In 2024, the number of visits to the Somerset House in the United Kingdom reached almost *** million. This figure represented a **** percent annual increase in visits.

Total number of patrons entering and exiting the library. In-house library visits are collected and calculated monthly using electronic gate counters. All libraries gather patron counts using the 3M / Bibliotheca security gates which count patrons as they enter and exit the library. Due to technical issues with the gate counters,Due to technical issues with the gate counters, the following numbers have been removed from the dataset. - 1/8/2019 Express Library removed a count of 8,392,559 - 3/7/2019 Main Library removed in count 62089 and out count 61916 - 7/3/2019 Dobson Ranch Library removed in count 276404 and out count 163364

The number of visits to the website christies.com declined in ********** over the same month of the previous year. As estimated, total views to the web page of the auction house Christie's totaled *** million in **********, decreasing by around ******* from **********.

The number of visits to the website sothebys.com decreased in March 2025 over the same month of the previous year. As estimated, total views to the web page of the auction house Sotheby's totaled *** million in March 2025. This figure represented a decline of roughly ******* visits compared to March 2024.

Rows: data for each inspector.

The number of visits to the website phillips.com declined in March 2025 over the same month of the previous year. As estimated, the web page of the auction house Phillips reported roughly 420,000 views in March 2025. This figure represented a 35 percent decline in visits compared to March 2024.

Abstract

The 1996 Papua New Guinea household survey is designed to measure the living standards of a random sample of PNG households. As well as looking at the purchases, own-production, gift giving/receiving and sales activities of households over a short period (usually 14 days), the survey also collects information on education, health, nutrition, housing conditions and agricultural activities. The survey also collects information on community level access to services for education, health, transport and communication, and on the price levels in each community so that the cost of living can be measured.

There are many uses of the data that the survey collects, but one main aim is for the results to help government, aid agencies and donors have a better picture of living conditions in all areas of PNG so that they can develop policies and projects that help to alleviate poverty. In addition, the survey will provide a socio-economic profile of Papua New Guinea, describing the access that the population has to agricultural, educational, health and transportation services, their participation in various economic activities, and household consumption patterns.

The survey is nationwide and the same questionnaire is being used in all parts of the country, including the urban areas. This fact can be pointed out if households find that some of the questions are irrelevant for their own living circumstances: there are at least some Papua New Guinean households for which the questions will be relevant and it is only by asking everyone the same questions that living standards can be compared.

Geographic coverage

The survey covers all provinces except Noth Solomons.

Analysis unit

• Household
• Individual
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The Household Listing Form and Selection of the Sample Listing of households is the first job to be done after the team has settled in and completed the introductions to the community. Listing is best done by the whole team working together. This way they all get to know the community and its lay-out. However, if the census unit is too large this wastes too much time. So before beginning asks how many households there are, very roughly, in the census unit (noting that teams are supplied with the number of households that were there in the 1990 census). If the answer is 80 or more, divide the team into two and have each half-team work on one sector of the community/village. See the section below on what to do when the listing work is divided up.

If the census unit is a "line-up point" that does not correspond to any single village or community the number of households will often exceed 200 and frequently they are also quite dispersed. In this case it is not practical to attempt to list the whole census unit, so a decision is made in advance to split the census unit into smaller areas (perhaps groupings of clans). First, a local informant must communicate the boundaries of the census unit and for natural or administrative sub-units with the larger census unit (such as hamlets; or canyons/valleys). The sub-units should be big enough to allow for the selection of a set of households (about 30 or more), but should not be so large that excessive transport time will be needed each day just to find the household. Once the subunit is defined, its boundaries should be clearly described. Then one of the smaller units is randomly selected and the procedures outlined above are then followed to complete the listing. Note: only one of the sub-units are listed, sample chosen, and interviews undertaken.

The most important thing in the listing is to be sure that you list all the households and only the households belonging to the named village or census unit (or subset of the census unit if it is a line-up point). In rural areas, explain to village leaders at the beginning: "We have to write down all the households belonging to (Name) village." In case of doubt, always ask: "Does this household belong to (Name) village?" In the towns, the selected area is shown on a map. Check that the address where you are listing is within the same area shown.

Also explain: "We only write down the name of the head of household. When we have the list of all the households, we will select 12 by chance, for interview."

Procedure for Listing The listing team walks around in every part of the village, accompanied by a guide who is a member of the village. If possible, find a person who conducted the 1990 Census in this community or someone with similar knowledge of the community and ask them to be your guide. Make sure you go to all parts of the village, including outlying hamlets. In hamlets, on in any place far from the centre, always check: "Do these people belong to (Name) village?"

In every part of the village, ask the guide about every house: "Who lives in this house? What is the name of the household head?" Note that you do not have to visit every household. At best, you just need to see each house but you do not need to go inside it or talk to anyone who lives there. Even the rule of seeing each house may be relaxed if there are far away household for which good information can be provided by the guide.

Enter the names of household heads in the lines of the listing form. One line is used for each household. As the lines are numbered, the procedure gives a number to each household. When you come to the last house, check with the guide: "Are you sure we have seen all the houses in the village?"

NOTE: It does not matter in what order you list the households as long as they are all listed. After the listing is complete, check that all lines are numbered consecutively with no gaps, from start to finish. The number on the last line should be exactly the number of households listed.

Note: If the list is long (say more than 30 households) interviewer may encounter difficulties when looking for their selected household. One useful way to avoid this is to show the approximately the place in the list here certain landmarks come. This can be done by writing in the margin, CHURCH or STORE or whatever. You can also indicate where the lister started in a hamlet, for example.

Sample Selection The sampling work is done by the supervisor. The first steps are done at the foot of the first page of the listing form. The steps to be taken are as follows:

1. Fill in the numbers asked for at the foot of the last listing page, as follows:
2. M: enter the total number of households listed (same as last household number shown).
3. Interval L: calculate (M / 15) to the nearest whole number.
4. R: This is a random number with 3-digit decimals between 0.000 and 0.999.

5. MR: multiply M by R and round to the nearest whole number. (If decimal 0.5, round up).

6. MR gives the 1st selection. (Exception: If MR=0, L gives the first selection.) Enter S against this line in the selection column of the list.

7. Count down the list, beginning after the 1st selection, a distance of L lines to get the 2nd selection, then another L to get the 3rd, etc. When you come to the bottom of the list, jump back to the top as if the list were circular. Stop after the 15th selection. Mark the 13th, 14th, and 15th selections "RES" (for reserve). Mark the 1st - 12th selection "S" (for selection).

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1996 Papua New Guinea Household Survey questionnaire consists of three basic parts:

Household questionnaire first visit: asks a series of questions about the household, discovering who lives there, what they do, their characteristics, where they live, and a little about what kinds of things they consume. This questionnaire consists of the following sections. - Section 1. Household Roster - Section 2. Education - Section 3. Income Sources - Section 4. Health - Section 5. Foods in the Diet - Section 6. Housing Conditions - Section 7. Agricultural Assets, Inputs and Services - Section 8. Anthropometrics - Section 9. Household Stocks

Consumption recall (second visit questionnaire): is focused primarily on assessing the household's expenditure, gift giving and recieving, production, and level of wealth. The information in the first and second visits will provide information that can determine the household's level of consumption, nutrition, degree of food security, and ways in which it organizes its income earning activities. This questionnaire consists of the following sections. - Section 1. Purchases of Food - Section 2. Other Frequent Purchases - Section 3. Own-production of Food - Section 4. Gifts Received: Food and Frequent Purchases (START) - Section 5. Annual Expenses and Gifts - Section 6. Inventory of Durable Goods - Section 7. Inward Transfers of Money - Section 8. Outward Transfers of Money - Section 9. Prices - Section 10. Repeat of Anthropometric Measurements - Section 11. Quality of Life

Community Questionnaire: which is completed by the interview team in consultation with community leaders. This questionnaire also includes market price surveys that are carried out by the team when they are working in the community. Associated with this is a listing of all households in the community, which has to be done prior to the selection of the 12 households. This questionnaire consists of the following sections. - Section A. Listing of Community Assets - Section B. Education - Section C. Health - Section D. Town or Government Station - Section E: Transport and Communications - Section F. Prices - Section G. Changes in Economic Activity, Infrastructure, and Services

This is a medical journal kept in accordance with the Lunacy Acts of 1868 (31 Vic. No.13) and 1879 (42 Vic. No.7). It shows weekly statements of number of patients in Bay View House; number of patients under restraint and in seclusion, their names and the reasons for and periods of such restraint or seclusion; the number and names of patients under medical treatment and the illness involved; and a column headed 'Condition of the Asylum', which invariably has the entry 'healthy'. There is also a column headed 'Deaths, Injuries and Violence to Patients since last entry'. This is subdivided into three columns by Dr Tucker, the first being used to show the names of patients and the third his signature. The second column occasionally carries entries about death or injury to patients and also medical details in some cases.

(5/92). 1 vol.

Note:

This description is extracted from Concise Guide to the State Archives of New South Wales, 3rd Edition 2000.

Abstract

The Measuring Living Standards in Cities (MLSC) survey is a new instrument designed to enhance understanding of cities in Africa and support evidence based policy design. The instrument was developed under the World Bank’s Spatial Development of African Cities Program, and was piloted in Dar es Salaam (Tanzania) and Durban (South Africa) over the course of 2014/15. These geo-referenced surveys provide information on urban living standards at an unprecedented level of granularity: they can be compared across different geographic levels within the cities, and between areas of ‘regular’ and ‘irregular’ settlement patterns. They also respond to the need to increased understanding of specifically ‘urban’ dimensions of quality of living: housing attributes, access to basic services, and commuting patterns, among others.

Geographic coverage

The survey covered households in Dar es Salaam, Tanzania.

Analysis unit

• Household

• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE FRAME

16,000 EAs generated by the Tanzania National Bureau of Statistics (NBS) for the 2012 Census.

STAGE ONE

200 EAs sorted into four strata. The central strata was divided into ‘central core, shanty’ and ‘central core, non-shanty’. Two EAs were replaced with reserve EAs as the original EAs were found to be inaccessible.

STAGE TWO

12 households randomly selected by systematic equal-probability from updated listing of each EA.

LISTING METHODOLOGY

The listing exercise took place between the first and the second stage of sampling. The household listing operations were implemented with computer assisted paperless interviewing (CAPI) techniques, which generates electronic files directly. Enumerators collected basic information about household: the name of the household head name, phone number and total number of household members living in the dwelling. Enumerators also recorded the GPS location of all structures,18 defined the type of structure, and aimed to provide measurement of structure size.

Listing was preceded by community sensitisation in both cities. In Dar es Salaam, enumerators visited the local chief (Mjumbe) of their assigned EA two days in advance of listing and on the day of listing.

Enumerators were equipped with maps created on Google My Maps to display shapefiles for the listing exercise. Hardcopies of their respective EA maps were also provided to be use in case of network failure. In Dar es Salaam, enumerators conducted a listing of all households in each of the selected EAs.

The listing exercise was conducted by 30 enumerators, each of which was assigned between 3 and 9 EAs for listing (enumerators were selected on the basis of performance from a group of 35 that were trained for listing). Enumerators were allocated EAs based on: (i) distance from enumerators’ homes in order to minimize transport time and cost; (ii) distance between the EAs; and (iii) safety and response rate considerations.

SURVEY IMPLEMENTATION

The surveys were fielded over the course of several months. The Dar es Salaam survey was implemented between November 2014 and January 2015.

Cases were assigned to interviewers using Survey Solutions. Interviewers were provided with both an electronic and hardcopy map, as well as a printed completion form, and could contact the listing manager through email, WhatsApp, or google hangouts if they were unable to find the assigned house.

Completing the survey often required repeat visits. This is because the survey required input from up to three separate respondents: the main respondent, who could be any present household member, and answered questions on household composition, basic information on members, assets, remittances, grants, housing, properties and consumption; the household head, who answered questions on residential history, satisfaction, employment, time use and commuting; and a random respondent, who was randomly selected from household members over the age of 12 (not including the head), who responded questions on satisfaction, employment, time use and commuting. Enumerators visited each house at least twice before a component could be marked as unavailable - in many cases, however, more than two visits were conducted.

Quality assurance procedures included: (i) In-interview feedback from CAPI, which provided a check that modules or questions were not missing, and alerted interviewers to mistakes and inconsistencies in given answers, so that these could be addressed while the interviewer was still with the respondent; (ii) Aggregate checks conducted using the Survey Solutions Supervisor application, which allows supervisors to identify common mistakes (applied to all initial interviews, and then through spot checks); interviewer performance and completion monitoring conducted by the implementing firm, through interviewer and EA level summaries of response rates, interview completion, and progress; (iii) weekly summaries of key indictors provided by the World Bank team (following each data delivery); (iv) direct observation of fieldwork; and (v) back check interviews. A key lesson learned is that the portion of back check interviews should be agreed in advance with the implementing firm: in Dar es Salaam back checks were conducted on 5% of the sample.

Mode of data collection

Computer Assisted Personal Interview [capi]

Response rate

Non-response rate: 13%

Net Additional Homes Provided - (YTD)

The net additional dwellings figure, or net supply of housing, is the absolute change in dwelling stock. It is derived from the number of new build completions; plus the net gain from dwelling conversions; plus the net gain of non-residential buildings brought into residential use; plus other gains and losses to the dwelling stock (such as mobile and temporary dwellings); less any demolitions during the financial year.

*These figures are only verified through the housing monitoring site visits undertaken bi-annually. Full breakdowns of net housing completions and consents are produced six monthly by Planning and Environmental Management and are published on the council website.

Zillow reigns supreme in the U.S. real estate website landscape, attracting a staggering ***** million monthly visits in 2024. This figure dwarfs its closest competitor, Realtor.com, which garnered less than half of Zillow's traffic. Online platforms are extremely popular, with the majority of homebuyers using a mobile device during the buying process. The rise of Zillow Founded in 2006, the Seattle-headquartered proptech Zillow has steadily grown over the years, establishing itself as the most popular U.S. real estate website. In 2023, the listing platform recorded about *** million unique monthly users across its mobile applications and website. Despite holding an undisputed position as a market leader, Zillow's revenue has decreased since 2021. A probable cause for the decline is the plummeting of housing transactions and the negative housing sentiment. Performance and trends in the proptech market The proptech market has shown remarkable performance, with companies like Opendoor and Redfin experiencing significant stock price increase in 2023. This growth is particularly notable in the residential brokerage segment. Meanwhile, major players in proptech fundraising, such as Fifth Wall and Hidden Hill Capital, have raised billions in direct investment, further fueling the sector's development. As technology continues to reshape the real estate industry, online platforms like Zillow are likely to play an increasingly crucial role in how people search for and purchase homes. (1477916, 1251604)

Graph and download economic data for Housing Inventory: Active Listing Count in the United States (ACTLISCOUUS) from Jul 2016 to Jun 2025 about active listing, listing, and USA.

Housing Voids 2025 2028 FCC. Published by Fingal County Council. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).This is a listing of the number of Council Houses that are with the Architects Department for Refitting or Refurbishment and Scheme Work to be done. Updated with Voids (stock off the system) in housing...

Windsor Castle and Frogmore House were the most popular Royal Estate locations in the United Kingdom in 2023/24. The site recorded over 1.4 million paid visitors between April 2023 and March 2024. While this figure denoted a significant increase over the previous fiscal year, it remained below the number of admissions reported in 2019/20, prior to the onset of the coronavirus (COVID-19) pandemic. Royal tourism in the UK The Royal Estate refers to British royal residences including palaces, castles, and houses owned or occupied by the British Monarchy. Only a selection of the estates are open to the public and give access to the Royal Collection (works of art held by the King in right of the Crown and in trust for his successors and for the nation). Even though the number of admissions remained below pre-pandemic levels, retail sales income from the Royal Estate in the UK bounced back in 2022/23, and continued to rise the following year. Queen Elizabeth II: the longest reigning British monarch Queen of the United Kingdom between 1952 and 2022, Elizabeth II was the longest reigning monarch in British history, having held the crown for 70 years and 214 days. Following her death on September 8, 2022, her eldest son acceded to the throne as King Charles III. For a selection of statistics and facts on the British monarchy, please check the dossier on The British Royal Family.

This has been derived based on net additional homes provided and the number of affordable homes delivered. This expresses a simple count of affordable housing units provided - newly built, including gains from conversions such as subdivision, and acquisitions, as a percentage of the net increase in overall dwelling stock over one year, calculated as the sum of new build completions, minus demolitions, plus any gains or losses through change of use and conversions.

Net additions does not include new delivery and acquisitions to the existing stock. Affordable housing is the sum of social rent, affordable rent, intermediate rent (including London Living Rent), affordable home ownership, shared ownership, London affordable rent and First Homes.

This should be considered alongside the actual numbers reported for affordable dwellings and overall new dwellings, however as these are given as absolute values for each area care should be taken when drawing any comparisons with other areas. Some percentages therefore may be over 100%.

New build figures are from the annual 'housing supply; net additional dwellings' statistical release may not correspond to new build data from the quarterly 'Housing supply: indicators of supply' building control reported completions statistical release. New build data collected for 'net additions dwellings' is more comprehensive, as this collection is over a longer time period, is based on all available evidence (e.g., site visits, council tax records, planning databases, building control records and any other sources), and may pick up some elements missing from the quarterly P2 and AIR collections (which are based on building control reported completions only).

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