates (university); - expenditures on health and welfare; - average distance to facilities. 2022: Most available figures are definite, figures are provisional for: - hospital admissions by some diagnoses; - physicians and nurses employed in care; - persons employed in health and welfare; - persons employed in healthcare; - expenditures on health and welfare; - profitability and operating results at institutions. 2021: Most available figures are definite, figures are provisional for: - expenditures on health and welfare. 2020 and earlier: All available figures are definite.

Changes as of 18 december 2024: - Distance to facilities: the figures withdrawn on 5 June have been replaced (unchanged). - Youth care: the previously published final results for 2021 and 2022 have been adjusted due to improvements in the processing. - Due to a revision of the statistics Expenditure on health and welfare 2021, figures for expenditure on health and welfare care have been replaced from 2021 onwards. - Due to the revision of the National Accounts, the figures on persons employed in health and welfare have been replaced for all years. - AWBZ/Wlz-funded long term care: from 2015, the series Wlz residential care including total package at home has been replaced by total Wlz care. This series fits better with the chosen demarcation of indications for Wlz care.

More recent figures have been added for: - crude birth rate; - live births to teenage mothers; - causes of death; - perinatal mortality at pregnancy duration at least 24 weeks; - life expectancy in perceived good health; - diagnoses known to the general practitioner; - supplied drugs; - AWBZ/Wlz-funded long term care; - youth care; - persons employed in health and welfare; - persons employed in healthcare; - expenditures on health and welfare; - average distance to facilities.

When will new figures be published? New figures will be published in July 2025.

The EVIDENT serious game explores consumer behaviour in response to a malfunctioning home appliance. Specifically, it examines how consumers approach decisions to repair or replace a broken home appliance and the impact of behavioural biases on these decisions. There are two key aims addressed within the EVIDENT serious game. 1) Determine the impact of socio-demographic factors, environmental literacy, and financial literacy on consumer willingness to pay for the repair of home appliances. 2) Determine the impact of information and education mediated through a serious game on consumer in-game and real-world repair/replace decision-making.

The serious game itself is a life-simulation game in which users are tasked with maintaining their virtual home while ensuring their avatar remains comfortable (i.e. basic needs such as hunger, warmth and hygiene are met) while monitoring their financial and energy consumption. Within this game, users learn that an appliance has malfunctioned, and a repairperson is called. Users must then determine how best to proceed by entering a negotiation with the repairperson.

The experiment consists of the following sections: 1) demographic information; 2) financial literacy; 3) environmental literacy; 4) serious game. The game receives as input the replies of the participant on the demographics information section to provide a personalized gameplay experience. Replies regarding participant's age ("What is your age?"), role ("Which of the following apply to you?"), income ("What is your household's annual income?"), gender ("Which character would you like to play with?") and family status ("How many people live in your home (including you) - Children") will be used to adjust players' avatar, starting amount of money, size of the house, age of the player and the negotiation process with the repair person.

The negotiation process differs based on the participants' role ("Which of the following apply to you?"). In this question, the participant can choose one of the following replies: 1) I am a homeowner, 2) I am a tenant (i.e. I pay someone to rent my accommodation), 3) I am a landlord (i.e. I receive payment for accommodation from someone else). Participants who rent (2) or are landlords (3) will be assigned to an additional in-game scenario to explore the unique context in which their energy decisions are made. Random allocation to a role will be applied for participants who select multiple options (i.e., homeowners who are also landlords).

More information on the EVIDENT Serious Game Experiment can be found on the public deliverables of the EVIDENT project https://evident-h2020.eu/deliverables/. More specifically, the serious game implementation design is described in deliverable D2.3 Serious game implementation design, the design of the experiment is reported in D2.2 Optimised Protocols Design, and the experiment preparatory actions are described in D3.1 Specifications of preparatory actions for RCT, surveys and serious game and D3.2 Implementation of preparatory actions for RCT, surveys and serious game.

Finally, the EVIDENT serious game can be found in the following locations:

EVIDENT Website: https://evident-h2020.eu/seriousgame

Google Play: https://play.google.com/store/apps/details?id=com.CERTH.EvidentSeriousGame

App Store: https://apps.apple.com/gr/app/evident-serious-game/id6447255106

EVIDENT Platform (participation in the experiment): https://platform.evident-h2020.eu/sessions/participate_session/1560d6e6-732a-470c-807a-c70472d51c53

This dataset provides a detailed record of active building condemnations in the city. Condemnation happens when a property is deemed unsafe or uninhabitable under building codes, often due to structural issues or health hazards. A condemned building doesn’t mean it’s automatically set to be torn down. Property owners can often step in to save these buildings by starting repair work or challenging the decision in court. See below details for technical definitions for condemnation and how they are remediated.

  A parcel is designated as condemned when an open and issued violation of "Condemnation - Main Structure" exists. This status remains in effect until one of the following occurs:


  The condemned structure is demolished, or
  A new Certificate of Occupancy is issued for the parcel.


  This dataset serves as a vital resource for tracking condemned properties and understanding the enforcement of building safety regulations within the city. It combines data from the city's Accela system with historical condemnation records previously maintained by Building & Housing (B&H) before the adoption of current Accela violation workflows.


  Update Frequency


  Weekly on Sundays at 7 AM EST (6 AM during daylight savings)


  Contacts


  Department of Building and Housing 216-664-2282


  Data Glossary

Parcel_Number: Permanent parcel number
Address: Address of condemned parcelActive_Condemnation: True/false field to confirm this is an active Condemnation. This should always be "Yes".
Condemnation_Date: Active condemnation start date on the parcel (Date is only available from Accela's condemnations)


The below fields are not from the system of record for permits, Accela. They are extra fields produced by the City"s Data Warehouse to make it more useful for staff and the public.DW_Parcel:Current Cuyahoga County parcel that matches this addressDW_Ward:Ward location of that parcelDW_Tract2020:Census tract ID of that parcelDW_Neighborhood:City neighborhood of that parcel

We have a comprehensive database of 100 most-selling companies for each country (in Europe and USA) for each market segment. We can integrate companies based on your specific needs and provide additional insights blending them with other market data.

The market segments we cover are: Animals & Pets Animal Health Animal Parks & Zoo Cats & Dogs Horses & Riding Pet Services Pet Stores Beauty & Well-being Cosmetics & Makeup Hair Care & Styling Personal Care Salons & Clinics Tattoos & Piercings Wellness & Spa Yoga & Meditation Business Services Administration & Services Associations & Centers HR & Recruiting Import & Export IT & Communication Office Space & Supplies Print & Graphic Design Research & Development Sales & Marketing Shipping & Logistics Wholesale Construction & Manufacturing Architects & Engineers Building Materials Chemicals & Plastic Construction Services Contractors & Consultants Factory Equipment Garden & Landscaping Industrial Supplies Manufacturing Production Services Tools & Equipment Education & Training Colleges & Universities Courses & Classes Education Services Language Learning Music & Theater Classes School & High School Specials Schools Vocational Training Electronics & Technology Appliances & Electronics Audio & Visual Computers & Phones Internet & Software Repair & Services Events & Entertainment Adult Entertainment Children's Entertainment Clubbing & Nightlife Events & Venues Gambling Gaming Museums & Exhibits Music & Movies Theater & Opera Wedding & Party Food, Beverages & Tobacco Agriculture & Produce Asian Grocery Stores Bakery & Pastry Beer & Wine Beverages & Liquor Candy & Chocolate Coffee & Tea Food Production Fruits & Vegetables Grocery Stores & Markets Lunch & Catering Meat, Seafood & Eggs Smoking & Tobacco Health & Medical Clinics Dental Services Diagnostics & Testing Doctors & Surgeons Health Equipment Hospital & Emergency Medical Specialists Mental Health Pharmacy & Medicine Physical Aids Pregnancy & Children Therapy & Senior Health Vision & Hearing Hobbies & Crafts Art & Handicraft Astrology & Numerology Fishing & Hunting Hobbies Metal, Stone & Glass Work Music & Instruments Needlework & Knitting Outdoor Activities Painting & Paper Home & Garden Bathroom & Kitchen Cultural Goods Decoration & Interior Energy & Heating Fabric & Stationery Furniture Stores Garden & Pond Home & Garden Services Home Goods Stores Home Improvements Home Services Cleaning Service Providers Craftsman House Services House Sitting & Security Moving & Storage Plumbing & Sanitation Repair Service Providers Legal Services & Government Customs & Toll Government Department Law Enforcement Lawyers & Attorneys Legal Service Providers Libraries & Archives Municipal Department Registration Services Media & Publishing Books & Magazines Media & Information Photography Video & Sound Money & Insurance Accounting & Tax Banking & Money Credit & Debt Services Insurance Investments & Wealth Real Estate Public & Local Services Employment & Career Funeral & Memorial Housing Associations Kids & Family Military & Veteran Nature & Environment Professional Organizations Public Services & Welfare Religious Institutions Shelters & Homes Waste Management Restaurants & Bars African & Pacific Cuisine Bars & Cafes Chinese & Korean Cuisine European Cuisine General Restaurants Japanese Cuisine Mediterranean Cuisine Middle Eastern Cuisine North & South American Cuisine Southeast Asian Cuisine Takeaway Vegetarian & Diet Shopping & Fashion Accessories Clothing & Underwear Clothing Rental & Repair Costume & Wedding Jewelry & Watches Malls & Marketplaces Sports Ball Games Bat-and-ball Games Bowls & Lawn Sports Dancing & Gymnastics Equipment & Associations Extreme Sports Fitness & Weight Lifting Golf & Ultimate Hockey & Ice Skating Martial arts & Wrestling Outdoor & Winter Sports Shooting & Target Sports Swimming & Water Sports Tennis & Racquet Sports Travel & Vacation Accommodation & Lodging Activities & Tours Airlines & Air Travel Hotels Travel Agencies Utilities Energy & Power Oil & Fuel Water Utilities Vehicles & Transportation Air & Water Transport Airports & Parking Auto Parts & Wheels Bicycles Cars & Trucks Motorcycle & Powersports Other Vehicles & Trailers Taxis & Public Transport Vehicle Rental Vehicle Repair & Fuel

Fields available for each shop since the date of the first review on Trustpilot:

• businessUrl
• companyName
• reviewDate
• verified
• reviewTitle
• reviewDescription
• reviewRating
• reviewCountry
• reviewLanguage
• reviewCompanyResponse
• consumerAvatar
• consumerName
• reviewUrl

Key Table Information.Table Title.Construction: Summary Statistics for the U.S., States, and Selected Geographies: 2022.Table ID.ECNBASIC2022.EC2223BASIC.Survey/Program.Economic Census.Year.2022.Dataset.ECN Core Statistics Summary Statistics for the U.S., States, and Selected Geographies: 2022.Source.U.S. Census Bureau, 2022 Economic Census, Core Statistics.Release Date.2024-12-05.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.The data in this file come from the 2022 Economic Census data files released on a flow basis starting in January 2024 with First Look Statistics. Preliminary U.S. totals released in January 2024 are superseded with final data shown in the releases of later economic census statistics through March 2026.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Methodology.Data Items and Other Identifying Records.Number of firmsNumber of establishmentsSales, value of shipments, or revenue ($1,000)Annual payroll ($1,000)First-quarter payroll ($1,000)Number of employeesConstruction workers annual wages($1,000)Construction workers for pay period including March 12Construction workers for pay period including June 12Construction workers for pay period including September 12Construction workers for pay period including December 12Construction, production and/or development and exploration workers annual hours (1,000)Other employees annual wages ($1,000)Other employees for pay period including March 12Other employees for pay period including June 12Other employees for pay period including September 12Other employees for pay period including December 12Total fringe benefits ($1,000)Employers cost for legally required fringe benefits ($1,000)Employers cost for voluntarily provided fringe benefits ($1,000)Total selected costs ($1,000) Cost of materials, components, packaging and/or supplies used, minerals received, or purchased machinery installed ($1,000)Cost of construction work subcontracted out to others ($1,000)Cost of purchased land ($1,000)Total cost of selected power, fuels, and lubricants ($1,000)Cost of gasoline and diesel fuel ($1,000)Cost of natural gas and manufactured gas ($1,000)Cost of on-highway use of gasoline and diesel fuel ($1,000)Cost of off-highway use of gasoline and diesel fuel ($1,000)Cost of all other fuels and lubricants ($1,000)Cost of purchased electricity ($1,000)Value of construction work ($1,000)Value of construction work on government owned projects ($1,000)Value of construction work on federally owned projects ($1,000)Value of construction work on state and locally owned projects ($1,000)Value of construction work on privately owned projects ($1,000)Value of other business done ($1,000)Value of construction work subcontracted in from others ($1,000)Net value of construction work ($1,000)Value added ($1,000)Materials and/or supplies, parts, fuels, etc. inventories, beginning of year ($1,000)Materials and/or supplies, parts, fuels, etc. inventories, end of year ($1,000)Gross value of depreciable assets (acquisition costs), beginning of year ($1,000)Total capital expenditures for buildings, structures, machinery, and equipment (new and used) ($1,000)Total retirements ($1,000)Gross value of depreciable assets (acquisition costs), end of year ($1,000)Total depreciation during year ($1,000)Total rental payments or lease payments ($1,000)Rental payments or lease payments for buildings and other structures ($1,000)Rental payments or lease payments for machinery and equipment ($1,000)Total other operating expenses ($1,000)Temporary staff and leased employee expenses ($1,000)Expensed computer hardware and other equipment ($1,000)Expensed purchases of software ($1,000)Data processing and other purchased computer services ($1,000)Communication services ($1,000)Repair and maintenance services of buildings and/or machinery ($1,000) Refuse removal (including hazardous waste) services ($1,000)Advertising and promotional services ($1,000)Purchased professional and technical services ($1,000) Taxes and license fees ($1,000)All other operating expenses ($1,000)Range indicating imputed percentage of total sales, value of shipments, or revenueRange indicating imputed percentage of total annual payrollRange indicating imputed percentage of total employeesDefinitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the economic census are employer establishments. An establishment is generally a single physical locati...

1) Data Introduction • The Major League Baseball Dataset contains various game data, including Elo ratings, predictive probabilities, pitcher information, and actual scores for each MLB game from 1871 to the latest season.

2) Data Utilization (1) Major League Baseball Dataset has characteristics that: • This dataset provides detailed game-specific information, including match dates, seasons, home/away teams, Elo ratings, team-by-team odds, starting pitchers, pitcher-by-pitcher adjustment scores, and actual match results. (2) Major League Baseball Dataset can be used to: • Development of game outcome prediction model: It can be utilized to build machine learning models that predict MLB game outcomes by utilizing various variables such as Elo rating, pitcher information, and team-specific predictive probabilities. • Team and Pitcher Performance Analysis: Analysis of Elo changes and pitcher impact by season and game can be used for in-depth performance analysis such as team strategy, pitcher replacement, and season outlook.

Seniors Home Repair Program Activity starting with the year 2009/2010.

These National Statistics provide monthly estimates of the number of residential and non-residential property transactions in the UK and its constituent countries. National Statistics are accredited official statistics.

England and Northern Ireland statistics are based on information submitted to the HM Revenue and Customs (HMRC) Stamp Duty Land Tax (SDLT) database by taxpayers on SDLT returns.

Land and Buildings Transaction Tax (LBTT) replaced SDLT in Scotland from 1 April 2015 and this data is provided to HMRC by https://www.revenue.scot/" class="govuk-link">Revenue Scotland to continue the time series.

Land Transaction Tax (LTT) replaced SDLT in Wales from 1 April 2018. To continue the time series, the https://gov.wales/welsh-revenue-authority" class="govuk-link">Welsh Revenue Authority (WRA) have provided HMRC with a monthly data feed of LTT transactions since July 2021.

LTT figures for the latest month are estimated using a grossing factor based on data for the most recent and complete financial year. Until June 2021, LTT transactions for the latest month were estimated by HMRC based upon year on year growth in line with other UK nations.

LTT transactions up to the penultimate month are aligned with LTT statistics.

Go to Stamp Duty Land Tax guidance for the latest rates and information.

Go to Stamp Duty Land Tax rates from 1 December 2003 to 22 September 2022 and Stamp Duty: rates on land transfers before December 2003 for historic rates.

The latest release was published 09:30 27 June 2025 and was updated with provisional data from completed transactions during May 2025.

The next release will be published 09:30 31 July 2025 and will be updated with provisional data from completed transactions during June 2025.

https://webarchive.nationalarchives.gov.uk/ukgwa/20240320184933/https://www.gov.uk/government/statistics/monthly-property-transactions-completed-in-the-uk-with-value-40000-or-above" class="govuk-link">Archive versions of the Monthly property transactions completed in the UK with value of £40,000 or above are available via the UK Government Web Archive, from the National Archives.

Overall attendance data include students in Districts 1-32 and 75 (Special Education). Students in District 79 (Alternative Schools & Programs), charter schools, home schooling, and home and hospital instruction are excluded. Pre-K data do not include NYC Early Education Centers or District Pre-K Centers; therefore, Pre-K data are limited to those who attend K-12 schools that offer Pre-K. Transfer schools are included in citywide, borough, and district counts but removed from school-level files. Attendance is attributed to the school the student attended at the time. If a student attends multiple schools in a school year, the student will contribute data towards multiple schools. Starting in 2020-21, the NYC DOE transitioned to NYSED's definition of chronic absenteeism. Students are considered chronically absent if they have an attendance of 90 percent or less (i.e. students who are absent 10 percent or more of the total days). In order to be included in chronic absenteeism calculations, students must be enrolled for at least 10 days (regardless of whether present or absent) and must have been present for at least 1 day. The NYSED chronic absenteeism definition is applied to all prior years in the report. School-level chronic absenteeism data reflect chronic absenteeism at a particular school. In order to eliminate double-counting students in chronic absenteeism counts, calculations at the district, borough, and citywide levels include all attendance data that contribute to the given geographic category. For example, if a student was chronically absent at one school but not at another, the student would only be counted once in the citywide calculation. For this reason, chronic absenteeism counts will not align across files. All demographic data are based on a student's most recent record in a given year. Students With Disabilities (SWD) data do not include Pre-K students since Pre-K students are screened for IEPs only at the parents' request. English language learner (ELL) data do not include Pre-K students since the New York State Education Department only begins administering assessments to be identified as an ELL in Kindergarten. Only grades PK-12 are shown, but calculations for "All Grades" also include students missing a grade level, so PK-12 may not add up to "All Grades". Data include students missing a gender, but are not shown due to small cell counts. Data for Asian students include Native Hawaiian or Other Pacific Islanders . Multi-racial and Native American students, as well as students missing ethnicity/race data are included in the "Other" ethnicity category. In order to comply with the Family Educational Rights and Privacy Act (FERPA) regulations on public reporting of education outcomes, rows with five or fewer students are suppressed, and have been replaced with an "s". Using total days of attendance as a proxy , rows with 900 or fewer total days are suppressed. In addition, other rows have been replaced with an "s" when they could reveal, through addition or subtraction, the underlying numbers that have been redacted. Chronic absenteeism values are suppressed, regardless of total days, if the number of students who contribute at least 20 days is five or fewer. Due to the COVID-19 pandemic and resulting shift to remote learning in March 2020, 2019-20 attendance data was only available for September 2019 through March 13, 2020. Interactions data from the spring of 2020 are reported on a separate tab. Interactions were reported by schools during remote learning, from April 6 2020 through June 26 2020 (a total of 57 instructional days, excluding special professional development days of June 4 and June 9). Schools were required to indicate any student from their roster that did not have an interaction on a given day. Schools were able to define interactions in a way that made sense for their students and families. Definitions of an interaction included: • Student submission of an assignment or completion of an

Note: Please use the following view to be able to see the entire Dataset Description: https://data.ct.gov/Environment-and-Natural-Resources/Hazardous-Waste-Portal-Manifest-Metadata/x2z6-swxe

Dataset Description Outline (5 sections)

• INTRODUCTION

• WHY USE THE CONNECTICUT OPEN DATA PORTAL MANIFEST METADATA DATASET INSTEAD OF THE DEEP DOCUMENT ONLINE SEARCH PORTAL ITSELF?

• WHAT MANIFESTS ARE INCLUDED IN DEEP’S MANIFEST PERMANENT RECORDS ARE ALSO AVAILABLE VIA THE DEEP DOCUMENT SEARCH PORTAL AND CT OPEN DATA?

• HOW DOES THE PORTAL MANIFEST METADATA DATASET RELATE TO THE OTHER TWO MANIFEST DATASETS PUBLISHED IN CT OPEN DATA?

• IMPORTANT NOTES

INTRODUCTION • All of DEEP’s paper hazardous waste manifest records were recently scanned and “indexed”. • Indexing consisted of 6 basic pieces of information or “metadata” taken from each manifest about the Generator and stored with the scanned image. The metadata enables searches by: Site Town, Site Address, Generator Name, Generator ID Number, Manifest ID Number and Date of Shipment. • All of the metadata and scanned images are available electronically via DEEP’s Document Online Search Portal at: https://filings.deep.ct.gov/DEEPDocumentSearchPortal/ • Therefore, it is no longer necessary to visit the DEEP Records Center in Hartford for manifest records or information. • This CT Data dataset “Hazardous Waste Portal Manifest Metadata” (or “Portal Manifest Metadata”) was copied from the DEEP Document Online Search Portal, and includes only the metadata – no images.

WHY USE THE CONNECTICUT OPEN DATA PORTAL MANIFEST METADATA DATASET INSTEAD OF THE DEEP DOCUMENT ONLINE SEARCH PORTAL ITSELF? The Portal Manifest Metadata is a good search tool to use along with the Portal. Searching the Portal Manifest Metadata can provide the following advantages over searching the Portal: • faster searches, especially for “large searches” - those with a large number of search returns unlimited number of search returns (Portal is limited to 500); • larger display of search returns; • search returns can be sorted and filtered online in CT Data; and • search returns and the entire dataset can be downloaded from CT Data and used offline (e.g. download to Excel format) • metadata from searches can be copied from CT Data and pasted into the Portal search fields to quickly find single scanned images. The main advantages of the Portal are: • it provides access to scanned images of manifest documents (CT Data does not); and • images can be downloaded one or multiple at a time.

WHAT MANIFESTS ARE INCLUDED IN DEEP’S MANIFEST PERMANENT RECORDS ARE ALSO AVAILABLE VIA THE DEEP DOCUMENT SEARCH PORTAL AND CT OPEN DATA? All hazardous waste manifest records received and maintained by the DEEP Manifest Program; including: • manifests originating from a Connecticut Generator or sent to a Connecticut Destination Facility including manifests accompanying an exported shipment • manifests with RCRA hazardous waste listed on them (such manifests may also have non-RCRA hazardous waste listed) • manifests from a Generator with a Connecticut Generator ID number (permanent or temporary number) • manifests with sufficient quantities of RCRA hazardous waste listed for DEEP to consider the Generator to be a Small or Large Quantity Generator • manifests with PCBs listed on them from 2016 to 6-29-2018. • Note: manifests sent to a CT Destination Facility were indexed by the Connecticut or Out of State Generator. Searches by CT Designated Facility are not possible unless such facility is the Generator for the purposes of manifesting.

All other manifests were considered “non-hazardous” manifests and not scanned. They were discarded after 2 years in accord with DEEP records retention schedule. Non-hazardous manifests include: • Manifests with only non-RCRA hazardous waste listed • Manifests from generators that did not have a permanent or temporary Generator ID number • Sometimes non-hazardous manifests were considered “Hazardous Manifests” and kept on file if DEEP had reason to believe the generator should have had a permanent or temporary Generator ID number. These manifests were scanned and included in the Portal.

Dates included: manifests with shipment dates from 1980 to present • States were the primary keepers of manifest records until June 29, 2018. Any manifest regarding a Connecticut Generator or Destination Facility should have been sent to DEEP, and should be present in the Portal and CT Data. • June 30, 2018 was the start of the EPA e-Manifest program. Most manifests with a shipment date on and after this date are sent to, and maintained by the EPA. • For information from EPA regarding these newer manifests: • Overview: https://rcrapublic.epa.gov/rcrainfoweb/action/modules/em/emoverview • To search by site, use EPA’s Sites List: https://rcrapublic.epa.gov/rcrainfoweb/action/modules/hd/handlerindex (Tip: Change the Location field from “National” to “Connecticut”) • Manifests still sent to DEEP on or after 6-30-2018 include: • manifests from exported shipments; and • manifest copies submitted pursuant to discrepancy reports and unmanifested shipments.

HOW DOES THE PORTAL MANIFEST METADATA RELATE TO THE OTHER TWO MANIFEST DATASETS PUBLISHED IN CT DATA? • DEEP has posted in CT Data two other datasets about the same hazardous waste documents which are the subject of the Portal and the Portal Manifest Metadata Copy. • There are likely some differences in the metadata between the Portal Manifest Metadata and the two others. DEEP recommends using all data sources for a complete search. • These two datasets were the best search tool DEEP had available to the public prior to the Portal and the Metadata Copy: • “Hazardous Waste Manifest Data (CT) 1984 – 2008” https://data.ct.gov/Environment-and-Natural-Resources/Hazardous-Waste-Manifest-Data-CT-1984-2008/h6d8-qiar; and • “Hazardous Waste Manifest Data (CT) 1984 – 2008: Generator Summary View” https://data.ct.gov/Environment-and-Natural-Resources/Hazardous-Waste-Manifest-Data-CT-1984-2008-Generat/72mi-3f82.
• The only difference between these two datasets is: • the first dataset includes all of the metadata transcribed from the manifests. • the second “Generator Summary View” dataset is a smaller subset of the first, requested for convenience by the public. Both of these datasets: • Are copies of metadata from a manifest database maintained by DEEP. No scanned images are available as a companion to these datasets. • The date range of the manifests for these datasets is 1984 to approximately 2008.

IMPORTANT NOTES (4): NOTE 1: Some manifest images are effectively unavailable via the Portal and the Portal Metadata due to incomplete or incorrect metadata. Such errors may be the result of unintentional data entry error, errors on the manifests or illegible manifests. • Incomplete or incorrect metadata may prevent a manifest from being found by a search. DEEP is currently working to complete the metadata as best it can. • Please report errors to the DEEP Manifest Program at deep.manifests@ct.gov. • DEEP will publish updates regarding this work here and through the DEEP Hazardous Waste Advisory Committee listserv. To sign up for this listserv, visit this webpage: https://portal.ct.gov/DEEP/Waste-Management-and-Disposal/Hazardous-Waste-Advisory-Committee/HWAC-Home. NOTE 2: This dataset does not replace the potential need for a full review of other files publicly available either on-line and/or at CT DEEP’s Records Center. For a complete review of agency records for this or other agency programs, you can perform your own search in our DEEP public file room located at 79 Elm Street, Hartford CT or at our DEEP Online Search Portal at: https://filings.deep.ct.gov/DEEPDocumentSearchPortal/Home. NOTE 3: Other DEEP programs or state and federal agencies may maintain manifest records (e.g., DEEP Emergency Response, US Environmental Protection Agency, etc.) These other manifests were not scanned along with those from the Manifest Program files. However, most likely these other manifests are duplicate copies of manifests available via the Portal. NOTE 4: search tips for using the Portal and CT Data: • If your search will yield a small number of search returns, try using the Portal for your search. “Small” is meant to mean fewer than the 500 maximum search returns allowed using the Portal. • Start your search as broadly as possible – try entering just the town and the street name, or a portion of the street name that is likely to be spelled correctly • For searches yielding a large number of search returns, try using first the Portal Manifest Metadata in CT Data. • Try downloading the metadata and sorting, filtering, etc. the data to look for related spellings, etc. • Once you narrow down you research, copy the manifest number of a manifest you are interested in, and paste it into the Agency ID field of the Portal search page. • If you are using information from older information sources for consistency, you may want to search the two datasets copied from the older DEEP Manifest Database.

Seniors Home Repair Program Activity starting with the year 2009/2010.