The U.S. manufacturing sector plays a central role in the economy, accounting for 20% of U.S. capital investment, 60% of the nation's exports and 70% of business R&D. Overall, the sector's market size, measured in terms of revenue is worth roughly $6 trillion, making it a major industry to do business with. So which U.S. states are the biggest for manufacturing? This article will explore the nation's top manufacturing states, measured by number of employees, based on MNI's database of 400,000 U.S. manufacturing companies.

This dataset provides values for MANUFACTURING PMI reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset provides values for WAGES IN MANUFACTURING reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

t CompanyData.com (BoldData), we provide trusted, verified company data sourced directly from official trade registers around the world. Our global list of 22 million manufacturing companies offers unmatched access to the industrial backbone of the global economy—spanning small-scale producers to large multinational manufacturers. This comprehensive dataset is built to support everything from outreach to automation.

Each record contains rich, up-to-date firmographics, company hierarchies, and contact information, including names of key decision-makers, direct emails, mobile phone numbers, turnover estimates, and employee ranges. Our data is collected and maintained with precision to ensure the highest standards of accuracy and compliance. Whether you’re navigating the automotive, food processing, electronics, or machinery sectors, we help you connect to the right manufacturing companies across global markets.

Our manufacturing dataset powers a broad range of use cases: from KYC verification and due diligence to sales prospecting, marketing campaigns, CRM data enrichment, and AI model training. Whether you need to verify business legitimacy, expand your market reach, or automate intelligence pipelines, our data gives you the edge.

We deliver our data in the format that fits your business best: tailored bulk files, access through our self-service platform, real-time API integration, or data enrichment services that complete and refine your existing databases. Backed by a global database of 380 million verified companies and deep domain expertise, CompanyData.com helps you reach manufacturers worldwide with confidence, compliance, and strategic precision.

Manufacturing Production in the United States increased 0.90 percent in August of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Manufacturing Production - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

US Toy Manufacturers by State

Number of Toy Manufacturers by State (2005-2016)

By Throwback Thursday [source]

About this dataset

The Week 39 - US Toy Manufacturers 2005-2016 dataset provides comprehensive information on the number of toy manufacturers operating in the United States from 2005 to 2016. It categorizes these manufacturers based on their geographical locations, specifically states within the country. The dataset contains three columns: State, which represents the state where each toy manufacturer is located; Year, which indicates the specific year when data was recorded; and Number of Manufacturers, which signifies the total count of toy manufacturers in a particular state and year.

The data source for this dataset is the U.S. Census Bureau's County Business Patterns report spanning over eleven years. This dataset aims to offer valuable insights into industry trends and fluctuations within the toy manufacturing sector across different states in America during this period.

Please note that actual dates are not mentioned in this description, as they were excluded as per your instruction

How to use the dataset

Introduction:

• Exploring the Dataset: a. The dataset consists of three columns: State, Year, and Number of Manufacturers. b. The State column represents different states in the United States where toy manufacturers are located. c. The Year column indicates when each data point was recorded. d. The Number of Manufacturers column provides information on how many toy manufacturers were present for each state and year.

• Understanding Categorical and Numeric Data: a. Categorical Data (State): This data is non-numerical and represents different states in the United States.

  • You can use this data to analyze regional distribution patterns or compare different states based on their number of toy manufacturers.

  b. Numeric Data (Year & Number of Manufacturers): These columns contain numerical values. - 'Year' data allows you to identify trends or patterns over time within each state's toy manufacturing industry. - 'Number of Manufacturers' data enables you to understand variations in manufacturer count for specific years across multiple states.

• Analysis Tips: a) Identifying State-Wise Variation: - Grouping by state, calculate average/minimum/maximum number of manufacturers over specified years, e.g., which state consistently had maximum/minimum numbers during this period?

  b) Analyzing Trends Over Time: - Grouping by year across all states or specific ones, calculate average/minimum/maximum number of manufacturers, e.g., what was the overall trend for toy manufacturers in certain states or across the country?

• Visualizing Insights: a) Bar/Column charts: Represent the number of manufacturers by state or year, allowing easy comparison between different categories.

• Combining with External Data: a) Explore correlations:

  • Combine this dataset with external factors like economic indicators to analyze how changes in different aspects might have influenced toy manufacturing trends.

• Additional Considerations:

  • Ensure you validate and cross-reference findings or hypotheses using other sources.
  • If incorporating results into your work, remember to cite the

Research Ideas

• Market Analysis: This dataset can be used to analyze the toy manufacturing industry in different states over time. By comparing the number of manufacturers in each state, trends and patterns can be identified. This information can be helpful for market analysis, identifying potential growth areas, and understanding market saturation.
• Economic Development: The dataset can be utilized by policymakers and government agencies to assess the economic development of different states. By looking at the number of toy manufacturers over time, policymakers can determine which states are attracting more business investment and potentially replicate those factors in other regions.
• Demographic Analysis: The dataset can also provide insights into demographic trends related to toy manufacturing. By analyzing changes in the number of manufacturers across different years and states, researchers could identify if there are any correlations with population growth or decline, employment rates, or other demographic factors

Acknowledgements

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

License

See the dataset descript...

Abstract

UNIDO maintains a variety of databases comprising statistics of overall industrial growth, detailed data on business structure and statistics on major indicators of industrial performance by country in the historical time series. Among which is the UNIDO Industrial Statistics Database at the 3 & 4-digit levels of ISIC Revision 4 (INDSTAT4-Rev.4).

INDSTAT4 contains highly disaggregated data on the manufacturing sector for the period 2005 onwards. Comparability of data over time and across the countries has been the main priority of developing and updating this database. INDSTAT4 offers a unique possibility of in-depth analysis of the structural transformation of economies over time. The database contains seven principle indicators of industrial statistics. The data are arranged at the 3- and 4-digit levels of the International Standard Industrial Classification of All Economic Activities (ISIC) Revision 4 pertaining to the manufacturing, which comprises more than 160 manufacturing sectors and sub-sectors. The time series can either be used to compare a certain branch or sector of countries or – if present in the data set – some sectors of one country.

For more information, please visit: http://www.unido.org/resources/statistics/statistical-databases.html

Analysis unit

Sectors

Kind of data

Aggregate data [agg]

Mode of data collection

Other [oth]

Manufacturing Production in China increased 5.70 percent in August of 2025 over the same month in the previous year. This dataset provides - China Manufacturing Production- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Industrial Production in the United States increased 0.10 percent in August of 2025 over the previous month. This dataset provides the latest reported value for - United States Industrial Production MoM - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Since China’s initiative of the Belt and Road Initiative, overseas industrial parks have become an important carrier for economic and trade cooperation and have become an important force for Chinese enterprises to go global.However, although there are many industrial parks invested by Chinese companies abroad, there is not yet a comprehensive statistical work that is crucial for national or corporate investors.The start-up time of some parks and the name of Chinese enterprises that are under construction are difficult to find, so comprehensive statistical work is relatively difficult.This paper collects data through the network crawling technology, the public number of the Belt and Road International Industrial Park, the official website of the major enterprises participating in the Belt and Road construction, and the database of the Ministry of Commerce.Under the most comprehensive collection possible, a detailed data set of the China Outland Campus Belt and Road Project from 1992 to 2018 was compiled.This data set summarizes the existing park names and determines the total number of parks currently built in China; statistics on the number of parks on each continent to understand the distribution of the park; then analyze the type of the park, and understand the distribution of resources in the area by type; finally,compare the time between the construction of the park and the time of the country where the park is located join the Asian Infrastructure Investment Bank(AIIB) to know the relationship between the AIIB and the park.

Time series data for the statistic Manufacturing, value added (current US$) and country Czechia. Indicator Definition:Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current U.S. dollars.The indicator "Manufacturing, value added (current US$)" stands at 69.13 Billion usd as of 12/31/2024, the highest value at least since 12/31/1994, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes an increase of 0.6311 percent compared to the value the year prior.The 1 year change in percent is 0.6311.The 3 year change in percent is 20.96.The 5 year change in percent is 21.67.The 10 year change in percent is 39.66.The Serie's long term average value is 37.25 Billion usd. It's latest available value, on 12/31/2024, is 85.60 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/1993, to it's latest available value, on 12/31/2024, is +706.36%.The Serie's change in percent from it's maximum value, on 12/31/2024, to it's latest available value, on 12/31/2024, is 0.0%.

Time series data for the statistic Manufacturing, value added (current US$) and country Georgia. Indicator Definition:Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current U.S. dollars.The indicator "Manufacturing, value added (current US$)" stands at 2.74 Billion usd as of 12/31/2024, the highest value at least since 12/31/1997, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes an increase of 6.67 percent compared to the value the year prior.The 1 year change in percent is 6.67.The 3 year change in percent is 46.73.The 5 year change in percent is 76.21.The 10 year change in percent is 65.77.The Serie's long term average value is 1.21 Billion usd. It's latest available value, on 12/31/2024, is 125.84 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/1999, to it's latest available value, on 12/31/2024, is +667.37%.The Serie's change in percent from it's maximum value, on 12/31/2024, to it's latest available value, on 12/31/2024, is 0.0%.

Time series data for the statistic Manufacturing, value added (current US$) and country United Kingdom. Indicator Definition:Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current U.S. dollars.The indicator "Manufacturing, value added (current US$)" stands at 291.80 Billion usd as of 12/31/2024, the highest value since 12/31/2008. Regarding the One-Year-Change of the series, the current value constitutes an increase of 4.53 percent compared to the value the year prior.The 1 year change in percent is 4.53.The 3 year change in percent is 7.36.The 5 year change in percent is 16.33.The 10 year change in percent is 1.17.The Serie's long term average value is 240.24 Billion usd. It's latest available value, on 12/31/2024, is 21.46 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/1993, to it's latest available value, on 12/31/2024, is +77.24%.The Serie's change in percent from it's maximum value, on 12/31/2007, to it's latest available value, on 12/31/2024, is -2.38%.

Time series data for the statistic Manufacturing, value added (current US$) and country Mali. Indicator Definition:Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current U.S. dollars.The indicator "Manufacturing, value added (current US$)" stands at 1.96 Billion usd as of 12/31/2024, the highest value at least since 12/31/1968, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes an increase of 10.34 percent compared to the value the year prior.The 1 year change in percent is 10.34.The 3 year change in percent is 9.24.The 5 year change in percent is 28.05.The 10 year change in percent is 15.30.The Serie's long term average value is 0.857 Billion usd. It's latest available value, on 12/31/2024, is 128.89 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/1967, to it's latest available value, on 12/31/2024, is +13,804.46%.The Serie's change in percent from it's maximum value, on 12/31/2024, to it's latest available value, on 12/31/2024, is 0.0%.

This dataset represents the entire Industrial PinPointer database of manufacturing companies. Only those locations primarily engaged in manufacturing (SIC Codes 2000-3999) or those that are headquarters of manufacturing companies are included. This dataset covers manufacturing locations in the State of Alabama. Homeland SecurityThis dataset includes the entire Industrial PinPointer database of manufacturing companies, which includes the 2009 D2 of 2 update. Only those locations primarily engaged in manufacturing (SIC Codes 2000-3999) or those that are headquarters of manufacturing companies are included. SIC codes are not provided for 125 companies in the US territories. Where an employee count is available, only locations employing fifteen (15) or more people are included. All text fields were set to upper case, leading and trailing spaces were trimmed from all text fields, and non-printable and diacritic characters were removed from all text fields per NGA's request.Metadata

Abstract

This survey was conducted in Hungary between February 2013 and August 2013 as part of the fifth round of the Business Environment and Enterprise Performance Survey (BEEPS V), a joint initiative of the World Bank Group and the European Bank for Reconstruction and Development. The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

Data from 310 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses.

The survey topics include firm characteristics, information about sales and suppliers, competition, infrastructure services, judiciary and law enforcement collaboration, security, government policies, laws and regulations, financing, overall business environment, bribery, capacity utilization, performance and investment activities, and workforce composition.

In 2011, the innovation module was added to the standard set of Enterprise Surveys questionnaires to examine in detail how introduction of new products and practices influence firms' performance and management.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is an establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or universe of the study, is the non-agricultural economy. It comprises: all manufacturing sectors according to the group classification of ISIC Revision 3.1: (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities-sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed in the way that follows: the universe was stratified into one manufacturing industry, and two service industries (retail, and other services).

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not common practice, apart from the construction and agriculture sectors which are not included in the survey.

Regional stratification was defined in 3 regions (city and the surrounding business area) throughout Hungary.

The database from Hungarian Central Statistical Office was used as the frame for the selection of a sample with the aim of obtaining interviews at 270 establishments with five or more employees.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 9.2% (102 out of 1,106 establishments).

In the dataset, the variables a2 (sampling region), a6a (sampling establishment's size), and a4a (sampling sector) contain the establishment's classification into the strata chosen for each country using information from the sample frame. Variable a4a is coded using ISIC Rev 3.1 codes for the chosen industries for stratification. These codes include most manufacturing industries (15 to 37), retail (52), and (45, 50, 51, 55, 60-64, 72) for other services.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different versions of the questionnaire were used. The basic questionnaire, the Core Module, includes all common questions asked to all establishments from all sectors. The second expanded variation, the Manufacturing Questionnaire, is built upon the Core Module and adds some specific questions relevant to manufacturing sectors. The third expanded variation, the Retail Questionnaire, is also built upon the Core Module and adds to the core specific questions.

The innovation module was added to the standard set of Enterprise Surveys questionnaires to examine how introduction of new products and practices influence firms' performance and management.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether, while the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect the refusal to respond as a different option from don’t know. b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

The number of realized interviews per contacted establishment was 0.26. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The number of rejections per contact was 0.28.

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...

Emissions by Country

Quantifying Sources and Emission Levels

By [source]

About this dataset

This dataset provides an in-depth look into the global CO2 emissions at the country-level, allowing for a better understanding of how much each country contributes to the global cumulative human impact on climate. It contains information on total emissions as well as from coal, oil, gas, cement production and flaring, and other sources. The data also provides a breakdown of per capita CO2 emission per country - showing which countries are leading in pollution levels and identifying potential areas where reduction efforts should be concentrated. This dataset is essential for anyone who wants to get informed about their own environmental footprint or conduct research on international development trends

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How to use the dataset

This dataset provides a country-level survey of global fossil CO2 emissions, including total emissions, emissions from coal, oil, gas, cement, flaring and other sources as well as per capita emissions.

For researchers looking to quantify global CO2 emission levels by country over time and understand the sources of these emissions this dataset can be a valuable resource.

The data is organized using the following columns: Country (the name of the country), ISO 3166-1 alpha-3 (the three letter code for the country), Year (the year of survey data), Total (the total amount of CO2 emitted by the country in that year), Coal (amount of CO2 emitted by coal in that year), Oil (amount emitted by oil) , Gas (amount emitted by gas) , Cement( amount emitted by cement) , Flaring(flaring emission levels ) and Other( other forms such as industrial processes ). In addition there is also one extra column Per Capita which provides an insight into how much personal carbon dioxide emission is present in each Country per individual .

To make use of these columns you can aggregate sum up Total column for a specific region or help define how much each source contributes to Total column such as how many percent it accounts for out of 100 or construct dashboard visualizations to explore what sources are responsible for higher level emission across different countries similar clusters or examine whether individual countries Focusing on Flaring — emissions associated with burning off natural gas while drilling—can improve overall Fossil Fuel Carbon Emission profiles better understanding of certain types nuclear power plants etc.

The main purpose behind this dataset was to facilitate government bodies private organizations universities NGO's research agencies alike applying analytical techniques tracking environment changes linked with influence cross regions providing resources needed analyze process monitor developing directed ways managing efficient ways get detailed comprehensive verified information

With insights gleaned from this dataset one can begin identify strategies efforts pollutant mitigation climate change combat etc while making decisions centered around sustainable developments with continent wide unified plans policy implementations keep an eye out evidences regional discrepancies being displayed improving quality life might certainly seem likely assure task easy quickly done “Global Fossil Carbon Dioxide Emissions:Country Level Survey 2002 2022 could exactly what us

Research Ideas

• Using the per capita emissions data, develop a reporting system to track countries' progress in meeting carbon emission targets and give policy recommendations for how countries can reach those targets more quickly.
• Analyze the correlation between different fossil fuel sources and CO2 emissions to understand how best to reduce CO2 emissions at a country-level.
• Create an interactive map showing global CO2 levels over time that allows users to visualize trends by country or region across all fossil fuel sources

Acknowledgements

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

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: GCB2022v27_MtCO2_flat.csv | Column name | Description ...

This dataset provides values for GDP FROM MANUFACTURING reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Key Table Information.Table Title.Manufacturing: Location of Manufacturing Establishments by Employment Size for the U.S., States, and Counties: 2022.Table ID.ECNLOCMFG2022.EC2231LOCMFG.Survey/Program.Economic Census.Year.2022.Dataset.ECN Sector Statistics Economic Census: Manufacturing: Location of Manufacturing Establishments by Employment Size for the U.S., States, and Counties.Source.U.S. Census Bureau, 2022 Economic Census, Sector Statistics.Release Date.2025-05-15.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.Employment size of establishmentsNumber of establishmentsFor more information about the survey, see Economic Census..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, and County 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 for U.S. and States; and at the 2- through 3-digit 2022 NAICS code levels for Counties. 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 Ec...