The percentage of residential addresses for which the United States Postal Service has identified as being unoccupied (no mail collection) for a period of at least 90 days or longer. These properties may be habitable, but are not currently being occupied. It is important to note that a single residential property can contain more than one address. Source: U.S. Postal Service, U.S. Department of Housing and Urban Development Years Available: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

🇩🇪 독일 English Households total and by household size Household structure of the resident population by total number of households and by household size (by number of persons in the household). The data are presented for the city of Konstanz and for the 15 districts from 2010. The household structure of the resident population is not recorded directly in the population register. Therefore, the household generation programme HHGen is used to determine households in a multi-stage generation process. To this end, the programme identifies relationships between residents registered in Constance on the basis of family and birth names, the same residential address, the date of registration and other demographic characteristics such as age, gender, marital status and nationality. It is not always possible to capture all budgetary relations correctly. For this reason, the number of 1-person households tends to be overestimated and the number of 2-person households underestimated. The reason for this distortion is that, in particular, non-marital cohabitation or residential cohabitation cannot always be recognised as such. Source: City of Constance

Please be advised that there are issues with the Small Area boundary dataset generalised to 20m which affect Small Area 268014010 in Ballygall D, Dublin City. The Small Area boundary dataset generalised to 20m is in the process of being revised and the updated datasets will be available as soon as the boundaries are amended. This feature layer was created using Census 2016 data produced by the Central Statistics Office (CSO) and Small Areas national boundary data (generalised to 20m) produced by Tailte Éireann. The layer represents Census 2016 theme 2.3, the population usually resident in Ireland by usual residence 1 year before Census Day. Attributes include population breakdown by usual residence (e.g. same address, outside Ireland). Census 2016 theme 2 represents Migration, Ethnicity and Religion. The Census is carried out every five years by the CSO to determine an account of every person in Ireland. The results provide information on a range of themes, such as, population, housing and education. The data were sourced from the CSO. The Small Area Boundaries were created with the following credentials. National boundary dataset. Consistent sub-divisions of an ED. Created not to cross some natural features. Defined area with a minimum number of GeoDirectory building address points. Defined area initially created with minimum of 65 – approx. average of around 90 residential address points. Generated using two bespoke algorithms which incorporated the ED and Townland boundaries, ortho-photography, large scale vector data and GeoDirectory data. Before the 2011 census they were split in relation to motorways and dual carriageways. After the census some boundaries were merged and other divided to maintain privacy of the residential area occupants. They are available as generalised and non generalised boundary sets.

The data set of georeferenced existing addresses with residential location Wuppertal is created by a weekly automated intersection of the georeferenced existing addresses of the city of Wuppertal with the residential location map, which is updated and decided annually by the Evaluation Committee for Land Values in the City of Wuppertal. Currently, the delimitations of the residential areas are used, which were decided on 02.03.2021 as of 01.01.2021 and confirmed as unchanged on 31.03.2022 as of the reference date 01.01.2022. The residential map classifies the Wuppertal residential areas in four gradations (simple, medium, good and exclusive residential area) according to the predominant character of a coherent living area. (The location quality of individual plots may differ.) The current residential location map is a basis of the qualified rental mirror for the city of Wuppertal, which has been available since December 2016. The georeferenced inventory addresses are created by the weekly automated merging of the building references from the ALKIS Official Property Register Information System for the measured buildings and the monthly building references of existing but not yet measured buildings from the municipal information system Wunda/addresses. The coordinates of the building references to existing but not yet measured buildings differ in the order of a few meters from the ALKIS coordinates available only later. The dataset is provided in CSV format under an open data license (Data License Germany — Attribution — Version 2.0, dl-by-de/2.0).

Please be advised that there are issues with the Small Area boundary dataset generalised to 20m which affect Small Area 268014010 in Ballygall D, Dublin City. The Small Area boundary dataset generalised to 20m is in the process of being revised and the updated datasets will be available as soon as the boundaries are amended. This feature layer was was created using Census 2016 data produced by the Central Statistics Office (CSO) and Small Areas national boundary data (generalised to 20m) produced by Tailte Éireann. The layer represents Census 2016 theme 2.1, the population usually resident in Ireland by place of birth and nationality. Attributes include population breakdown by place of birth and nationality (e.g. UK Birthplace, Poland Nationality). Census 2016 theme 2 represents Migration, Ethnicity and Religion. The Census is carried out every five years by the CSO to determine an account of every person in Ireland. The results provide information on a range of themes, such as, population, housing and education. The data were sourced from the CSO. The Small Area Boundaries were created with the following credentials. National boundary dataset. Consistent sub-divisions of an ED. Created not to cross some natural features. Defined area with a minimum number of GeoDirectory building address points. Defined area initially created with minimum of 65 – approx. average of around 90 residential address points. Generated using two bespoke algorithms which incorporated the ED and Townland boundaries, ortho-photography, large scale vector data and GeoDirectory data. Before the 2011 census they were split in relation to motorways and dual carriageways. After the census some boundaries were merged and other divided to maintain privacy of the residential area occupants. They are available as generalised and non generalised boundary sets.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. ZIP Code Tabulation Areas (ZCTAs) are approximate area representations of U.S. Postal Service (USPS) ZIP Code service areas that the Census Bureau creates to present statistical data from Census 2000. The Census Bureau creates ZCTAs for the United States, Puerto Rico, American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands for the 2010 Census. Data users should not use ZCTAs to identify the official USPS ZIP Code for mail delivery. The USPS makes periodic changes to ZIP Codes to support more efficient mail delivery. For the 2010 Census, ZCTAs should more accurately represent the actual ZIP Codes at the time of their delineation than they did for Census 2000. This is because that before the tabulation blocks, which the ZCTAs are built from, were delineated for the 2010 Census, the Census Bureau undertook the process of inserting lines that could be used as 2010 Census tabulation block boundaries, and these lines split polygons where the result would be that a significant number of addresses would occur on either one or both sides of the line associated with a single ZIP Code. Each 2010 Census tabulation block that contains addresses is assigned to a single ZCTA, usually to the ZCTA that reflects the most frequently occurring ZIP Code for the addresses within that tabulation block. As a result, ZIP Codes associated with address ranges found in the Address Ranges relationship file may not always match the ZCTA. Blocks that do not contain addresses but are completely surrounded by a single ZCTA (enclaves) are assigned to the surrounding ZCTA. A ZCTA may not exist for every USPS ZIP Code. Some ZIP Codes may not have a matching ZCTA because too few addresses were associated with the specific ZIP Code or the ZIP Code was not the most frequently occurring ZIP Code within any of the blocks were it exists. The Census Bureau uses the addresses stored within MTDB to delineate ZCTAs, and at the time of the 2010 Census the MTDB primarily included addresses for residential or at least potentially residential structures, so ZCTAs representing only non-residential structures are infrequent. Also, in each tabulation block, if a choice existed between using a potential city-style mail delivery ZIP Code for an address or a post office box ZIP Code, the city-style mail delivery ZIP Code was preferred for the 2010 Census ZCTA delineation. The Census Bureau identifies 5-digit ZCTAs using a five-character numeric code that represents the most frequently occurring USPS ZIP Code within that ZCTA, and this code may contain leading zeros.

TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

NOTE: As of 2/16/2023, this table is not being updated. For data on COVID-19 updated (bivalent) booster coverage by town please to go to https://data.ct.gov/Health-and-Human-Services/COVID-19-Updated-Bivalent-Booster-Coverage-By-Town/bqd5-4jgh.

This table shows the number and percent of residents of each CT town that have initiated COVID-19 vaccination, are fully vaccinated and who have received additional dose 1 by age group.

All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected.

In the data shown here, a person who has received at least one dose of COVID-19 vaccine is considered to have initiated vaccination. A person is considered fully vaccinated if he/she has completed a primary vaccination series by receiving 2 doses of the Pfizer, Novavax or Moderna vaccines or 1 dose of the Johnson & Johnson vaccine. The fully vaccinated are a subset of the people who have received at least one dose.

A person who completed a Pfizer, Moderna, Novavax or Johnson & Johnson primary series (as defined above) and then had an additional monovalent dose of COVID-19 vaccine is considered to have had additional dose 1. The additional dose may be Pfizer, Moderna, Novavax or Johnson & Johnson and may be a different type from the primary series. For people who had a primary Pfizer or Moderna series, additional dose 1 was counted starting August 18th, 2021. For people with a Johnson & Johnson primary series additional dose 1 was counted starting October 22nd, 2021. For most people, additional dose 1 is a booster. However, additional dose 1 may represent a supplement to the primary series for a people who is moderately or severely immunosuppressed. Bivalent booster administrations are not included in the additional dose 1 calculations.

The percent with at least one dose many be over-estimated, and the percent fully vaccinated and with additional dose 1 may be under-estimated because of vaccine administration records for individuals that cannot be linked because of differences in how names or date of birth are reported.

Town of residence is verified by geocoding the reported address and then mapping it a town using municipal boundaries. If an address cannot be geocoded, the reported town is used. Out-of-state residents vaccinated by CT providers are excluded from the table.

The population denominators for these town- and age-specific coverage estimates are based on 2014 census estimates. This is the most recent year for which reliable town- and age-specific estimates are available. (https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Town-Population-with-Demographics). This census data is grouped in 5-year age bands. For vaccine coverage age groupings not consistent with a standard 5-year age band, each age was assumed to be 20% of the total within a 5-year age band. However, given the large deviation from this assumption for Mansfield because of the presence of the University of Connecticut, the age distribution observed in the 2010 census for the age bands 15 to 19 and 20 to 24 was used to estimate the population denominators.

Town-level coverage estimates have been capped at 100%. Observed coverage may be greater than 100% for multiple reasons, including census denominator data not including all individuals that currently reside in the town (e.g., part time residents, change in population size since the census), errors in address data or other reporting errors.

Caution should be used when interpreting coverage estimates for towns with large college/university populations since coverage may be underestimated. In the census, college/university students who live on or just off campus would be counted in the college/university town. However, if a student was vaccinated while studying remotely in his/her hometown, the student may be counted as a vaccine recipient in that town.

Connecticut COVID-19 Vaccine Program providers are required to report information on all COVID-19 vaccine doses administered to CT WiZ, the Connecticut Immunization Information System. Data on doses administered to CT residents out-of-state are being added to CT WiZ jurisdiction-by-jurisdiction. Doses administered by some Federal entities (including Department of Defense, Department of Correction, Department of Veteran’s Affairs, Indian Health Service) are not yet reported to CT WiZ.  Data reported here reflect the vaccination records currently reported to CT WiZ.

SVI refers to the CDC's Social Vulnerability Index - a measure that combines 15 demographic variables to identify communities most vulnerable to negative health impacts from disasters and public health crises. Measures of social vulnerability include socioeconomic status, household composition, disability, race, ethnicity, language, and transportation limitations - among others. Towns with a "yes" in the "Has SVI tract >0.75" field are those that have at least one census tract that is in the top quartile of vulnerability (e.g., a high-need area). 34 towns in Connecticut have at least one census tract in the top quartile for vulnerability.

Note: This dataset takes the place of the original "COVID-19 Vaccinations by Town" dataset (https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccinations-by-Town/pdqi-ds7f), which will not be updated after 4/15/2021. A dataset of vaccinations by town for all age groups is available here: https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccinations-by-Town/x7by-h8k4.

As part of continuous data quality improvement efforts, duplicate records were removed from the COVID-19 vaccination data during the weeks of 4/19/2021 and 4/26/2021.

Historical Data: Annual USPS Data by Zip Code for residential addresses for five parishes - St. Bernard, Plaquemines, East Baton Rouge, Ascension, and Livingston - for eleven years from 2005 through 2015 monthly USPS Data by Residential Zip Code For five parishes from March 2016 to December 2017.

Ongoing Data: Monthly USPS Data by Zip Code for residential addresses for five parishes - St. Bernard, Plaquemines, East Baton Rouge, Ascension, and Livingston - for two years beginning January 2018 through December 2019.

Comprehensive dataset containing 6 verified Residents association businesses in Illinois, United States with complete contact information, ratings, reviews, and location data.

Mid-year estimates of resident population for the respective calendar years, rebased on the 2011 Census by age and sex. The estimated resident population of an area includes all people who usually live there, whatever their nationality. Members of UK and non-UK armed forces stationed in the UK are included and UK forces stationed outside the UK are excluded. Students are taken to be resident at their term time address. To facilitate planning of health services at local level and provide denominators for epidemiological analyses. Legacy unique identifier: P00012

Percentage of residents who have lived at their current address for at least 5 years among residents aged 5 and older as a percentage on December 31, 2018 (MSS 2019, PLR, context indicator: K10), map with group formation based on standard deviation from the mean

Date created: Data first uploaded to Open Ottawa on August 11, 2021.Update frequency: Every 4 weeksAccuracy - Points of consideration for interpretation of the data:Data extracted by Ottawa Public Health from COVaxON, the Ontario provincial repository for vaccinations administered in Ontario and to residents of Ontario, using intellihealth Ontario. COVaxON is a dynamic system that allows for continuous updates. Because these data are a snapshot in time and reflect the most accurate information that OPH has at the time of reporting, the data presented may differ from previous and subsequent reports. A vaccinated individual is attributed to an Ottawa Neighbourhood Study (ONS) neighbourhood based on their postal code and, if postal code is missing, on their address, if available. Residents with a postal code that straddles more than one neighbourhood are allocated to neighbourhoods based on the relative size of the population residing in each of the straddled neighbourhoods. If there is no postal code or address information for an individual believed to reside in Ottawa, the resident is not attributed to a neighbourhood. For this reason, the number of first doses administered by neighbourhood does not sum to the total number of first doses administered among all Ottawa residents. In rural settings, the geographic boundaries of postal codes may span multiple health units. Since a client cannot be shared between health units, each postal code is attributed to a specific health unit by the Ministry of Health. This can cause artificially higher or lower vaccination rates in rural neighbourhoods as some non-Ottawa residents will be attributed to rural Ottawa neighbourhoods and some rural Ottawa residents will be attributed to other health units (i.e., excluded from our Ottawa resident counts. For these reasons, we are continuously monitoring and reviewing neighbourhood attributions in rural neighbourhoods using a client’s residential address, when available, and working with neighbouring health units to identify incorrectly attributed clients.Estimates of the number of residents 5 years of age and older (5+) and 18 years of age and older (18+), by ONS neighbourhood, are based on data provided by ICES using the Registered Persons Database (RPDB), which has basic demographic information for anyone who has an Ontario health card number and had contact with the health care system within 9 years or contact within 3 years for individuals 65 years and older. These estimates reflect the neighbourhood populations as of September 1, 2021.Estimation of these neighbourhood populations was provided by the Institute for Clinical Evaluative Sciences (ICES), which is funded by the Ontario Ministry of Health. Parts of this material are based on data and information compiled and provided by Ontario Ministry of Health, the Canadian Institute for Health Information and Public Health Ontario. The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of ICES, the OHDP, the funding or data sources; no endorsement is intended or should be inferred.The total 2020 5+ and 18+ population for Ottawa is based on the 2020 estimate from the 2016 Canadian Census and was downloaded from IntelliHealth, Ontario Ministry of Health, on November 29, 2021. Because of the different population data sources, neighbourhood populations and vaccinations will not sum to the totals for Ottawa.Rates with smaller populations are less stable and should be interpreted with caution.Attributes - Data fields:ONS_ID: Ottawa Neighbourhood Study neighbourhood ID number ONS_NAME: Ottawa Neighbourhood Study neighbourhood nameICES_POP_5plus: Number of residents 5 years of age or olderNum_dose1: Number of residents 5 years of age or older who have received at least one dose of vaccinePerc_eligible_dose1: Percent of residents 5 years of age or older who have received at least one dose of vaccineNum_fullyvacc: Number of residents 5 years of age or older who are fully vaccinated (i.e., have received two doses of a two-dose series or a single Johnson & Johnson vaccine)Perc_eligible_fullyvacc: Percent of residents 5 years of age or older who are fully vaccinated (i.e., have received two doses of a two-dose series or a single Johnson & Johnson vaccine)ICES_POP_18plus: Number of residents 18 years of age or olderNum_booster: Number of residents 18 years of older who have received a booster dose of vaccine Perc_eligible_boostervacc: Percent of residents 18 years of age or older who have received a booster doseAuthor: OPH Epidemiology Team & Ottawa Neighbourhood Study TeamAuthor email: OPH-Epidemiology@ottawa.caMaintainer Organization: Epidemiology & Evidence, Ottawa Public Health

The residential location refers to the quality of the location conditions of the further residential environment of an address compared to other addresses in the entire Berlin city area. In Berlin, a distinction is made in 3 residential areas: simple, medium, good.

Comprehensive dataset of 1 Residents associations in Ulsan, South Korea 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.

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: No - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: no - Households: Yes - Group quarters: A collective household is a group of persons that does not live in an ordinary household, but lives in a collective establishment, sharing meal times.

Universe

Residents of France, of any nationality. Does not include French citizens living in other countries, foreign tourists, or people passing through. Reintegrated persons: Persons living in group quarters or without a fixed address but having a usual home elsewhere (i.e., enumerated away from their usual residence). During data processing, most of these people are reintegrated into their usual households. Legal population refers to the population without duplicate counts (population sans double compte) and the institutional population (population comptee a part).

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: INSEE (Institut National de la Statisque et des Etudes Economiques)

SAMPLE SIZE (person records): 2934758.

SAMPLE DESIGN: 1/20 sample: A 1/5 systematic sample selected from 1/4 sample. 1/4 sample: a systematic sample of every 4th dwelling (or individual from institutional households). Dwellings, either for households/quasi-households or vacant dwellings, are sorted by locality and household size (if for households/quasi-households), before sampling. Individuals from communities/quasi-communities are sorted by locality, type of community and date of birth before sampling. All individuals within households constitute the 1/4 sample. Reintegrated persons: Persons living in group quarters or without a fixed address but having a usual home elsewhere (i.e., enumerated away from their usual residence). During data processing, most of these people are reintegrated into their usual households. Legal population refers to the population without duplicate counts (population sans double compte) and the institutional population (population comptee a part).

Mode of data collection

Face-to-face [f2f]

Research instrument

Form 1A for dwelling consists of (1) dwelling characteristics, (2) List A. permanent occupants of the dwelling, (3) List B. household members who do not live in the dwelling of enumeration, and (4) building characteristics; Form 2B. Individual form.

This dataset presents the preliminary estimates of the resident population by age and sex as at 30 June 2019. The data is aggregated to the 2019 edition of the Local Government Areas (LGA).

Estimated resident population (ERP) is the official estimate of the Australian population, which links people to a place of usual residence within Australia. Usual residence within Australia refers to that address at which the person has lived or intends to live for six months or more in a given reference year. For the 30 June reference date, this refers to the calendar year around it. Estimates of the resident population are based on Census counts by place of usual residence (excluding short-term overseas visitors in Australia), with an allowance for Census net undercount, to which are added the estimated number of Australian residents temporarily overseas at the time of the Census. A person is regarded as a usual resident if they have been (or expected to be) residing in Australia for a period of 12 months or more over a 16-month period.

This data is ABS data (catalogue number: 3235.0) available from the Australian Bureau of Statistics.

For more information please visit the Explanatory Notes.

• AURIN has spatially enabled the data.

• Regions which contain unpublished data have been left blank in the dataset.

This dataset presents the preliminary estimates of the resident population by age and sex as at 30 June 2017. The data is aggregated to Statistical Areas Level 4 (SA4), according to the 2016 edition of the Australian Statistical Geography Standard (ASGS). Estimated resident population (ERP) is the official estimate of the Australian population, which links people to a place of usual residence within Australia. Usual residence within Australia refers to that address at which the person has lived or intends to live for six months or more in a given reference year. For the 30 June reference date, this refers to the calendar year around it. Estimates of the resident population are based on Census counts by place of usual residence (excluding short-term overseas visitors in Australia), with an allowance for Census net undercount, to which are added the estimated number of Australian residents temporarily overseas at the time of the Census. A person is regarded as a usual resident if they have been (or expected to be) residing in Australia for a period of 12 months or more over a 16-month period. This data is ABS data (catalogue number: 3235.0) available from the Australian Bureau of Statistics. For more information please visit the Explanatory Notes. AURIN has spatially enabled the data. Regions which contain unpublished data have been left blank in the dataset.

Inside Airbnb is an independent, non-commercial set of tools and data that allows you to explore how Airbnb is really being used in cities around the world.

By analyzing publicly available information about a city's Airbnb's listings, Inside Airbnb provides filters and key metrics so you can see how Airbnb is being used to compete with the residential housing market.

With Inside Airbnb, you can ask fundamental questions about Airbnb in any neighbourhood, or across the city as a whole. Questions such as:

• "How many listings are in my neighbourhood and where are they?"
• "How many houses and apartments are being rented out frequently to tourists and not to long-term residents?"
• "How much are hosts making from renting to tourists (compare that to long-term rentals)?"
• "Which hosts are running a business with multiple listings and where they?"

The tools are presented simply, and can also be used to answer more complicated questions, such as:

• "Show me all the highly available listings in Bedford-Stuyvesant in Brooklyn, New York City, which are for the 'entire home or apartment' that have a review in the last 6 months AND booked frequently AND where the host has other listings."

These questions (and the answers) get to the core of the debate for many cities around the world, with Airbnb claiming that their hosts only occasionally rent the homes in which they live.

In addition, many city or state legislation or ordinances that address residential housing, short term or vacation rentals, and zoning usually make reference to allowed use, including:

• how many nights a dwelling is rented per year
• minimum nights stay
• whether the host is present
• how many rooms are being rented in a building
• the number of occupants allowed in a rental
• whether the listing is licensed

The Inside Airbnb tool or data can be used to answer some of these questions.

The data behind the Inside Airbnb site is sourced from publicly available information from the Airbnb site.

The data has been analyzed, cleansed and aggregated where appropriate to faciliate public discussion. Read more disclaimers here.

https://raw.githubusercontent.com/betanyc/getDataButton/master/png/120x60.png" style="box-sizing: border-box; vertical-align: middle;" vspace="5" width="120">If you would like to do further analysis or produce alternate visualisations of the data, it is available below under a Creative Commons CC0 1.0 Universal (CC0 1.0) "Public Domain Dedication" license.