The average volume per capita, at home is forecast to experience significant growth in all segments in 2027. The trend observed from 2019 to 2027 remains consistent throughout the entire forecast period. There is a continuous increase in the average volume per capita, at home across all segments. Notably, the Hard Seltzer, at home segment achieves the highest value of 0.84 U.S. dollars at 2027. The Statista Market Insights cover a broad range of additional markets.

The Inventory of Owned and Leased Properties (IOLP) allows users to search properties owned and leased by the General Services Administration (GSA) across the United States, Puerto Rico, Guam and American Samoa. The Owned and Leased Data Sets include the following data except where noted below for Leases: Location Code - GSA’s alphanumeric identifier for the building Real Property Asset Name - Allows users to find information about a specific building Installation Name - Allows users to identify whether a property is part of an installation, such as a campus Owned or Leased - Indicates the building is federally owned (F) or leased (L) GSA Region - GSA assigned region for building location Street Address/City/State/Zip Code - Building address Longitude and Latitude - Map coordinates of the building (only through .csv export) Rentable Square Feet - Total rentable square feet in building Available Square Feet - Vacant space in building Construction Date (Owned Only) - Year built Congressional District - Congressional District building is located Senator/Representative/URL - Senator/Representative of the Congressional District and their URL Building Status (Owned Only) - Indicates building is active Lease Number (Leased Only) - GSA’s alphanumeric identifier for the lease Lease Effective/Expiration Dates (Leased Only) - Date lease starts/expires Real Property Asset Type - Identifies a property as land, building, or structure

Graph and download economic data for All Employees: Retail Trade: Furniture and Home Furnishings Stores in Puerto Rico (DISCONTINUED) (SMU72000004244200001SA) from Jan 1990 to Dec 2022 about furniture, retail trade, sales, retail, employment, and housing.

General Services Administration Owned PropertiesThis National Geospatial Data Asset (NGDA) dataset, shared as a General Services Administration (GSA) feature layer, displays federal government owned properties in the United States, Puerto Rico, Northern Mariana Islands, U.S. Virgin Islands, Guam and American Samoa. Per GSA, it is "the nation’s largest public real estate organization, provides workspace for over one million federal workers. These employees, along with government property, are housed in space owned by the federal government and in leased properties including buildings, land, antenna sites, etc. across the country."Federally owned buildings in downtown DCData currency: Current federal service (FC_IOLP_BLDG))NGDAID: 133 (Inventory of Owned and Leased Properties (IOLP))OGC API Features Link: Not AvailableFor more information: Real EstateFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets

In 2023, New York led all states in the United States with the highest population residing in public housing units. The number of residents in assisted houses in New York was more than *******, much higher than in other states. Other states with a high number of residents in government-aided accommodations included Pennsylvania and Puerto Rico, with both states having around 100,000 public housing residents. In contrast, Vermont recorded the lowest number of residents in public housing units, at just ***. North Dakota, Wyoming, and Idaho were also some of the states that had comparatively low populations, each reporting fewer than ***** people.

The Inventory of Owned and Leased Properties (IOLP) allows users to search properties owned and leased by the General Services Administration (GSA) across the United States, Puerto Rico, Guam and American Samoa.

The Owned and Leased Data Sets include the following data except where noted below for Leases:

• Location Code - GSA’s alphanumeric identifier for the building
• Owned or Leased - Indicates the building is Federally Owned (F) or Leased (L)
• GSA Region - GSA assigned region for building location.
• Street Address/City/State/Zip Code - Building Address.
• Latitude and Longitude - Map coordinates of the building.
• Building Rentable Square Feet - Total Rentable Square Feet in building.
• Available Square Feet - Vacant Space in building.
• Construction Date - Date of year built.
• Congressional District - Congressional District building is located. - Senator/Representative/URL - Senator/Representative of the Congressional District and their web address.

The Leased Data set also includes the following:

• Lease Number - GSA’s alphanumeric identifier for the lease.
• Lease Effective Date - Date lease starts.
• Lease Expiration Date - Date lease expires.

The property level flood risk statistics generated by the First Street Foundation Flood Model Version 2.0 come in CSV format.

The data that is included in the CSV includes:

An FSID; a First Street ID (FSID) is a unique identifier assigned to each location.

The latitude and longitude of a parcel as well as the zip code, census block group, census tract, county, congressional district, and state of a given parcel.

The property’s Flood Factor as well as data on economic loss.

The flood depth in centimeters at the low, medium, and high CMIP 4.5 climate scenarios for the 2, 5, 20, 100, and 500 year storms this year and in 30 years.

Data on the cumulative probability of a flood event exceeding the 0cm, 15cm, and 30cm threshold depth is provided at the low, medium, and high climate scenarios for this year and in 30 years.

Information on historical events and flood adaptation, such as ID and name.

This dataset includes First Street's aggregated flood risk summary statistics. The data is available in CSV format and is aggregated at the congressional district, county, and zip code level. The data allows you to compare FSF data with FEMA data. You can also view aggregated flood risk statistics for various modeled return periods (5-, 100-, and 500-year) and see how risk changes due to climate change (compare FSF 2020 and 2050 data). There are various Flood Factor risk score aggregations available including the average risk score for all properties (flood factor risk scores 1-10) and the average risk score for properties with risk (i.e. flood factor risk scores of 2 or greater). This is version 2.0 of the data and it covers the 50 United States and Puerto Rico. There will be updated versions to follow.

If you are interested in acquiring First Street flood data, you can request to access the data here. More information on First Street's flood risk statistics can be found here and information on First Street's hazards can be found here.

The data dictionary for the parcel-level data is below.

Field Name

Type

Description

fsid

int

First Street ID (FSID) is a unique identifier assigned to each location

long

float

Longitude

lat

float

Latitude

zcta

int

ZIP code tabulation area as provided by the US Census Bureau

blkgrp_fips

int

US Census Block Group FIPS Code

tract_fips

int

US Census Tract FIPS Code

county_fips

int

County FIPS Code

cd_fips

int

Congressional District FIPS Code for the 116th Congress

state_fips

int

State FIPS Code

floodfactor

int

The property's Flood Factor, a numeric integer from 1-10 (where 1 = minimal and 10 = extreme) based on flooding risk to the building footprint. Flood risk is defined as a combination of cumulative risk over 30 years and flood depth. Flood depth is calculated at the lowest elevation of the building footprint (largest if more than 1 exists, or property centroid where footprint does not exist)

CS_depth_RP_YY

int

Climate Scenario (low, medium or high) by Flood depth (in cm) for the Return Period (2, 5, 20, 100 or 500) and Year (today or 30 years in the future). Today as year00 and 30 years as year30. ex: low_depth_002_year00

CS_chance_flood_YY

float

Climate Scenario (low, medium or high) by Cumulative probability (percent) of at least one flooding event that exceeds the threshold at a threshold flooding depth in cm (0, 15, 30) for the year (today or 30 years in the future). Today as year00 and 30 years as year30. ex: low_chance_00_year00

aal_YY_CS

int

The annualized economic damage estimate to the building structure from flooding by Year (today or 30 years in the future) by Climate Scenario (low, medium, high). Today as year00 and 30 years as year30. ex: aal_year00_low

hist1_id

int

A unique First Street identifier assigned to a historic storm event modeled by First Street

hist1_event

string

Short name of the modeled historic event

hist1_year

int

Year the modeled historic event occurred

hist1_depth

int

Depth (in cm) of flooding to the building from this historic event

hist2_id

int

A unique First Street identifier assigned to a historic storm event modeled by First Street

hist2_event

string

Short name of the modeled historic event

hist2_year

int

Year the modeled historic event occurred

hist2_depth

int

Depth (in cm) of flooding to the building from this historic event

adapt_id

int

A unique First Street identifier assigned to each adaptation project

adapt_name

string

Name of adaptation project

adapt_rp

int

Return period of flood event structure provides protection for when applicable

adapt_type

string

Specific flood adaptation structure type (can be one of many structures associated with a project)

fema_zone

string

Specific FEMA zone categorization of the property ex: A, AE, V. Zones beginning with "A" or "V" are inside the Special Flood Hazard Area which indicates high risk and flood insurance is required for structures with mortgages from federally regulated or insured lenders

footprint_flag

int

Statistics for the property are calculated at the centroid of the building footprint (1) or at the centroid of the parcel (0)

This is a special extract of the 2000 Census 5-Percent Public Use Microdata Samples (PUMS) created by the National Archive of Computerized Data on Aging (NACDA). The file combines the individual 5-percent state files for all 50 states, the District of Columbia, and Puerto Rico as released by the United States Census Bureau into a single analysis file. The file contains information on all households that contain at least one person aged 65 years or more in residence as of the 2000 Census enumeration. The file contains individual records on all persons aged 65 and older living in households as well as individual records for all other members residing in each of these households. Consequently, this file can be used to examine both the characteristics of the elderly in the United States as well as the characteristics of individuals who co-reside with persons aged 65 and older as of the year 2000. All household variables from the household-specific "Household record" of the 2000 PUMS are appended to the end of each individual level record. This file is not a special product of the Census Bureau and is not a resample of the PUMS data specific to the elderly population. While it is comparable to the 1990 release CENSUS OF POPULATION AND HOUSING, 1990: [UNITED STATES]: PUBLIC USE MICRODATA SAMPLE: 3-PERCENT ELDERLY SAMPLE (ICPSR 6219), the sampling procedures and weights for the 2000 file reflect the methodology that applies to the 5-percent PUMS release CENSUS OF POPULATION AND HOUSING, 2000 [UNITED STATES]: PUBLIC USE MICRODATA SAMPLE: 5-PERCENT SAMPLE (ICPSR 13568). Person variables cover age, sex, relationship to householder, educational attainment, school enrollment, race, Hispanic origin, ancestry, language spoken at home, citizenship, place of birth, year of immigration, place of residence in 1985, marital status, number of children ever born, military service, mobility and personal care limitation, work limitation status, employment status, occupation, industry, class of worker, hours worked last week, weeks worked in 1989, usual hours worked per week, temporary absence from work, place of work, time of departure for work, travel time to work, means of transportation to work, total earnings, total income, wages and salary income, farm and nonfarm self-employment income, Social Security income, public assistance income, retirement income, and rent, dividends, and net rental income. Housing variables include area type, state and area of residence, farm/nonfarm status, type of structure, year structure was built, vacancy and boarded-up status, number of rooms and bedrooms, presence or absence of a telephone, presence or absence of complete kitchen and plumbing facilities, type of sewage facilities, type of water source, type of heating fuel used, property value, tenure, year moved into house/apartment, type of household/family, type of group quarters, household language, number of persons in the household, number of persons and workers in the family, status of mortgage, second mortgage, and home equity loan, number of vehicles available, household income, sales of agricultural products, payments for rent, mortgage and property tax, condominium fees, mobile home costs, and cost of electricity, water, heating fuel, and flood/fire/hazard insurance.

In 2021, the United States (X units), distantly followed by Germany (X units), China (X units), the UK (X units), Slovenia (X units) and the Netherlands (X units) represented the largest exporters of trailers and semi-trailers of the caravan type, for housing or camping, together constituting 81% of total exports. The following exporters - Australia (X units), France (X units), Denmark (X units) and Hungary (X units) - together made up 11% of total exports.

The Inventory of Owned and Leased Properties (IOLP) allows users to search properties owned and leased by the General Services Administration (GSA) across the United States, Puerto Rico, Guam and American Samoa.GSA Inventory of Owned and Leased Properties (IOLP) Buildings includes the following data:Location Code - GSA’s alphanumeric identifier for the buildingOwned or Leased - Indicates the building is Federally Owned (F) or Leased (L)GSA Region - GSA assigned region for building location.Street Address/City/State/Zip Code - Building Address.Latitude and Longitude - Map coordinates of the building.Building Rentable Square Feet - Total Rentable Square Feet in building.Available Square Feet - Vacant Space in building.Construction Date - Date of year built.Congressional District - Congressional District building is located. - Senator/Representative/URL - Senator/Representative of the Congressional District and their web address.