These datasets contain measures of internet access per United States census tract and ZIP code tabulation area (ZCTA) from the 2015-2019 American Community Survey five-year estimate. Key variables include the number and percent of households per tract or ZCTA with any type of internet subscription, with broadband internet, and with a computer or smartphone.

US Census Bureau conducts American Census Survey 1 and 5 Yr surveys that record various demographics and provide public access through APIs. I have attempted to call the APIs through the python environment using the requests library, Clean, and organize the data in a usable format.

Data Ingestion and Cleaning:

ACS Subject data [2011-2019] was accessed using Python by following the below API Link: https://api.census.gov/data/2011/acs/acs1?get=group(B08301)&for=county:* The data was obtained in JSON format by calling the above API, then imported as Python Pandas Dataframe. The 84 variables returned have 21 Estimate values for various metrics, 21 pairs of respective Margin of Error, and respective Annotation values for Estimate and Margin of Error Values. This data was then undergone through various cleaning processes using Python, where excess variables were removed, and the column names were renamed. Web-Scraping was carried out to extract the variables' names and replace the codes in the column names in raw data.

The above step was carried out for multiple ACS/ACS-1 datasets spanning 2011-2019 and then merged into a single Python Pandas Dataframe. The columns were rearranged, and the "NAME" column was split into two columns, namely 'StateName' and 'CountyName.' The counties for which no data was available were also removed from the Dataframe. Once the Dataframe was ready, it was separated into two new dataframes for separating State and County Data and exported into '.csv' format

Data Source:

More information about the source of Data can be found at the URL below: US Census Bureau. (n.d.). About: Census Bureau API. Retrieved from Census.gov https://www.census.gov/data/developers/about.html

Final Word:

I hope this data helps you to create something beautiful, and awesome. I will be posting a lot more databases shortly, if I get more time from assignments, submissions, and Semester Projects 🧙🏼‍♂️. Good Luck.

The Census data API provides access to the most comprehensive set of data on current month and cumulative year-to-date exports using the End-use classification system. The End-use endpoint in the Census data API also provides value, shipping weight, and method of transportation totals at the district level for all U.S. trading partners. The Census data API will help users research new markets for their products, establish pricing structures for potential export markets, and conduct economic planning. If you have any questions regarding U.S. international trade data, please call us at 1(800)549-0595 option #4 or email us at eid.international.trade.data@census.gov.

Census ZIP Code Tabulation AreasThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau, displays ZIP Code Tabulation Areas. Per the USCB, “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 for each decennial 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.”Tabulation Area: 90069Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (ZIP Code Tabulation Areas) and will support mapping, analysis, data exports and OGC API – Feature access.Data.gov: Series Information for 2020 Census 5-Digit ZIP Code Tabulation Area (ZCTA5) National TIGER/Line Shapefiles, CurrentGeoplatform: Series Information for 2020 Census 5-Digit ZIP Code Tabulation Area (ZCTA5) National TIGER/Line Shapefiles, CurrentOGC API Features Link: (Census ZIP Code Tabulation Areas - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: ZIP Code Tabulation Areas (ZCTAs)For feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets

The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

The PCCF is a digital file which provides a correspondence between the CPC six-character postal code and Statistics Canada’s standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution. New to the June 2022 version, a separate data file is available for retired postal codes. The retired file uses the same record layout as the PCCF file. The same syntax file can be used for both the PCCF data file and the retired data file. The geographic coordinates, which represent the standard geostatistical areas linked to each postal code on the PCCF, are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for marketing, planning, or research purposes. In April 1983, the Statistical Geomatics Centre released the first version of the PCCF, which linked postal codes to 1981 Census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect changes. For this release of the PCCF, the postal codes are directly geocoded to 2021 Census geographic areas. A quality indicator for the confidence of this linkage is available in the PCCF.

This data comes from the 2010 Census Profile of General Population and Housing Characteristics. Zip codes are limited to those that fall at least partially within LA city boundaries. The dataset will be updated after the next census in 2020. To view all possible columns and access the data directly, visit http://factfinder.census.gov/faces/affhelp/jsf/pages/metadata.xhtml?lang=en&type=table&id=table.en.DEC_10_SF1_SF1DP1#main_content.

Census ZIP Code Tabulation Areas This feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau (USCB), displays ZIP Code Tabulation Areas in the United States. Per the USCB, “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 for each decennial 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.” Tabulation Area: 90210 Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (ZIP Code Tabulation Areas) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 58 (Series Information for 2020 Census 5-Digit ZIP Code Tabulation Area (ZCTA5) National TIGER/Line Shapefiles, Current)OGC API Features Link: (Census ZIP Code Tabulation Areas - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: ZIP Code Tabulation Areas (ZCTAs)For feedback please contact: Esri_US_Federal_Data@esri.comThumbnail source: Esri BasemapsNGDA Data Set This data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the “boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes.” For other NGDA Content: Esri Federal Datasets

Abstract

Dataset quality **: Medium/high quality dataset, not quality checked or modified by the EIDC team

Census data plays a pivotal role in academic data research, particularly when exploring relationships between different demographic characteristics. The significance of this particular dataset lies in its ability to facilitate the merging of various datasets with basic census information, thereby streamlining the research process and eliminating the need for separate API calls.

The American Community Survey is an ongoing survey conducted by the U.S. Census Bureau, which provides detailed social, economic, and demographic data about the United States population. The ACS collects data continuously throughout the decade, gathering information from a sample of households across the country, covering a wide range of topics

Methodology

The Census Data Application Programming Interface (API) is an API that gives the public access to raw statistical data from various Census Bureau data programs.

We used this API to collect various demographic and socioeconomic variables from both the ACS and the Deccenial survey on different geographical levels:

ZCTAs:

ZIP Code Tabulation Areas (ZCTAs) are generalized areal representations of United States Postal Service (USPS) ZIP Code service areas. The USPS ZIP Codes identify the individual post office or metropolitan area delivery station associated with mailing addresses. USPS ZIP Codes are not areal features but a collection of mail delivery routes.

Census Tract:

Census Tracts are small, relatively permanent statistical subdivisions of a county or statistically equivalent entity that can be updated by local participants prior to each decennial census as part of the Census Bureau’s Participant Statistical Areas Program (PSAP).

Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. A census tract usually covers a contiguous area; however, the spatial size of census tracts varies widely depending on the density of settlement. Census tract boundaries are delineated with the intention of being maintained over a long time so that statistical comparisons can be made from census to census.

Block Groups:

Block groups (BGs) are the next level above census blocks in the geographic hierarchy (see Figure 2-1 in Chapter 2). A BG is a combination of census blocks that is a subdivision of a census tract or block numbering area (BNA). (A county or its statistically equivalent entity contains either census tracts or BNAs; it can not contain both.) A BG consists of all census blocks whose numbers begin with the same digit in a given census tract or BNA; for example, BG 3 includes all census blocks numbered in the 300s. The BG is the smallest geographic entity for which the decennial census tabulates and publishes sample data.

Census Blocks:

Census blocks, the smallest geographic area for which the Bureau of the Census collects and tabulates decennial census data, are formed by streets, roads, railroads, streams and other bodies of water, other visible physical and cultural features, and the legal boundaries shown on Census Bureau maps.

Note: For information on data collection, confidentiality protection, nonsampling error, subject definitions, and guidance on using the data, access the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) Technical Documentation..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, access Improvements to the 2020 Census Race and Hispanic Origin Question Designs, Data Processing, and Coding Procedures..Data users may observe implausible and improbable data within this product and compared with other 2020 Census data products. For example, it is possible for a detailed group to have a larger count in a tract than in its corresponding county. For more information, access the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) Technical Documentation..Aggregating data, such as geographies and sex by age data, diminishes accuracy and increases the likelihood of inconsistent and improbable results. For guidance on creating custom aggregations from Detailed DHC-A data, access the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) Technical Documentation..Counts showing an "X" are suppressed for one of two reasons: (1) the count was negative or (2) it is an alone count larger than its equivalent alone or in any combination count. If the suppressed count is an alone count, data users should use the equivalent alone in any combination count, if it is available..This racial or ethnic group has sex by age data available for four age categories. More detailed age data are not available due to minimum population counts. For more information on the minimum population counts and accuracy, access the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) Technical Documentation..Washington, D.C. and American Indian/Alaska Native/Native Hawaiian (AIANNH) areas may show data when there should not be any displayed. This is due to postprocessing to ensure counts for statistically equivalent and coterminous geographies are consistent. For more information, access the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) Technical Documentation..Source: U.S. Census Bureau, 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A)

Key Table Information.Table Title.Manufacturing: E-Commerce Statistics for the U.S.: 2022.Table ID.ECNECOMM2022.EC2231ECOMM.Survey/Program.Economic Census.Year.2022.Dataset.ECN Core Statistics Manufacturing: E-Commerce Statistics for the U.S.: 2022.Release Date.2025-01-23.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.Sales, value of shipments, or revenue ($1,000)E-Shipments value ($1,000) E-Shipments as percent of total sales, value of shipments, or revenue (%) Range indicating imputed percentage of total sales, value of shipments, or revenueDefinitions 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 location where business is conducted or where services or industrial operations are performed. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization. For some industries, the reporting units are instead groups of all establishments in the same industry belonging to the same firm..Geography Coverage.The data are shown for the U.S. level only. For information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 2- through 3-digit 2022 NAICS code levels for the U.S. For information about NAICS, see Economic Census Code Lists..Sampling.The 2022 Economic Census sample includes all active operating establishments of multi-establishment firms and approximately 1.7 million single-establishment firms, stratified by industry and state. Establishments selected to the sample receive a questionnaire. For all data on this table, establishments not selected into the sample are represented with administrative data. For more information about the sample design, see 2022 Economic Census Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY23-099).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business’ data or identity.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing firms or three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the 2022 Economic Census Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, NAPCS codes, and more, see Economic Census Technical Documentation..Weights.No weighting applied as establishments not sampled are represented with administrative data..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector31/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.X - Not applicableA - Relative standard error of 100% or morer - Reviseds - Relative standard error exceeds 40%For a complete list of symbols, see Economic Census Data Dictionary..Data-Specific Notes.Data users who create their own es...

The United States census count (also known as the Decennial Census of Population and Housing) is a count of every resident of the US. The census occurs every 10 years and is conducted by the United States Census Bureau. Census data is publicly available through the census website, but much of the data is available in summarized data and graphs. The raw data is often difficult to obtain, is typically divided by region, and it must be processed and combined to provide information about the nation as a whole. The United States census dataset includes nationwide population counts from the 2000 and 2010 censuses. Data is broken out by gender, age and location using zip code tabular areas (ZCTAs) and GEOIDs. ZCTAs are generalized representations of zip codes, and often, though not always, are the same as the zip code for an area. GEOIDs are numeric codes that uniquely identify all administrative, legal, and statistical geographic areas for which the Census Bureau tabulates data. GEOIDs are useful for correlating census data with other censuses and surveys. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes. In April 1983, the Geography Division released the first version of the Postal Code Conversion File, which linked postal codes to census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect postal code changes provided by Canada Post Corporation. Every five years, the postal code linkages on the Postal Code Conversion File are “converted” to the latest census geographic areas. The original Postal Code Conversion File was linked to the 1981 Census geographic areas. Since then, the Postal Code Conversion File has undergone four “conversions”, following the 1986, 1991 and 1996 censuses. An automated system was used for the 1991-1996 conversion. Also, for the first time, the 1996 Census reported postal codes were used to validate the PCCF links. To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution.

Prior research has demonstrated that access to parks and greenspace can have a positive impact on many aspects of and contributors to health, including physical activity levels (Kaczynski et al., 2007), healthy aging (Finlay, 2015), and sense of well-being (Larson et al., 2016). Neighborhood parks can also contribute to sense of community (Gómez, 2015). These datasets describe the number and area of parks in each census tract or each ZIP code tabulation area (ZCTA) in the United States. Measures include the total number of parks, park area, and proportion of park area within each census tract or ZCTA.

From the United States Department of Agriculture’s Economic Research Service, the dataset contains information about US county’s ability to access supermarkets, supercenters, grocery stores, or other sources of healthy and affordable food. Most measures of how individuals and neighborhoods are able to access food are based on the following indicators: - Accessibility to sources of healthy food, as measured by distance to a store or by the number of stores in an area. - Individual-level resources that may affect accessibility, such as family income or vehicle availability. - Neighborhood-level indicators of resources, such as the average income of the neighborhood and the availability of public transportation.

Data Dictionary

Key	List of...	Comment	Example Value
County	String	County name	"Autauga County"
Population	Integer	Population count from 2010 census	54571
State	String	State name	"Alabama"
Housing Data.Residing in Group Quarters	Float	Count of tract population residing in group quarters	455.0
Housing Data.Total Housing Units	Integer	Occupied housing unit count from 2010 census	20221
Vehicle Access.1 Mile	Float	Housing units without vehicle count beyond 1 mile from supermarket	834.0
Vehicle Access.1/2 Mile	Float	Housing units without vehicle count beyond 1/2 mile from supermarket	1045.0
Vehicle Access.10 Miles	Float	Housing units without vehicle count beyond 10 miles from supermarket	222.0
Vehicle Access.20 Miles	Float	Housing units without vehicle count beyond 20 miles from supermarket	0.0
Low Access Numbers.Children.1 Mile	Float	Kids population count beyond 1 mile from supermarket	9973.0
Low Access Numbers.Children.1/2 Mile	Float	Kids population count beyond 1/2 mile from supermarket	13281.0
Low Access Numbers.Children.10 Miles	Float	Kids population count beyond 10 miles from supermarket	1199.0
Low Access Numbers.Children.20 Miles	Float	Kids population count beyond 20 miles from supermarket	0.0
Low Access Numbers.Low Income People.1 Mile	Float	Low income population count beyond 1 mile from supermarket	12067.0
Low Access Numbers.Low Income People.1/2 Mile	Float	Low income population count beyond 1/2 mile from supermarket	15518.0
Low Access Numbers.Low Income People.10 Miles	Float	Low income population count beyond 10 miles from supermarket	2307.0
Low Access Numbers.Low Income People.20 Miles	Float	Low income population count beyond 20 miles from supermarket	0.0
Low Access Numbers.People.1 Mile	Float	Population count beyond 1 mile from supermarket	37424.0
Low Access Numbers.People.1/2 Mile	Float	Population count beyond 1/2 mile from supermarket	49497.0
Low Access Numbers.People.10 Miles	Float	Population count beyond 10 miles from supermarket	5119.0
Low Access Numbers.People.20 Miles	Float	Population count beyond 20 miles from supermarket	0.0
Low Access Numbers.Seniors.1 Mile	Float	Seniors population count beyond 1 mile from supermarket	4393.0
Low Access Numbers.Seniors.1/2 Mile	Float	Seniors population count beyond 1/2 mile from supermarket	5935.0
Low ...

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show populations with computer and internet access by Zip Code Tabulation Area in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

Suffixes:

None

Change over two periods

_e

Estimate from most recent ACS

_m

Margin of Error from most recent ACS

_00

Decennial 2000

Attributes:

SumLevel

Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)

GEOID

Census tract Federal Information Processing Series (FIPS) code

NAME

Name of geographic unit

Planning_Region

Planning region designation for ARC purposes

Acres

Total area within the tract (in acres)

SqMi

Total area within the tract (in square miles)

County

County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)

CountyName

County Name

TotalHH_e

# Total households, 2017

TotalHH_m

# Total households, 2017 (MOE)

WithAComputer_e

# Households with a computer, 2017

WithAComputer_m

# Households with a computer, 2017 (MOE)

pWithAComputer_e

% Households with a computer, 2017

pWithAComputer_m

% Households with a computer, 2017 (MOE)

WithBroadband_e

# Households with broadband Internet, 2017

WithBroadband_m

# Households with broadband Internet, 2017 (MOE)

pWithBroadband_e

% Households with broadband Internet, 2017

pWithBroadband_m

% Households with broadband Internet, 2017 (MOE)

last_edited_date

Last date the feature was edited by ARC

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2013-2017

For additional information, please visit the Census ACS website.

Key Table Information.Table Title.Information: Summary Statistics for the U.S., States, and Selected Geographies: 2022.Table ID.ECNBASIC2022.EC2251BASIC.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.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 employeesRange 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 location where business is conducted or where services or industrial operations are performed. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization. For some industries, the reporting units are instead groups of all establishments in the same industry belonging to the same firm..Geography Coverage.The data are shown for the U.S., State, Combined Statistical Area, Metropolitan and Micropolitan Statistical Area, Metropolitan Division, Consolidated City, County (and equivalent), and Economic Place (and equivalent; incorporated and unincorporated) levels that vary by industry. For information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 2- through 6-digit 2022 NAICS code levels and selected 7-digit 2022 NAICS-based code levels. For information about NAICS, see Economic Census Code Lists..Sampling.The 2022 Economic Census sample includes all active operating establishments of multi-establishment firms and approximately 1.7 million single-establishment firms, stratified by industry and state. Establishments selected to the sample receive a questionnaire. For all data on this table, establishments not selected into the sample are represented with administrative data. For more information about the sample design, see 2022 Economic Census Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY23-099).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business’ data or identity.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing firms or three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the 2022 Economic Census Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, NAPCS codes, and more, see Economic Census Technical Documentation..Weights.No weighting applied as establishments not sampled are represented with administrative data..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.X - Not applicableA - Relative standard error of 100% or morer - Reviseds - Relative standard error exceeds 40%For a complete list of symbols, see Economic Census Data Dictionary..Data-Specific Notes.Data users who create their own estimates us...

What you get:

Upvote! The database contains +40,000 records on US Gross Rent & Geo Locations. The field description of the database is documented in the attached pdf file. To access, all 325,272 records on a scale roughly equivalent to a neighborhood (census tract) see link below and make sure to upvote. Upvote right now, please. Enjoy!

Get the full free database with coupon code: FreeDatabase, See directions at the bottom of the description... And make sure to upvote :) coupon ends at 2:00 pm 8-23-2017

Gross Rent & Geographic Statistics:

• Mean Gross Rent (double)
• Median Gross Rent (double)
• Standard Deviation of Gross Rent (double)
• Number of Samples (double)
• Square area of land at location (double)
• Square area of water at location (double)

Geographic Location:

• Longitude (double)
• Latitude (double)
• State Name (character)
• State abbreviated (character)
• State_Code (character)
• County Name (character)
• City Name (character)
• Name of city, town, village or CPD (character)
• Primary, Defines if the location is a track and block group.
• Zip Code (character)
• Area Code (character)

Abstract

The data set originally developed for real estate and business investment research. Income is a vital element when determining both quality and socioeconomic features of a given geographic location. The following data was derived from over +36,000 files and covers 348,893 location records.

License

Only proper citing is required please see the documentation for details. Have Fun!!!

Golden Oak Research Group, LLC. “U.S. Income Database Kaggle”. Publication: 5, August 2017. Accessed, day, month year.

For any questions, you may reach us at research_development@goldenoakresearch.com. For immediate assistance, you may reach me on at 585-626-2965

please note: it is my personal number and email is preferred

Check our data's accuracy: Census Fact Checker

Access all 325,272 location for Free Database Coupon Code:

Don't settle. Go big and win big. Optimize your potential**. Access all gross rent records and more on a scale roughly equivalent to a neighborhood, see link below:

• Website: Golden Oak Research make sure to upvote

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Food Access Research Atlas 2017

  Food Access Research atlas - Census tract-level overview of food access indicators using different measures of supermarket accessibility. Released 2017, data primarily from 2010 census. About USDA Food Security and Allocations Data: Links to several different USDA food security and allocations datasets, including a Census-level Food Access Research Atlas, county-level SNAP participation data through FY2020, and state-level total participant counts from FY2015 through FY2019 for the Commodity Supplemental Food Program, Emergency Food Assistance Program, and Food Distribution Program.
  Geography Level: State, County, Census TractItem Vintage: 2017
  Update Frequency: N/AAgency: USDAAvailable File Type: Excel 

  Return to Other Federal Agency Datasets Page

The British Household Panel Survey (BHPS) ran for 19 waves, from 1991-2009, and was conducted by the ESRC UK Longitudinal Studies Centre (ULSC), together with the Institute for Social and Economic Research (ISER) at the University of Essex. The ULSC, established in 1999, is a continuation of the research resource component of the ESRC Research Centre on Micro-Social Change (MISOC), established in 1989. In addition to running panel studies, ISER undertakes a programme of research based on panel data, using Understanding Society (see below), the BHPS and other national panels to monitor and measure social change.

The main objective of the BHPS was to further understanding of social and economic change at the individual and household level in Britain, and to identify, model and forecast such changes and their causes and consequences in relation to a range of socio-economic variables. It was designed as an annual survey of each adult member (aged 16 years and over) of a nationally representative sample of more than 5,000 households, making a total of approximately 10,000 individual interviews. The same individuals were re-interviewed in successive waves and, if they left their original households, all adult members of their new households were also interviewed. Children were interviewed once they reach the age of 16; there was also a special survey of household members aged 11-15 included in the BHPS from Wave 4 onwards (the British Youth Panel, or BYP). From Wave 9, two additional samples were added to the BHPS in Scotland and Wales, and at Wave 11 an additional sample from Northern Ireland (which formed the Northern Ireland Household Panel Study or NIHPS), was added to increase the sample to cover the whole of the United Kingdom. For Waves 7-11, the BHPS also provided data for the European Community Household Panel (ECHP). For details of sampling, methodology and changes to the survey over time, see Volume A of the documentation (Introduction, Technical Report and Appendices). From Wave 19, the BHPS was subsumed into a new longitudinal study called Understanding Society, or the United Kingdom Household Longitudinal Study (UKHLS), conducted by ISER. The BHPS Wave 19 is part of Understanding Society Wave 2 (January 2010-March 2011) (see under SN 6614). Further information is available on the Understanding Society series webpage.

BHPS Geographic data and other related studies:

• BHPS Medium-level Geographical Identifiers and Low-level Geographical Identifiers are available to registered users, subject to Special Licence access conditions;
• British National Grid postcode grid references for each BHPS household surveyed are also available, subject to Secure Access conditions;
• Several datasets from ISER-based BHPS research, and teaching/sampler data are also available;
• For details of all related data, see the BHPS series webpage.

The British Household Panel Survey, Waves 1-18, 1991-2008: 1991 Ward, Census Code Range (WARDC91) dataset contains the 1991 Electoral Ward (Census code range) geographic variable for each wave of the BHPS to date, and a household identification serial number for file matching to the main BHPS data. These data have more restrictive access conditions than those available under the standard End User Licence (see 'Access' section below). Those users who wish to make an application for these data should contact the HelpDesk for further details.

For the second edition (January 2014) revised geographic data files for each wave have been deposited. The documentation has also been updated.