US Industry Data by State, by Industry

Number of Establishments, Sales, Payroll, and Employees

By Gary Hoover [source]

About this dataset

This data set provides a detailed look into the US economy. It includes information on establishments and nonemployer businesses, as well as sales revenue, payrolls, and the number of employees. Gleaned from the Economic Census done every five years, this data is a valuable resource to anyone curious about where the nation was economically at the time. With columns including geographic area name, North American Industry Classification System (NAICS) codes for industries, descriptions of those codes meaning of operation or tax status, and annual payroll, this information-rich dataset contains all you need to track economic trends over time. Whether you’re a researcher studying industry patterns or an entrepreneur looking for market insight — this dataset has what you’re looking for!

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How to use the dataset

This dataset provides detailed US industry data by state, including the number of establishments, value of sales, payroll, and number of employees. All the data is based on the North American Industry Classification System (NAICS) code for each specific industry. This will allow you to easily analyze and compare industries across different states or regions.

Research Ideas

• Analyzing the economic impact of a new business or industry trends in different states: Comparing the change in the number of establishments, payroll, and employees over time can give insight into how a state is affected by a new industry trend or introduction of a new service or product.
• Estimating customer sales potential for businesses: This dataset can be used to estimate the potential customer base for businesses in different geographic areas. By analyzing total business done by non-employers in an area along with its estimated population can help estimate how much overall sales potential exists for a given region.
• Tracking competitor performance: By looking at shipments, receipts, and value of business done across industries in different regions or even cities, companies can track their competitors’ performance and compare it to their own to better assess their strategies going forward

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: 2012 Industry Data by Industry and State.csv | Column name | Description | |:----------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------| | Geographic area name | The name of the geographic area the data is for. (String) | | NAICS code | The North American Industry Classification System (NAICS) code for the industry. (String) | | Meaning of NAICS code | The description of the NAICS code. (String) | | Meaning of Type of operation or tax status code | The description of the type of operation or tax status code. (String) ...

This dataset shows the list of United States North American Industry Classification System (NAICS) Codes, Business Profiles by Sales and Employees. These codes are used by businesses and government authorities to differentiate types of business according to their process of production.

The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, Mexico and the United States. Created against the background of the North American Free Trade Agreement, it is designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate the analysis of the three economies. NAICS is based on supply-side or production-oriented principles, to ensure that industrial data, classified to NAICS, are suitable for the analysis of production-related issues such as industrial performance. NAICS Canada 2017 Version 2.0 consists of 20 sectors, 102 subsectors, 322 industry groups, 708 industries and 923 Canadian industries, and replaces NAICS 2017 Version 1.0.

Introduction

The dataset contains the Monthly sales for retail trade and food services in USA, adjusted and unadjusted for seasonal variations for various categories. These categories shows various kind of Business categories operating in USA. These categories are based on North American Industry Classification System (NAICS).

Dataset Description

• The dataset contains the estimates of Monthly Retail and Food Services Sales by Kind of Business from the year 1992 - 2020. These estimates are shown in millions of dollars and are based on data from the Monthly Retail Trade Survey, Annual Retail Trade Survey, * Service Annual Survey, and administrative records.
• Their are another to files that contain the monthly data for the code NAICS code 44X72: Retail Trade and Food Services: U.S. Total for both Seasonally Adjusted Sales and non Seasonally Adjusted Sales in Millions of Dollars from 1992 to 2020.
• An helper file for NAICS code for retail and food industry is also provided for reference

Acknowledgements

The Dataset was published on U.S. Census Bureau website (https://www.census.gov)

VITAL SIGNS INDICATOR
Jobs by Industry (EC1)

FULL MEASURE NAME
Employment by place of work by industry sector

LAST UPDATED
December 2022

DESCRIPTION
Jobs by industry refers to both the change in employment levels by industry and the proportional mix of jobs by economic sector. This measure reflects the changing industry trends that affect our region’s workers.

DATA SOURCE
Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW) - https://www.bls.gov/cew/downloadable-data-files.htm
1990-2021

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Quarterly Census of Employment and Wages (QCEW) employment data is reported by the place of work and represent the number of covered workers who worked during, or received pay for, the pay period that included the 12th day of the month. Covered employees in the private-sector and in the state and local government include most corporate officials, all executives, all supervisory personnel, all professionals, all clerical workers, many farmworkers, all wage earners, all piece workers and all part-time workers. Workers on paid sick leave, paid holiday, paid vacation and the like are also covered.

Besides excluding the aforementioned national security agencies, QCEW excludes proprietors, the unincorporated self-employed, unpaid family members, certain farm and domestic workers exempted from having to report employment data and railroad workers covered by the railroad unemployment insurance system. Excluded as well are workers who earned no wages during the entire applicable pay period because of work stoppages, temporary layoffs, illness or unpaid vacations.

The location quotient (LQ) is used to evaluate level of concentration or clustering of an industry within the Bay Area and within each county of the region. A location quotient greater than 1 means there is a strong concentration for of jobs in an industry sector. For the Bay Area, the LQ is calculated as the share of the region’s employment in a particular sector divided by the share of California's employment in that same sector. For each county, the LQ is calculated as the share of the county’s employment in a particular sector divided by the share of the region’s employment in that same sector.

Data is mainly pulled from aggregation level 73, which is county-level summarized at the North American Industry Classification System (NAICS) supersector level (12 sectors). This aggregation level exhibits the least loss due to data suppression, in the magnitude of 1-2 percent for regional employment, and is therefore preferred. However, the supersectors group together NAICS 11 Agriculture, Forestry, Fishing and Hunting; NAICS 21 Mining and NAICS 23 Construction. To provide a separate tally of Agriculture, Forestry, Fishing and Hunting, the aggregation level 74 data was used for NAICS codes 11, 21 and 23.

QCEW reports on employment in Public Administration as NAICS 92. However, many government activities are reported with an industry specific code - such as transportation or utilities even if those may be public governmental entities. In 2021 for the Bay Area, the largest industry groupings under public ownership are Education and health services (58%); Public administration (29%) and Trade, transportation, and utilities (29%). With the exception of Education and health services, all other public activities were coded as government/public administration, regardless of industry group.

For the county data there were some industries that reported 0 jobs or did not report jobs at the desired aggregation/NAICS level for the following counties/years:

Farm:
(aggregation level: 74, NAICS code: 11) - Contra Costa: 2008-2010 - Marin: 1990-2006, 2008-2010, 2014-2020 - Napa: 1990-2004, 2013-2021 - San Francisco: 2019-2020 - San Mateo: 2013

Information:
(aggregation level: 73, NAICS code: 51) - Solano: 2001

Financial Activities:
(aggregation level: 73, NAICS codes: 52, 53) - Solano: 2001

Unclassified:
(aggregation level: 73, NAICS code: 99) - All nine Bay Area counties: 1990-2000 - Marin, Napa, San Mateo, and Solano: 2020 - Napa: 2019 - Solano: 2001

The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, Mexico and the United States. Created against the background of the North American Free Trade Agreement, it is designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate the analysis of the three economies. NAICS is based on supply side or production oriented principles, to ensure that industrial data, classified to NAICS, is suitable for the analysis of production related issues such as industrial performance.

VITAL SIGNS INDICATOR
Jobs by Industry (EC1)

FULL MEASURE NAME
Employment by place of work by industry sector

LAST UPDATED
December 2022

DESCRIPTION
Jobs by industry refers to both the change in employment levels by industry and the proportional mix of jobs by economic sector. This measure reflects the changing industry trends that affect our region’s workers.

DATA SOURCE
Bureau of Labor Statistics, Quarterly Census of Employment and Wages (QCEW) - https://www.bls.gov/cew/downloadable-data-files.htm
1990-2021

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Quarterly Census of Employment and Wages (QCEW) employment data is reported by the place of work and represent the number of covered workers who worked during, or received pay for, the pay period that included the 12th day of the month. Covered employees in the private-sector and in the state and local government include most corporate officials, all executives, all supervisory personnel, all professionals, all clerical workers, many farmworkers, all wage earners, all piece workers and all part-time workers. Workers on paid sick leave, paid holiday, paid vacation and the like are also covered.

Besides excluding the aforementioned national security agencies, QCEW excludes proprietors, the unincorporated self-employed, unpaid family members, certain farm and domestic workers exempted from having to report employment data and railroad workers covered by the railroad unemployment insurance system. Excluded as well are workers who earned no wages during the entire applicable pay period because of work stoppages, temporary layoffs, illness or unpaid vacations.

The location quotient (LQ) is used to evaluate level of concentration or clustering of an industry within the Bay Area and within each county of the region. A location quotient greater than 1 means there is a strong concentration for of jobs in an industry sector. For the Bay Area, the LQ is calculated as the share of the region’s employment in a particular sector divided by the share of California's employment in that same sector. For each county, the LQ is calculated as the share of the county’s employment in a particular sector divided by the share of the region’s employment in that same sector.

Data is mainly pulled from aggregation level 73, which is county-level summarized at the North American Industry Classification System (NAICS) supersector level (12 sectors). This aggregation level exhibits the least loss due to data suppression, in the magnitude of 1-2 percent for regional employment, and is therefore preferred. However, the supersectors group together NAICS 11 Agriculture, Forestry, Fishing and Hunting; NAICS 21 Mining and NAICS 23 Construction. To provide a separate tally of Agriculture, Forestry, Fishing and Hunting, the aggregation level 74 data was used for NAICS codes 11, 21 and 23.

QCEW reports on employment in Public Administration as NAICS 92. However, many government activities are reported with an industry specific code - such as transportation or utilities even if those may be public governmental entities. In 2021 for the Bay Area, the largest industry groupings under public ownership are Education and health services (58%); Public administration (29%) and Trade, transportation, and utilities (29%). With the exception of Education and health services, all other public activities were coded as government/public administration, regardless of industry group.

For the county data there were some industries that reported 0 jobs or did not report jobs at the desired aggregation/NAICS level for the following counties/years:

Farm:
(aggregation level: 74, NAICS code: 11) - Contra Costa: 2008-2010 - Marin: 1990-2006, 2008-2010, 2014-2020 - Napa: 1990-2004, 2013-2021 - San Francisco: 2019-2020 - San Mateo: 2013

Information:
(aggregation level: 73, NAICS code: 51) - Solano: 2001

Financial Activities:
(aggregation level: 73, NAICS codes: 52, 53) - Solano: 2001

Unclassified:
(aggregation level: 73, NAICS code: 99) - All nine Bay Area counties: 1990-2000 - Marin, Napa, San Mateo, and Solano: 2020 - Napa: 2019 - Solano: 2001

Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Race for the U.S.: 2023.Table ID.ABSCS2023.AB00MYCSA01C.Survey/Program.Economic Surveys.Year.2023.Dataset.ECNSVY Annual Business Survey Company Summary.Source.U.S. Census Bureau, 2023 Economic Surveys, Annual Business Survey.Release Date.2025-11-20.Release Schedule.The Annual Business Survey (ABS) occurs every year, beginning in reference year 2017.For more information about ABS planned data product releases, see Tentative ABS Schedule..Dataset Universe.The dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Methodology.Data Items and Other Identifying Records.Number of employer firms (firms with paid employees)Sales and receipts of employer firms (reported in $1,000s of dollars)Number of employees (during the March 12 pay period)Annual payroll (reported in $1,000s of dollars)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Race White Black or African American American Indian and Alaska Native Asian Native Hawaiian and Other Pacific Islander Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White) Equally minority/nonminority Nonminority (Firms classified as non-Hispanic and White) Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) Definitions 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 ABS are employer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The data are shown for the U.S. only.For information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00") NAICS code. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Office of Notaries (NAICS 541120)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.The ABS sample includes firms that are selected with certainty if they have known research and development activities, were included in the 2023 BERD sample, or have high receipts, payroll, or employment. Total sample size is 330,000 firms. The universe is stratified by state, industry group, and expected demographic group. Firms selected to the sample receive a questionnaire. For all data on this table, firms not selected into the sample are represented with administrative, 2022 Economic Census, or other economic surveys records.For more information about the sample design, see Annual Business Survey 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. P-7504866, Disclosure Review Board (DRB) approval numbers: CBDRB-FY25-0115 and CBDRB-FY25-0410).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 data quality standards, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the Annual Business Survey Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, and more, see Technical Documentation..Weights.For more information about weighting, see Annual Business Survey Methodology..Table Inf...

The North American Industry Classification System (NAICS) is an industry classification sytems developed by the statistical agencies of Canada, Mexico and the United States. NAICS is based on production-oriented principles, to ensure that industrial data, classified to NAICS, are suitable for the analysis of production-related issues such as industrial performance. NAICS Canada 2012 updates NAICS Canada 2007. The new version was implemented in 2013 to coincide with the integration of Statistics Canada's business surveys into a generalized operational model.

Introduction

ExioNAICS is the first enterprise-level ML-ready benchmark dataset tailored for GHG emission estimation, bridging sector classification with carbon intensity analysis. In contrast to broad sectoral databases like ExioML, which offer global coverage of 163 sectors across 49 regions, ExioNAICS focuses on enterprise granularity by providing 20,850 textual descriptions mapped to validated NAICS codes and augmented with 166 sectoral carbon intensity factors. This design enables the automation of Scope 3 emission estimates (e.g., from purchased goods and services) at the firm level, a critical yet often overlooked component of supply chain emissions.

ExioNAICS is derived from the high-quality EE-MRIO dataset, ensuring robust economic and environmental data. By integrating firm-specific text descriptions, NAICS industry labels, and ExioML-based carbon intensity factors, ExioNAICS overcomes key data bottlenecks in enterprise-level GHG accounting. It significantly lowers the entry barrier for smaller firms and researchers by standardizing data formats and linking them to a recognized classification framework.

In demonstrating its usability, we formulate a NAICS classification and subsequent emission estimation pipeline using contrastive learning (Sentence-BERT). Our results showcase near state-of-the-art retrieval accuracy, paving the way for more accessible, cost-effective, and scalable approaches to corporate carbon accounting. ExioNAICS thus facilitates synergy between machine learning and climate research, fostering the integration of advanced NLP techniques in eco-economic studies at the enterprise scale.

Dataset

ExioNAICS serves as a hybrid textual and numeric dataset, capturing both enterprise descriptions (text modality) and sectoral carbon intensity factors (numeric modality). These data components are linked through NAICS codes, allowing end-to-end modeling of how enterprise descriptions map to sector emission intensities. Key dataset features include:

• Enterprise Description- NAICS Description- Sectoral Emission Factor- Over 20,000 textual entries- Hierarchical coverage: NAICS 2–6 digit codes (20 to 1,114 categories)

NAICS Classification

NAICS Classification is a fundamental component of enterprise-level GHG emission estimation. By assigning each firm to the appropriate sector category, practitioners can reference the corresponding carbon intensity factors, facilitating more accurate reporting. ExioNAICS adopts a natural language processing approach to NAICS classification, treating the task as an information retrieval problem.

Each enterprise description (query) is encoded separately, and matched against NAICS descriptions (corpus) based on the cosine similarity of their embeddings. This methodology leverages a dual-tower architecture, wherein the first tower processes the query (enterprise text) and the second tower processes NAICS descriptions.

We apply machine learning to fine-tune a pre-trained Sentence-BERT model. Zero-shot SBERT models may achieve only around 20% Top-1 accuracy on the 1000 classes sector classification task, whereas contrastive fine-tuning raises this to over 75%. Further preprocessing exceeding 77% Top-1 accuracy, such as lowercasing and URL removal, can add incremental gains, leading to state-of-the-art results.

Versions

Version 1 using ExioML as Emission Factor, Version 2 using EPA as Emission Factor.

Citation

@article{guo2025group, title={Group Reasoning Emission Estimation Networks}, author={Guo, Yanming and Qian, Xiao and Credit, Kevin and Ma, Jin}, journal={arXiv preprint arXiv:2502.06874}, year={2025} }

Table NameZIP Code Business Statistics: Total for Zip Code: 2014 Release ScheduleThe data in this file were released on May 19, 2016. Key Table InformationBeginning with reference year 2007, ZBP data are released using the Noise disclosure methodology to protect confidentiality. See Survey Methodologyfor complete information on the coverage and methodology of the ZIP Code Business Patterns data series. UniverseThe universe of this file is all operating establishments with one or more paid employees. This universe includes most establishments classified in the North American Industry Classification System (NAICS) Codes 11 through 813990. For specific exclusions and inclusions, see Industry Classification of Establishments. Geography CoverageThe data are shown at the 5-digit ZIP Code level only. Industry CoverageThe data are shown for NAICS code 00 (Total for all sectors) only. Data Items and Other Identifying RecordsThis file contains data on the number of establishments, total employment, first quarter payroll and annual payroll. Sort OrderData are presented in ascending ZIP Code sequence. FTP DownloadDownload the entire table at https://www2.census.gov/econ2014/CB/sector00/CB1400CZ11.zip. Contact InformationU.S. Census Bureau Economy-Wide Statistics Division Enterprise Statistics Branch Tel: (301)763-2580 Email: ewd.county.business.patterns@census.gov .Data User Notice posted on July 21, 2016: Census Bureau staff identified a processing error that affects selected data from the 2014 ZIP Code Business Patterns (ZBP). As a result, we suppressed 2014 employment and payroll totals in the Health Care and Social Assistance sector (Sector 62) for the ZIP code 49015. This processing error did not affect other ZIP codes. While suppressed values can be derived by subtraction, we do not recommend using the derived values in any analyses. The Census Bureau plans to release revised statistics at a later date..NOTE: Data based on the 2014 Zip Business Patterns. For information on confidentiality protection, nonsampling error, and definitions, see Survey Methodology..Source: U.S. Census Bureau, 2014 ZIP Code Business Patterns.

NEW!: Use the new Business Account Number lookup tool. SUMMARYThis dataset includes the locations of businesses that pay taxes to the City and County of San Francisco. Each registered business may have multiple locations and each location is a single row. The Treasurer & Tax Collector’s Office collects this data through business registration applications, account update/closure forms, and taxpayer filings. Business locations marked as “Administratively Closed” have not filed or communicated with TTX for 3 years, or were marked as closed following a notification from another City and County Department. The data is collected to help enforce the Business and Tax Regulations Code including, but not limited to: Article 6, Article 12, Article 12-A, and Article 12-A-1. http://sftreasurer.org/registration.HOW TO USE THIS DATASETSystem migration in 2014: When the City transitioned to a new system in 2014, only active business accounts were migrated. As a result, any businesses that had already closed by that point were not included in the current dataset.2018 account cleanup: In 2018, TTX did a major cleanup of dormant and unresponsive accounts and closed approximately 40,000 inactive businesses.To learn more about using this dataset watch this video.To update your listing or look up your BAN see this FAQ: Registered Business Locations ExplainerData pushed to ArcGIS Online on November 6, 2025 at 6:14 AM by SFGIS.Data from: https://data.sfgov.org/d/g8m3-pdisDescription of dataset columns:

 UniqueID
 Unique formula: @Value(ttxid)-@Value(certificate_number)


 Business Account Number
 Seven digit number assigned to registered business accounts


 Location Id
 Location identifier


 Ownership Name
 Business owner(s) name


 DBA Name
 Doing Business As Name or Location Name


 Street Address
 Business location street address


 City
 Business location city


 State
 Business location state


 Source Zipcode
 Business location zip code


 Business Start Date
 Start date of the business


 Business End Date
 End date of the business


 Location Start Date
 Start date at the location


 Location End Date
 End date at the location, if closed


 Administratively Closed
 Business locations marked as “Administratively Closed” have not filed or communicated with TTX for 3 years, or were marked as closed following a notification from another City and County Department.


 Mail Address
 Address for mailing


 Mail City
 Mailing address city



 Mail State
 Mailing address state



 Mail Zipcode
 Mailing address zipcode


 NAICS Code
 The North American Industry Classification System (NAICS) is a standard used by Federal statistical agencies for the purpose of collecting, analyzing and publishing statistical data related to the U.S. business economy. A subset of these are options on the business registration form used in the administration of the City and County's tax code. The registrant indicates the business activity on the City and County's tax registration forms.

See NAICS Codes tab in the attached data dictionary under About > Attachments.

 NAICS Code Description
 The Business Activity that the NAICS code maps on to ("Multiple" if there are multiple codes indicated for the business).


 NAICS Code Descriptions List
 A list of all NAICS code descriptions separated by semi-colon


 LIC Code
 The LIC code of the business, if multiple, separated by spaces


 LIC Code Description
 The LIC code description ("Multiple" if there are multiple codes for a business)


 LIC Code Descriptions List
 A list of all LIC code descriptions separated by semi-colon


 Parking Tax
 Whether or not this business pays the parking tax


 Transient Occupancy Tax
 Whether or not this business pays the transient occupancy tax


 Business Location
 The latitude and longitude of the business location for mapping purposes.


 Business Corridor
 The Business Corridor in which the the business location falls, if it is in one. Not all business locations are in a corridor.

Boundary reference: https://data.sfgov.org/d/h7xa-2xwk

 Neighborhoods - Analysis Boundaries
 The Analysis Neighborhood in which the business location falls. Not applicable outside of San Francisco.

Boundary reference: https://data.sfgov.org/d/p5b7-5n3h

 Supervisor District
 The Supervisor District in which the business location falls. Not applicable outside of San Francisco. Boundary reference: https://data.sfgov.org/d/xz9b-wyfc


 Community Benefit District
 The Community Benefit District in which the business location falls. Not applicable outside of San Francisco. Boundary reference: https://data.sfgov.org/d/c28a-f6gs


 data_as_of
 Timestamp the data was updated in the source system


 data_loaded_at
 Timestamp the data was loaded here (open data portal)


 SF Find Neighborhoods
 This column was automatically created in order to record in what polygon from the dataset 'SF Find Neighborhoods' (6qbp-sg9q) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.


 Current Police Districts
 This column was automatically created in order to record in what polygon from the dataset 'Current Police Districts' (qgnn-b9vv) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.


 Current Supervisor Districts
 This column was automatically created in order to record in what polygon from the dataset 'Current Supervisor Districts' (26cr-cadq) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.


 Analysis Neighborhoods
 This column was automatically created in order to record in what polygon from the dataset 'Analysis Neighborhoods' (ajp5-b2md) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.


 Neighborhoods
 This column was automatically created in order to record in what polygon from the dataset 'Neighborhoods' (jwn9-ihcz) the point in column 'location' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.

Note: If no description was provided by DataSF, the cell is left blank. See the source data for more information.

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...

Key Table Information.Table Title.Wholesale Trade: Sales and Commissions of Electronic Markets, Agents, Brokers, and Commission Merchants for the U.S.: 2022.Table ID.ECNCOMM2022.EC2242COMM.Survey/Program.Economic Census.Year.2022.Dataset.ECN Sector Statistics Sector 42: Wholesale Trade.Source.U.S. Census Bureau, 2022 Economic Census, Sector Statistics.Release Date.2025-07-10.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.The data in this file come from the 2022 Economic Census data files released on a flow basis starting in January 2024 with First Look Statistics. Preliminary U.S. totals released in January 2024 are superseded with final data shown in the releases of later economic census statistics through March 2026.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Methodology.Data Items and Other Identifying Records.Number of establishmentsSales, value of shipments, or revenue ($1,000)Sales on own account ($1,000)Sales made on the account of others ($1,000)Sales made on the account of others as percent of total sales, value of shipments, or revenue (%)Commissions received for sales made on the account of others ($1,000)Commissions received for sales made on the account of others as percent of sales on the account of others (%)Definitions 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 3- through 8-digit 2022 NAICS code levels within subsector 425. For information about NAICS, see Economic Census Code Lists..Business Characteristics.For Wholesale Trade (42), data are presented by Type of Operation (All establishments) only..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 some data on this table, estimates come only from the establishments selected into the sample. 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.For some data on this table, estimates come only from the establishments selected into the sample. For these estimates, selected establishments have sampling weights equal to the inverse of their selection probability, generally between 1 and 40. There is further weighting to account for nonresponse and to ensure that detailed estimates sum to basic statistics where applicable. For more information on weighting, see 2022 Economic Census Methodology..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector42/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing da...

Industry-year panel dataset derived from the VRscores 2024 release. Each record corresponds to a NAICS code and calendar year from 2012–2024 with at least five matched workers across any year. Variables include the NAICS code and description, worker counts, raw and imputed L2 voter registration counts by party, average match quality, raw and imputed partisan shares, two-party and overall margins, partisan diversity indices, effective number of parties, and a processing timestamp. The dataset contains 13,135 industry-year rows spanning roughly 1,010 NAICS codes per year. It is built from a matching of employment records from Revelio Labs (April 2025) with voter registration data from the L2 voter file (November 2024) using ensemble linkage techniques. Small industries (<5 matched workers) are excluded, one-to-one matches are enforced, and the VRscores methodology and working paper document the data processing and definitions. These files are provided in CSV format; they mirror the industry parquet release but are stored as comma-separated values for convenience.

Listing of all (active and inactive) businesses registered with the Office of Finance. An "active" business is defined as a registered business whose owner has not notified the Office of Finance of a cease of business operations. Update Interval: Monthly. NAICS Codes are from 2007 NAICS: https://www.census.gov/cgi-bin/sssd/naics/naicsrch?chart=2007

This dataset captures Kaggle machine learning competitions over time by project type, host-organization classification, and host-organization headquartered states. Data extraction and analysis were done by the Internet Association.

The following variables are included in the dataset:

start_date: Start date of the competition

end_date: End date of the competition

comp_org_conf: Host organization, company, or conference

primary_us_host: Primary host organization or company if the competition is sponsored by a conference or multiple hosts.

host_type: Private, nonprofit, or government

NAICS_code: 6 digit NAICS classification

NAICS: Definition of the 6 digit NAICS classification

hq_in_us: 1 - Yes, primary host is headquartered in US. 0 - No, host is not headquartered in US.

hq: Headquartered state of primary host

two_digit_definition: First 2 digit NAICS definition

three_digit_definition: First 3 digit NAICS definition

project_type: A classification of project based on project description

subtopic: Subtopic of the project type

project_title: Title of the competition

description: A brief description of the competition

prize: Prizes in US dollars

NAICS.link: link to NAICS code

Source: Internet Association. 2016. Machine Learning Awards. District of Columbia: Internet Association [producer]. Washington, DC: Internet Association. San Francisco, CA: Kaggle [distributor]. Web. 4 November 2016.

(StatCan Product) Customization details: This information product has been customized to present information on commodity sector estimates for Alberta and Canada for 2007 (Revised) and 2008 (Preliminary). Other variables include: NAICS Code, Commodity Code, NAICS and Commodity Description, Number of Establishments, Total Revenue, Revenue from Goods Manufactured (Financial Data), Revenue from Goods Manufactured (Commodity Data), Total Expenses, Total Salaries and Wages (Direct and Indirect Labour), Production Workers Wages (Direct Labour), Non-manufacturing Employees Salaries (Indirect Labour), Total Cost of Energy, Water Utility and Vehicle Fuel , Cost of Energy and Water Utility, Cost of Vehicle Fuel, Cost of Materials and Supplies, Total Number of Employees (Direct and Indirect Labour), Number of Production Workers (Direct Labour), Number of Manufacturing Employees (Indirect Labour), Total Opening Inventories, Opening Inventories - Goods or Work in Progress, Opening Inventories - Finished Goods Manufactured, Total Closing Inventories, Closing Inventories - Goods/Work in Progress, Closing Inventories - Finished Goods Manufactured, Manufacturing Value Added. For more information about the industries and commodity codes presented contact OSI.Support@gov.ab.ca. Annual Survey of Manufactures and Logging: The Annual Survey of Manufactures and Logging (ASML) is a survey of the manufacturing and logging industries in Canada. It is intended to cover all establishments primarily engaged in manufacturing and logging activities, as well as the sales offices and warehouses which support these establishments. The details collected include principal industrial statistics (such as revenue, employment, salaries and wages, cost of materials and supplies used, cost of energy and water utility, inventories, etc.), as well as information about the commodities produced and consumed. Data collected by the Annual Survey of Manufactures and Logging are important because they help measure the production of Canada's industrial and primary resource sectors, as well as provide an indication of the well-being of each industry covered by the survey and its contribution to the Canadian economy. Within Statistics Canada, the data are used by the Canadian System of National Accounts, the Monthly Survey of Manufacturing (record number 2101) and Prices programs. The data are also used by the business community, trade associations, federal and provincial departments, as well as international organizations and associations to profile the manufacturing and logging industries, undertake market studies, forecast demand and develop trade and tariff policies.

Uncovering Retail Trends with US Economic Census Data

2012 Store Types and Sales by Product Category

By Gary Hoover [source]

About this dataset

This US Retail Sales of Products and Services by Store dataset from the 2012 US Economic Census provides valuable insights into the different store types selling products and services in the United States. The dataset includes columns that specify various values like: Products and services code, Meaning of Products & Services Code, 2012 NAICS code, Code length, Meaning of 2012 NAICS Code, Number of Establishments, Total sales of Estabs Reporting Product Line ($1K), Sales ($1K), and Percent of Sales Accounted for by Industry (%). Gain a comprehensive view into what types of products are being sold across different stores within each product category—explore how they are performing relative to the industry with these analytical values. Analyze an in-depth perspective on where America’s retail market is headed

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How to use the dataset

This dataset provides information about the US retail sales of products and services by store type from 2012 US Economic Census. It is an interesting resource for analyzing the retail markets from a macro district perspective.
The dataset contains several columns which are key to a thorough analysis. These include: Products and services code, Meaning of Products and services code, 2012 NAICS code, Code length, Meaning of 2012 NAICS code, Number of establishments, Total sales of estabs reporting product line ($1,000), Sales ($1,000), and Percent of sales accounted for by industry (%).
To use this dataset in an effective manner it is important to consider following points: - Understand the meaning behind each column to fully comprehend what the data represents; - Analyze trends within categories or between different categories; - Use visualizations such as bar graphs or scatter plots to determine relationships between different variables; - Consider a variety factors when interpreting the data such as seasonality or population demographics in geographic regions; 5) Establish benchmarks for performance among similar stores; 6) Compare performance over time periods.

By using these tips you can effectively analyze datasets that uncover valuable insights into understanding trends within retail markets using US Economic Census Data

Research Ideas

• Identifying retail establishments with the highest demand for specific product and services categories.
• Analyzing retail store sales performance in different geographical locations to assess regional economic trends.
• Developing marketing campaigns to target specific stores that sell high volumes of certain products and services in order to increase overall sales

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: 2012 Retail Sales by Store Type within Product Category.csv | Column name | Description | |:----------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------| | Products and services code | A numerical code that identifies the type of product or service being sold. (Numeric) | | Meaning of Products and services code | A description of the product or service being sold. (Text) | | 2012 NAICS code | A numerical code that identifies the type of store selling the product or service...

Key Table Information.Table Title.Manufacturing: Materials Consumed by Kind of Industry for the U.S.: 2022.Table ID.ECNMATFUEL2022.EC2231MATFUEL.Survey/Program.Economic Census.Year.2022.Dataset.ECN Sector Statistics Combined version: Manufacturing and Mining: Materials Consumed and Selected Supplies, Minerals Received for Preparation, Purchased Machinery and Fuels Consumed by Type of Industry for the U.S..Source.U.S. Census Bureau, 2022 Economic Census, Sector Statistics.Release Date.2025-05-08.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.Material or fuel codeDelivered cost ($1,000)Definitions 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 6-digit 2022 NAICS code level. 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_Datasets/.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 w...