This report is organized into seven sections. Section A describes the survey, including information about the sample design, data collection procedures, and key aspects of data processing (e.g., development of analysis weights). Section B presents technical details on the statistical methods and measurement, such as suppression criteria for unreliable estimates, statistical testing procedures, and issues for selected substance use and mental health measures. Section C discusses special topics related to prescription psychotherapeutic drugs. A glossary that covers key definitions used in NSDUH reports and tables is included in Section D. Section E describes other sources of data on substance use and mental health issues, including data sources for populations outside the NSDUH target population. A list of references cited in the report (Section F) and a list of contributors to this report (Section G) also are provided.

Use this summary report to properly interpret 2019 NSDUH estimates of substance use and mental health issues. The report accompanies theannual detailed tablesand covers overall methodology, key definitions for measures and terms used in 2019 NSDUH reports and tables, and selected analyses of the measures and how they should be interpreted.The report is organized into five chapters:Introduction.Description of the survey, including information about the sample design, data collection procedures, and key aspects of data processing such as development of the analysis weights.Technical details on the statistical methods and measurement, such as suppression criteria for unreliable estimates, statistical testing procedures, issues around data accuracy, and measurement issues for selected substance use and mental health measures.Special topics related to prescription psychotherapeutic drugs.A comparison between NSDUH and other sources of data on substance use and mental health issues, including data sources for populations outside the NSDUH target population.An appendix covers key definitions used in NSDUH reports and tables.

Use this summary report to properly interpret 2020 NSDUH estimates of substance use and mental health issues. The report accompanies theannual detailed tablesand covers overall methodology, key definitions for measures and terms used in 2020 NSDUH reports and tables, and selected analyses of the measures and how they should be interpreted.The report is organized into six chapters:Introduction.Description of the survey, including information about the sample design, data collection procedures, and key aspects of data processing such as development of the analysis weights.Technical details on the statistical methods and measurement, such as suppression criteria for unreliable estimates, statistical testing procedures, issues around data accuracy, and measurement issues for selected substance use and mental health measures.Special topics related to prescription psychotherapeutic drugs.A comparison between NSDUH and other sources of data on substance use and mental health issues, including data sources for populations outside the NSDUH target population.A more in-depth view of special methodological issues for the 2020 NSDUH, including those related to methodological changes made because of the Coronavirus 2019 Pandemic.An appendix covers key definitions used in NSDUH reports and tables.

This page summarises how people understand their core values, how meaningful life feels, and how digital noise and AI shape decisions, focus and long-term direction.

Use this summary report to properly interpret 2021 NSDUH estimates of substance use and mental health issues. The report accompanies theannual detailed tablesand covers overall methodology, key definitions for measures and terms used in 2021 NSDUH reports and tables, and selected analyses of the measures and how they should be interpreted.The report is organized into six chapters:Introduction.Description of the survey, including information about the sample design, data collection procedures, and key aspects of data processing such as development of the analysis weights. The report also includes methodological changes and related issues in the 2021 NSDUH due to COVID-19.Technical details on the statistical methods and measurement, such as suppression criteria for unreliable estimates, statistical testing procedures, issues around selected substance use and mental health measures, and the impact of methodological changes on response rates.Special topics related to prescription psychotherapeutic drugs.A comparison between NSDUH and other sources of data on substance use and mental health issues, including data sources for populations outside the NSDUH target population.A more in-depth view of special methodological issues for the 2021 NSDUH, including the results of special analyses that led SAMHSA to not compare estimates from 2021 to estimates from previous years.An appendix covers key definitions used in NSDUH reports and tables.

This report summarizes the 2018 NSDUH methods and other supporting information relevant to estimates of substance use and mental health issues, and organized into five chapters. Chapter 1 is an introduction to the report. Chapter 2 describes the survey, including information about the sample design; data collection procedures; and key aspects of data processing, such as development of analysis weights. Chapter 3 presents technical details on the statistical methods and measurement, such as suppression criteria for unreliable estimates, statistical testing procedures, and issues for selected substance use and mental health measures. Chapter 4 covers special topics related to prescription psychotherapeutic drugs. Chapter 5 describes other sources of data on substance use and mental health issues, including data sources for populations outside the NSDUH target population. Appendix A is a glossary that covers key definitions for use as a resource with the 2018 NSDUH reports and detailed tables. Appendix B provides a list of contributors to the report.

Key Table Information.Table Title.Information: Summary Statistics for the U.S., States, and Selected Geographies: 2022.Table ID.ECNBASIC2022.EC2251BASIC.Survey/Program.Economic Census.Year.2022.Dataset.ECN Core Statistics Summary Statistics for the U.S., States, and Selected Geographies: 2022.Source.U.S. Census Bureau, 2022 Economic Census, Core Statistics.Release Date.2024-12-05.Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Methodology.Data Items and Other Identifying Records.Number of firmsNumber of establishmentsSales, value of shipments, or revenue ($1,000)Annual payroll ($1,000)First-quarter payroll ($1,000)Number of employeesRange indicating imputed percentage of total sales, value of shipments, or revenueRange indicating imputed percentage of total annual payrollRange indicating imputed percentage of total employeesDefinitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the economic census are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization. For some industries, the reporting units are instead groups of all establishments in the same industry belonging to the same firm..Geography Coverage.The data are shown for the U.S., State, Combined Statistical Area, Metropolitan and Micropolitan Statistical Area, Metropolitan Division, Consolidated City, County (and equivalent), and Economic Place (and equivalent; incorporated and unincorporated) levels that vary by industry. For information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 2- through 6-digit 2022 NAICS code levels and selected 7-digit 2022 NAICS-based code levels. For information about NAICS, see Economic Census Code Lists..Sampling.The 2022 Economic Census sample includes all active operating establishments of multi-establishment firms and approximately 1.7 million single-establishment firms, stratified by industry and state. Establishments selected to the sample receive a questionnaire. For all data on this table, establishments not selected into the sample are represented with administrative data. For more information about the sample design, see 2022 Economic Census Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY23-099).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business’ data or identity.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing firms or three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the 2022 Economic Census Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, NAPCS codes, and more, see Economic Census Technical Documentation..Weights.No weighting applied as establishments not sampled are represented with administrative data..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.X - Not applicableA - Relative standard error of 100% or morer - Reviseds - Relative standard error exceeds 40%For a complete list of symbols, see Economic Census Data Dictionary..Data-Specific Notes.Data users who create their own estimates us...

Summary

This dataset contains biographical information derived from articles on English Wikipedia as it stood in early June 2024. It was created as part of the Structured Contents initiative at Wikimedia Enterprise and is intended for evaluation and research use.

The beta sample dataset is a subset of the Structured Contents Snapshot focusing on people with infoboxes in EN wikipedia; outputted as json files (compressed in tar.gz).

We warmly welcome any feedback you have. Please share your thoughts, suggestions, and any issues you encounter on the discussion page for this dataset here on Kaggle.

Data Structure

• File name: wme_people_infobox.tar.gz
• Size of compressed file: 4.12 GB
• Size of uncompressed file: 21.28 GB

Noteworthy Included Fields: - name - title of the article. - identifier - ID of the article. - image - main image representing the article's subject. - description - one-sentence description of the article for quick reference. - abstract - lead section, summarizing what the article is about. - infoboxes - parsed information from the side panel (infobox) on the Wikipedia article. - sections - parsed sections of the article, including links. Note: excludes other media/images, lists, tables and references or similar non-prose sections.

The Wikimedia Enterprise Data Dictionary explains all of the fields in this dataset.

Stats

Infoboxes - Compressed: 2GB - Uncompressed: 11GB

Infoboxes + sections + short description - Size of compressed file: 4.12 GB - Size of uncompressed file: 21.28 GB

Article analysis and filtering breakdown: - total # of articles analyzed: 6,940,949 - # people found with QID: 1,778,226 - # people found with Category: 158,996 - people found with Biography Project: 76,150 - Total # of people articles found: 2,013,372 - Total # people articles with infoboxes: 1,559,985 End stats - Total number of people articles in this dataset: 1,559,985 - that have a short description: 1,416,701 - that have an infobox: 1,559,985 - that have article sections: 1,559,921

This dataset includes 235,146 people articles that exist on Wikipedia but aren't yet tagged on Wikidata as instance of:human.

Maintenance and Support

This dataset was originally extracted from the Wikimedia Enterprise APIs on June 5, 2024. The information in this dataset may therefore be out of date. This dataset isn't being actively updated or maintained, and has been shared for community use and feedback. If you'd like to retrieve up-to-date Wikipedia articles or data from other Wikiprojects, get started with Wikimedia Enterprise's APIs

Initial Data Collection and Normalization

The dataset is built from the Wikimedia Enterprise HTML “snapshots”: https://enterprise.wikimedia.com/docs/snapshot/ and focuses on the Wikipedia article namespace (namespace 0 (main)).

Who are the source language producers?

Wikipedia is a human generated corpus of free knowledge, written, edited, and curated by a global community of editors since 2001. It is the largest and most accessed educational resource in history, accessed over 20 billion times by half a billion people each month. Wikipedia represents almost 25 years of work by its community; the creation, curation, and maintenance of millions of articles on distinct topics. This dataset includes the biographical contents of English Wikipedia language editions: English https://en.wikipedia.org/, written by the community.

Attribution

Terms and conditions

Wikimedia Enterprise provides this dataset under the assumption that downstream users will adhere to the relevant free culture licenses when the data is reused. In situations where attribution is required, reusers should identify the Wikimedia project from which the content was retrieved as the source of the content. Any attribution should adhere to Wikimedia’s trademark policy (available at https://foundation.wikimedia.org/wiki/Trademark_policy) and visual identity guidelines (ava...

Use this summary report to properly interpret 2022 NSDUH estimates related to substance use, mental health, and treatment. The report accompanies theannual detailed tablesand covers overall methodology, key definitions for measures and terms used in 2022 NSDUH reports and tables, and selected analyses of the measures and how they should be interpreted.The report is organized into five chapters:Introduction.Description of the survey, including information about the sample design, data collection procedures and questionnaire changes, and key aspects of data processing such as development of the analysis weights.Technical details on the statistical methods and measurement, such as suppression criteria for unreliable estimates, statistical testing procedures, revised estimates for 2021 to account for data collection mode, and issues around selected substance use and mental health measures.Special topics related to prescription psychotherapeutic drugs.Description of other sources of data on substance use and mental health issues in the United States, including data sources for populations outside the NSDUH target population.An appendix covers key definitions used in NSDUH reports and tables.

Definition of the summary measures computed using IMU data from each phase of the mood induction task.

This report summarizes methods and other supporting information that are relevant to estimates of substance use and mental health issues from the 2014 National Survey on Drug Use and Health (NSDUH), an annual survey of the civilian, noninstitutionalized population of the United States aged 12 years old or older. This report is organized into six sections. Section A describes the survey, including information about the sample design, data collection procedures, and key aspects of data processing (e.g., development of analysis weights). Section B presents technical details on the statistical methods and measurement, such as suppression criteria for unreliable estimates, statistical testing procedures, and issues for selected substance use and mental health measures. A glossary that covers key definitions used in NSDUH reports and tables is included in Section C. Section D describes other sources of data on substance use and mental health issues, including data sources for populations outside the NSDUH target population. A list of references cited in the report (Section E) and contributors to this report (Section F) also are provided.

Definition and summary statistics of the variables.

The Colorado COVID-19 Data Summary contains data on cases, hospitalizations, and deaths since the start of the COVID-19 pandemic to the end of 2024.year_and_month: The year and month of onset of disease covid_case_total: COVID-19 probable and confirmed cases reported to the Colorado Department of Public Health and Environment (CDPHE) as defined by the Council of State and Territorial Epidemiologists (CSTE) case definitions. All cases are categorized by the month and year of onset.covid_case_total: COVID-19 probable and confirmed cases reported to the Colorado Department of Public Health and Environment (CDPHE) as defined by the Council of State and Territorial Epidemiologists (CSTE) case definitions. All cases are categorized by the month and year of onset.covid_hospital_total: The total number of people hospitalized in Colorado with COVID-19 infections. Multiple hospitalizations for the same instance of illness are not included in the total counts. For example, if an individual were hospitalized on July 1st of 2020, discharged on July 3rd and readmitted on July 7th, only the initial hospitalization would be counted. This metric is meant to be a calculation of severity of disease, not hospital capacity. All hospitalizations are categorized by the month and year of admission.death_due_covid_total: Deaths due to COVID-19 are deaths where COVID-19 is an underlying cause of death or named as a significant contributing condition on the death certificate. This data rests on the judgment and assessment of the person completing the death certificate (usually the provider if the patient is in the hospital or a county coroner). The information is then sent to the National Center for Health Statistics (NCHS) at the Centers for Disease Control and Prevention, which then verifies the death. All deaths are categorized by the month and year of death and the analysis is limited to individuals who were Colorado residents at the time of death.publish_date: Date that this dataset was published to the CDPHE Open Data website.For more information, data definitions, and context, please visit Colorado’s Viral Respiratory Diseases data website (https://cdphe.colorado.gov/viral-respiratory-diseases-report).

IPPS DRG Provider Summary

Average Discharges, Charges, and Medicare Payments

By Health [source]

About this dataset

This dataset is a valuable resource for gaining insight into Inpatient Prospective Payment System (IPPS) utilization, average charges and average Medicare payments across the top 100 Diagnosis-Related Groups (DRG). With column categories such as DRG Definition, Hospital Referral Region Description, Total Discharges, Average Covered Charges, Average Medicare Payments and Average Medicare Payments 2 this dataset enables researchers to discover and assess healthcare trends in areas such as provider payment comparsons by geographic location or compare service cost across hospital. Visualize the data using various methods to uncover unique information and drive further hospital research

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset provides a provider level summary of Inpatient Prospective Payment System (IPPS) discharges, average charges and average Medicare payments for the Top 100 Diagnosis-Related Groups (DRG). This data can be used to analyze cost and utilization trends across hospital DRGs.

To make the most use of this dataset, here are some steps to consider:

• Understand what each column means in the table: Each column provides different information from the DRG Definition to Hospital Referral Region Description and Average Medicare Payments.
• Analyze the data by looking for patterns amongst the relevant columns: Compare different aspects such as total discharges or average Medicare payments by hospital referral region or DRG Definition. This can help identify any potential trends amongst different categories within your analysis.
• Generate visualizations: Create charts, graphs, or maps that display your data in an easy-to-understand format using tools such as Microsoft Excel or Tableau. Such visuals may reveal more insights into patterns within your data than simply reading numerical values on a spreadsheet could provide alone.

Research Ideas

• Identifying potential areas of cost savings by drilling down to particular DRGs and hospital regions with the highest average covered charges compared to average Medicare payments.
• Establishing benchmarks for typical charges and payments across different DRGs and hospital regions to help providers set market-appropriate prices.
• Analyzing trends in total discharges, charges and Medicare payments over time, allowing healthcare organizations to measure their performance against regional peers

Acknowledgements

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

License

License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - 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. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: 97k6-zzx3.csv | Column name | Description | |:-----------------------------------------|:------------------------------------------------------| | drg_definition | Diagnosis-Related Group (DRG) definition. (String) | | average_medicare_payments | Average Medicare payments for each DRG. (Numeric) | | hospital_referral_region_description | Description of the hospital referral region. (String) | | total_discharges | Total number of discharges for each DRG. (Numeric) | | average_covered_charges | Average covered charges for each DRG. (Numeric) | | average_medicare_payments_2 | Average Medicare payments for each DRG. (Numeric) |

**File: Inpatient_Prospective_Payment_System_IPPS_Provider_Summary_for_the_Top_100_Diagnosis-Related_Groups_DRG...

WA-APCD - Washington All-Payer Claims Database

The WA-APCD is the state’s most complete source of health care eligibility, medical claims, pharmacy claims, and dental claims insurance data. It contains claims from more than 50 data suppliers, spanning commercial, Medicaid, and Medicare managed care. The WA-APCD has historical claims data for five years (2013-2017), with ongoing refreshes scheduled quarterly. Workers' compensation data from the Washington Department of Labor & Industries will be added in fall 2018.

Download the attachment for the data dictionary and more information about WA-APCD and the data.

Studies of economic mobility summarize the relationship between parent and offspring incomes. At each level of parent income there is an entire distribution of possible incomes for offspring. Mitnik and Grusky (2020, hereafter MG) highlight that the conventional intergenerational elasticity targets the geometric mean and propose a parametric strategy for estimating the arithmetic mean. We decompose each proposal into two choices an analyst must make: (1) the summary statistic for the conditional distribution and (2) whether to assume or learn a functional form. These choices lead us to a different strategy---visualizing several quantiles of the offspring income distribution as smooth, nonparametric functions of parent income. Our proposal solves the problems MG highlight with geometric means, avoids the sensitivity of arithmetic means to top incomes, and provides more information about the conditional distribution than any single-number summary can provide. Our proposal has broader implications for regression analyses, which often collapse a distribution to its mean although this summary can be sensitive to skew.

This dataset comes from the Community Survey questions relating to the Community Health & Well-Being performance measure: "With “10” representing the best possible life for you and “0” representing the worst, how would you say you personally feel you stand at this time?" and "With “10” representing the best possible life for you and “0” representing the worst, how do you think you will stand about five years from now?" – the results of both scores are then used to assess a Cantril Scale which is a way of assessing general life satisfaction. As per the Cantril Self-Anchoring Striving Scale, the three categories of identification are as follows: Thriving – Respondents rate their current life as a 7 or higher AND their future life as an 8 or higher. Suffering – Respondents rate their current life negatively (0 to 4) AND their future life negatively (0 to 4). Struggling – Respondents who do not meet the criteria for Thriving or Suffering. The survey is mailed to a random sample of households in the City of Tempe and has a 95% confidence level. Note on Methodology Update: In 2025, the Cantril classification method was revised to align with Gallup’s official Life Evaluation Index methodology. This change affects only a small number of respondents whose answers did not fit cleanly into the previous custom definition of “Struggling,” which classified respondents who rated their current life moderately (5 or 6) or their future life moderately or negatively (0 to 7). Under the updated approach, respondents who previously fell outside that definition are now appropriately included in the Struggling category. The overall distribution of Thriving, Struggling, and Suffering changed only minimally, and the updated methodology has been applied consistently to all prior years.This page provides data for the Community Health and Well-Being performance measure.The performance measure dashboard is available at 3.34 Community Health and Well-Being.Data Dictionary Additional InformationSource: Community Attitude Survey (Vendor: ETC Institute)Contact: Amber AsburryContact email: amber_asburry@tempe.govPreparation Method: Survey results from two questions are calculated to create a Cantril Scale value that falls into the categories of Thriving, Struggling, and Suffering.Publish Frequency: AnnuallyPublish Method: Manual

This dataset comes from the Annual Community Survey question related to satisfaction with the quality of the city’s online services. Respondents are asked to provide their level of satisfaction related to “Tempe's online services (registration, payment, etc.)” on a scale of 5 to 1, where 5 means "Very Satisfied" and 1 means "Very Dissatisfied" (without "don't know" as an option).The survey is mailed to a random sample of households in the City of Tempe and has a 95% confidence level.This page provides data for the Online Service Satisfaction performance measure. The performance measure dashboard is available at 2.05 Online Services Satisfaction Rate. Additional Information Source: Community Attitude Survey ( Vendor: ETC Institute)Contact: Wydale HolmesContact E-Mail: Wydale_Holmes@tempe.govData Source Type: Excel and PDFPreparation Method: Extracted from Annual Community Survey results  Publish Frequency: Annual  Publish Method: Manual  Data Dictionary

A monthly model of groundwater-transported nitrogen loads was developed for 12-digit hydrologic unit code (HUC12) watersheds on the north shore of Long Island Sound in coastal Connecticut and adjacent areas of New York and Rhode Island. As part of the analysis, potential management actions that upgraded septic systems or reduced fertilizer application to areas of turf-grass were also simulated. This compilation includes a zipped file (Tables.zip) of aggregated model outputs and datasets used in the model development. The zipped file contains a file dictionary (file_dictionary.csv) that includes the file name, title, and caption for each table and a data dictionary (data_dictionary.csv) that includes the variable name, data type, units, reasonable values, and a description for each column in the tables. This compilation also includes a zipped file of supplemental figures (Figure.zip) that were not included in the main report. The zipped file contains a file dictionary (file_dictio ...

Biennial Business Survey data summary for Quality of Business Services survey results. The Business Survey question that relates to this dataset is: “Quality of services provided by City of Tempe.” Respondents are asked to rate their satisfaction level using a scale of 1 to 5, where 1 means "Very Dissatisfied" and 5 means "Very Satisfied".This page provides data for the Quality of Business Services performance measure. The performance measure dashboard is available at 5.01 Quality of Business Services.Additional InformationSource: Business Survey (Vendor: ETC Institute) Contact: Wydale HolmesContact E-Mail: wydale_holmes@tempe.govData Source Type: .pdf, ExcelPreparation Method: The City contracts with a vendor to conduct the survey, analyze the data, and prepare for publication.Publish Frequency: Every other yearPublish Method: Manual, .pdfData Dictionary