53 datasets found
  1. HR Dataset.csv

    • kaggle.com
    Updated Mar 8, 2024
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    Fahad Rehman (2024). HR Dataset.csv [Dataset]. https://www.kaggle.com/datasets/fahadrehman07/hr-comma-sep-csv
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 8, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Fahad Rehman
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    🟡Please Upvote my dataset If you like It.✨

    This dataset contains valuable employee information over time that can be analyzed to help optimize key HR functions. Some potential use cases include:

    Attrition analysis: Identify factors correlated with attrition like department, role, salary, etc. Segment high-risk employees. Predict future attrition.

    Performance management: Analyze the relationship between metrics like ratings, and salary increments. recommend performance improvement programs.

    Workforce planning: Forecast staffing needs based on historical hiring/turnover trends. Determine optimal recruitment strategies.

    Compensation analysis: Benchmark salaries vs performance, and experience. Identify pay inequities. Inform compensation policies.

    Diversity monitoring: Assess diversity metrics like gender ratio over roles, and departments. Identify underrepresented groups.

    Succession planning: Identify high-potential candidates and critical roles. Predict internal promotions/replacements in advance.

    Given its longitudinal employee data and multiple variables, this dataset provides rich opportunities for exploration, predictive modeling, and actionable insights. With a large sample size, it can uncover subtle patterns. Cleaning, joining with other contextual data sources can yield even deeper insights. This makes it a valuable starting point for many organizational studies and evidence-based decision-making.

    .............................................................................................................................................................................................................................................

    This dataset contains information about different attributes of employees from a company. It includes 1000 employee records and 12 feature columns.

    The columns are:

    satisfaction_level: Employee satisfaction score (1-5 scale) last_evaluation: Score on last evaluation (1-5 scale) number_project: Number of projects employee worked on average_monthly_hours: Average hours worked in a month time_spend_company: Number of years spent with the company work_accident: If an employee had a workplace accident (yes/no) left: If an employee has left the company (yes/no) promotion_last_5years: Number of promotions in last 5 years Department: Department of the employee Salary: Annual salary of employee satisfaction_level: Employee satisfaction level (1-5 scale) last_evaluation: Score on last evaluation (1-5 scale)

  2. Employee Attrition for Healthcare

    • kaggle.com
    Updated Feb 15, 2023
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    JohnM (2023). Employee Attrition for Healthcare [Dataset]. https://www.kaggle.com/datasets/jpmiller/employee-attrition-for-healthcare
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 15, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    JohnM
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Attrition of nurses in the US Healthcare system is at an all-time high. It is a major area of focus, especially for hospitals.

    This dataset contains employee and company data useful for supervised ML, unsupervised ML, and analytics. Attrition - whether an employee left or not - is included and can be used as the target variable.

    The data is synthetic and based on the IBM Watson dataset for attrition. Employee roles and departments were changed to reflect the healthcare domain. Also, known outcomes for some employees were changed to help increase the performance of ML models.

    Here's an app I use as a demo based on this dataset and an ML classification model.

    https://i.imgur.com/Aft3t1E.png"> https://i.imgur.com/QNRX2LA.png">

  3. m

    Chapter 12: Data Preparation for Fraud Analytics: Project: Human Recourses...

    • data.mendeley.com
    Updated Nov 1, 2023
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    ABDELRAHIM AQQAD (2023). Chapter 12: Data Preparation for Fraud Analytics: Project: Human Recourses Analysis - Human_Resources.csv [Dataset]. http://doi.org/10.17632/smypp8574h.1
    Explore at:
    Dataset updated
    Nov 1, 2023
    Authors
    ABDELRAHIM AQQAD
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Project: Human Recourses Analysis - Human_Resources.csv

    Description:

    The dataset, named "Human_Resources.csv", is a comprehensive collection of employee records from a fictional company. Each row represents an individual employee, and the columns represent various features associated with that employee.

    The dataset is rich, highlighting features like 'Age', 'MonthlyIncome', 'Attrition', 'BusinessTravel', 'DailyRate', 'Department', 'EducationField', 'JobSatisfaction', and many more. The main focus is the 'Attrition' variable, which indicates whether an employee left the company or not.

    Employee data were sourced from various departments, encompassing a diverse array of job roles and levels. Each employee's record provides an in-depth look into their background, job specifics, and satisfaction levels.

    The dataset further includes specific indicators and parameters that were considered during employee performance assessments, offering a granular look into the complexities of each employee's experience.

    For privacy reasons, certain personal details and specific identifiers have been anonymized or fictionalized. Instead of names or direct identifiers, each entry is associated with a unique 'EmployeeNumber', ensuring data privacy while retaining data integrity.

    The employee records were subjected to rigorous examination, encompassing both manual assessments and automated checks. The end result of this examination, specifically whether an employee left the company or not, is clearly indicated for each record.

  4. f

    Human Resources.csv

    • figshare.com
    csv
    Updated Apr 11, 2025
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    anurag pardiash (2025). Human Resources.csv [Dataset]. http://doi.org/10.6084/m9.figshare.28780886.v1
    Explore at:
    csvAvailable download formats
    Dataset updated
    Apr 11, 2025
    Dataset provided by
    figshare
    Authors
    anurag pardiash
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset titled Human Resources.csv contains anonymized employee data collected for internal HR analysis and research purposes. It includes fields such as employee ID, department, gender, age, job role, and employment status. The data can be used for workforce trend analysis, HR benchmarking, diversity studies, and training models in human resource analytics.The file is provided in CSV format (3.05 MB) and adheres to general data privacy standards, with no personally identifiable information (PII).Last updated: April 11, 2025. Uploaded by Anurag Pardiash.

  5. Australian Employee Salary/Wages DATAbase by detailed occupation, location...

    • figshare.com
    txt
    Updated May 31, 2023
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    Richard Ferrers; Australian Taxation Office (2023). Australian Employee Salary/Wages DATAbase by detailed occupation, location and year (2002-14); (plus Sole Traders) [Dataset]. http://doi.org/10.6084/m9.figshare.4522895.v5
    Explore at:
    txtAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    figshare
    Authors
    Richard Ferrers; Australian Taxation Office
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The ATO (Australian Tax Office) made a dataset openly available (see links) showing all the Australian Salary and Wages (2002, 2006, 2010, 2014) by detailed occupation (around 1,000) and over 100 SA4 regions. Sole Trader sales and earnings are also provided. This open data (csv) is now packaged into a database (*.sql) with 45 sample SQL queries (backupSQL[date]_public.txt).See more description at related Figshare #datavis record. Versions:V5: Following #datascience course, I have made main data (individual salary and wages) available as csv and Jupyter Notebook. Checksum matches #dataTotals. In 209,xxx rows.Also provided Jobs, and SA4(Locations) description files as csv. More details at: Where are jobs growing/shrinking? Figshare DOI: 4056282 (linked below). Noted 1% discrepancy ($6B) in 2010 wages total - to follow up.#dataTotals - Salary and WagesYearWorkers (M)Earnings ($B) 20028.528520069.4372201010.2481201410.3584#dataTotal - Sole TradersYearWorkers (M)Sales ($B)Earnings ($B)20020.9611320061.0881920101.11122620141.19630#links See ATO request for data at ideascale link below.See original csv open data set (CC-BY) at data.gov.au link below.This database was used to create maps of change in regional employment - see Figshare link below (m9.figshare.4056282).#packageThis file package contains a database (analysing the open data) in SQL package and sample SQL text, interrogating the DB. DB name: test. There are 20 queries relating to Salary and Wages.#analysisThe database was analysed and outputs provided on Nectar(.org.au) resources at: http://118.138.240.130.(offline)This is only resourced for max 1 year, from July 2016, so will expire in June 2017. Hence the filing here. The sample home page is provided here (and pdf), but not all the supporting files, which may be packaged and added later. Until then all files are available at the Nectar URL. Nectar URL now offline - server files attached as package (html_backup[date].zip), including php scripts, html, csv, jpegs.#installIMPORT: DB SQL dump e.g. test_2016-12-20.sql (14.8Mb)1.Started MAMP on OSX.1.1 Go to PhpMyAdmin2. New Database: 3. Import: Choose file: test_2016-12-20.sql -> Go (about 15-20 seconds on MacBookPro 16Gb, 2.3 Ghz i5)4. four tables appeared: jobTitles 3,208 rows | salaryWages 209,697 rows | soleTrader 97,209 rows | stateNames 9 rowsplus views e.g. deltahair, Industrycodes, states5. Run test query under **#; Sum of Salary by SA4 e.g. 101 $4.7B, 102 $6.9B#sampleSQLselect sa4,(select sum(count) from salaryWageswhere year = '2014' and sa4 = sw.sa4) as thisYr14,(select sum(count) from salaryWageswhere year = '2010' and sa4 = sw.sa4) as thisYr10,(select sum(count) from salaryWageswhere year = '2006' and sa4 = sw.sa4) as thisYr06,(select sum(count) from salaryWageswhere year = '2002' and sa4 = sw.sa4) as thisYr02from salaryWages swgroup by sa4order by sa4

  6. D

    San Francisco Employee Compensation, Fiscal years 2013 and 2017

    • data.sfgov.org
    application/rdfxml +5
    Updated Jul 7, 2025
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    SF Controller's Office (2025). San Francisco Employee Compensation, Fiscal years 2013 and 2017 [Dataset]. https://data.sfgov.org/City-Management-and-Ethics/San-Francisco-Employee-Compensation-Fiscal-years-2/35vr-y3kw
    Explore at:
    application/rssxml, application/rdfxml, xml, csv, tsv, jsonAvailable download formats
    Dataset updated
    Jul 7, 2025
    Authors
    SF Controller's Office
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Area covered
    San Francisco
    Description

    The San Francisco Controller's Office maintains a database of the salary and benefits paid to City employees since fiscal year 2013. This data is summarized and presented on the Employee Compensation report hosted at http://openbook.sfgov.org, and is also available in this dataset in CSV format. New data is added on a bi-annual basis when available for each fiscal and calendar year.

  7. Employees Data

    • kaggle.com
    Updated Feb 7, 2025
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    JAYESH CHAUHAN (2025). Employees Data [Dataset]. https://www.kaggle.com/datasets/jayeshchauhan051/employees-data/suggestions
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 7, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    JAYESH CHAUHAN
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    Dataset

    This dataset was created by JAYESH CHAUHAN

    Released under ODC Public Domain Dedication and Licence (PDDL)

    Contents

  8. 2012 APS employee census

    • data.gov.au
    csv, pdf, sav
    Updated Aug 9, 2023
    + more versions
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    Australian Public Service Commission (2023). 2012 APS employee census [Dataset]. https://data.gov.au/data/dataset/aps_employee_census_2012
    Explore at:
    pdf(966701), sav(32273115), csv(223436049)Available download formats
    Dataset updated
    Aug 9, 2023
    Dataset authored and provided by
    Australian Public Service Commissionhttp://www.apsc.gov.au/
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    The 2012 APS employee census was administered to all available APS employees. This census approach provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The census' content is designed to establish the views of APS employees on workplace issues such as leadership, learning and development and job satisfaction. The census ran from 8 May to 6 June 2012. Overall, 87,214 APS employees responded to the employee census, a response rate of 55%.

    Please be aware that the very large number of respondents to the employee census means these files are over 200 mb in size. Downloading and opening these files may take some time.

    TECHNICAL NOTES

    Three files are available for download.

    • 2012 APS employee census - Questionnaire: This contains the 2012 APS employee census questionnaire.
    • 2012 APS employee census - 5 point dataset.csv: This file contains individual responses to the 2012 APS employee census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document.
    • 2012 APS employee census - 5 point dataset.sav: This file contains individual responses to the 2012 APS employee census for use with the SPSS software package.

    To protect the privacy and confidentiality of respondents to the 2012 APS employee census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

    Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author.

    A recommended short citation is: 2012 APS employee census data, Australian Public Service Commission.

    Any queries can be directed to research@apsc.gov.au.

  9. 2020 APS Employee Census

    • data.gov.au
    .csv, .pdf, .sav
    Updated Mar 30, 2021
    + more versions
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    Australian Public Service Commission (2021). 2020 APS Employee Census [Dataset]. https://data.gov.au/data/dataset/2020-aps-employee-census
    Explore at:
    .csv(164692755), .pdf(375669), .sav(23514770)Available download formats
    Dataset updated
    Mar 30, 2021
    Dataset authored and provided by
    Australian Public Service Commissionhttp://www.apsc.gov.au/
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    The 2020 APS Employee Census was administered to all available Australian Public Service (APS) employees, running from 12 October to 13 November 2020. This was delayed from the usual May to June timeframe due to the impact of COVID-19.

    The Employee Census provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The Census' content is designed to establish the views of APS employees on workplace issues such as leadership, learning and development, and job satisfaction.

    Overall, 108,085 APS employees responded to the Employee Census in 2020, a response rate of 78%.

    Please be aware that the very large number of respondents to the employee census means these files are over 200MB in size. Downloading and opening these files may take some time.

    TECHNICAL NOTES

    Three files are available for download.

    • 2020 APS Employee Census - Questionnaire: This contains the 2020 APS Employee Census questionnaire.

    • 2020 APS Employee Census - 5 point dataset.csv: This file contains individual responses to the 2020 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document.

    • 2020 APS Employee Census - 5 point dataset.sav: This file contains individual responses to the 2020 APS Employee Census for use with the SPSS software package.

    To protect the privacy and confidentiality of respondents to the 2020 APS Employee Census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

    Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author. A recommended short citation is: 2020 APS Employee Census data, Australian Public Service Commission.

    Any queries can be directed to research@apsc.gov.au.

  10. D

    Employee Compensation 5 yr

    • data.sfgov.org
    application/rdfxml +5
    Updated Jul 7, 2025
    + more versions
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    SF Controller's Office (2025). Employee Compensation 5 yr [Dataset]. https://data.sfgov.org/City-Management-and-Ethics/Employee-Compensation-5-yr/uzny-i7ak
    Explore at:
    csv, xml, application/rdfxml, tsv, application/rssxml, jsonAvailable download formats
    Dataset updated
    Jul 7, 2025
    Authors
    SF Controller's Office
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    A. SUMMARY The San Francisco Controller's Office maintains a database of the salary and benefits paid to City employees since fiscal year 2013.

    B. HOW THE DATASET IS CREATED This data is summarized and presented on the Employee Compensation report hosted at http://openbook.sfgov.org, and is also available in this dataset in CSV format.

    C. UPDATE PROCESS New data is added on a bi-annual basis when available for each fiscal and calendar year.

    D. HOW TO USE THIS DATASET Before using please first review the following two resources: Data Dictionary - Can be found in 'About this dataset' section after click 'Show More' Employee Compensation FAQ - https://support.datasf.org/help/employee-compensation-faq

  11. 2021 APS Employee Census

    • data.gov.au
    csv, pdf, spss
    Updated Aug 9, 2023
    + more versions
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    Australian Public Service Commission (2023). 2021 APS Employee Census [Dataset]. https://data.gov.au/data/dataset/2021-aps-employee-census
    Explore at:
    spss(23502938), csv(175179392), pdf(554582)Available download formats
    Dataset updated
    Aug 9, 2023
    Dataset authored and provided by
    Australian Public Service Commissionhttp://www.apsc.gov.au/
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    The 2021 APS Employee Census was administered to all available Australian Public Service (APS) employees, running from 10 May to 11 June 2021.

    The Employee Census provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The Census' content is designed to establish the views of APS employees on workplace issues such as leadership, learning and development, and job satisfaction.

    Overall, 109,537 APS employees responded to the Employee Census in 2021, a response rate of 77%.

    Please be aware that the very large number of respondents to the employee census means these files are over 200MB in size. Downloading and opening these files may take some time.

    TECHNICAL NOTES

    Three files are available for download.

    • 2021 APS Employee Census - Questionnaire: This contains the 2021 APS Employee Census questionnaire.
    • 2021 APS Employee Census - 5 point dataset.csv: This file contains individual responses to the 2021 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document.
    • 2021 APS Employee Census - 5 point dataset.sav: This file contains individual responses to the 2021 APS Employee Census for use with the SPSS software package.

    To protect the privacy and confidentiality of respondents to the 2021 APS Employee Census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

    Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author.

    A recommended short citation is: 2021 APS Employee Census data, Australian Public Service Commission.

    Any queries can be directed to research@apsc.gov.au.

  12. d

    Job Postings Dataset for Labour Market Research and Insights

    • datarade.ai
    Updated Sep 20, 2023
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    Oxylabs (2023). Job Postings Dataset for Labour Market Research and Insights [Dataset]. https://datarade.ai/data-products/job-postings-dataset-for-labour-market-research-and-insights-oxylabs
    Explore at:
    .json, .xml, .csv, .xlsAvailable download formats
    Dataset updated
    Sep 20, 2023
    Dataset authored and provided by
    Oxylabs
    Area covered
    British Indian Ocean Territory, Luxembourg, Tajikistan, Zambia, Anguilla, Jamaica, Sierra Leone, Switzerland, Togo, Kyrgyzstan
    Description

    Introducing Job Posting Datasets: Uncover labor market insights!

    Elevate your recruitment strategies, forecast future labor industry trends, and unearth investment opportunities with Job Posting Datasets.

    Job Posting Datasets Source:

    1. Indeed: Access datasets from Indeed, a leading employment website known for its comprehensive job listings.

    2. Glassdoor: Receive ready-to-use employee reviews, salary ranges, and job openings from Glassdoor.

    3. StackShare: Access StackShare datasets to make data-driven technology decisions.

    Job Posting Datasets provide meticulously acquired and parsed data, freeing you to focus on analysis. You'll receive clean, structured, ready-to-use job posting data, including job titles, company names, seniority levels, industries, locations, salaries, and employment types.

    Choose your preferred dataset delivery options for convenience:

    Receive datasets in various formats, including CSV, JSON, and more. Opt for storage solutions such as AWS S3, Google Cloud Storage, and more. Customize data delivery frequencies, whether one-time or per your agreed schedule.

    Why Choose Oxylabs Job Posting Datasets:

    1. Fresh and accurate data: Access clean and structured job posting datasets collected by our seasoned web scraping professionals, enabling you to dive into analysis.

    2. Time and resource savings: Focus on data analysis and your core business objectives while we efficiently handle the data extraction process cost-effectively.

    3. Customized solutions: Tailor our approach to your business needs, ensuring your goals are met.

    4. Legal compliance: Partner with a trusted leader in ethical data collection. Oxylabs is a founding member of the Ethical Web Data Collection Initiative, aligning with GDPR and CCPA best practices.

    Pricing Options:

    Standard Datasets: choose from various ready-to-use datasets with standardized data schemas, priced from $1,000/month.

    Custom Datasets: Tailor datasets from any public web domain to your unique business needs. Contact our sales team for custom pricing.

    Experience a seamless journey with Oxylabs:

    • Understanding your data needs: We work closely to understand your business nature and daily operations, defining your unique data requirements.
    • Developing a customized solution: Our experts create a custom framework to extract public data using our in-house web scraping infrastructure.
    • Delivering data sample: We provide a sample for your feedback on data quality and the entire delivery process.
    • Continuous data delivery: We continuously collect public data and deliver custom datasets per the agreed frequency.

    Effortlessly access fresh job posting data with Oxylabs Job Posting Datasets.

  13. Employee Attrition

    • kaggle.com
    zip
    Updated Dec 4, 2017
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    Aditya Bhati (2017). Employee Attrition [Dataset]. https://www.kaggle.com/datasets/aditya1205/employee-attrition
    Explore at:
    zip(51585 bytes)Available download formats
    Dataset updated
    Dec 4, 2017
    Authors
    Aditya Bhati
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Dataset

    This dataset was created by Aditya Bhati

    Released under CC0: Public Domain

    Contents

  14. Annual Earnings and Hours Survey - Table E014 : Number of Employees Analysed...

    • data.gov.hk
    csv
    Updated Apr 13, 2021
    + more versions
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    Census and Statistics Department (2021). Annual Earnings and Hours Survey - Table E014 : Number of Employees Analysed by Selected Hourly Wage Level [- Accompanying Files] [CSV Datasets] [Traditional Chinese and English] [Dataset]. https://data.gov.hk/en-data/dataset/hk-censtatd-tablechart-aehs/resource/a3e9bec8-2863-4ebf-9341-a1035c1c5211
    Explore at:
    csvAvailable download formats
    Dataset updated
    Apr 13, 2021
    Dataset provided by
    Census And Statistics Departmenthttps://www.censtatd.gov.hk/
    License

    http://data.gov.hk/en/terms-and-conditionshttp://data.gov.hk/en/terms-and-conditions

    Description

    Please visit https://www.censtatd.gov.hk/en/EIndexbySubject.html?scode=210&pcode=D5250019 for the historical issues, related publications, concept, methods, definitions of terms, and notes of this dataset. User can download, distribute and reproduce free of charge for both commercial and non-commercial purposes subject to the Terms and Conditions of Use as stipulated under DATA.GOV.HK.

  15. C

    Current Employee Names, Salaries, and Position Titles

    • chicago.gov
    • data.cityofchicago.org
    • +4more
    application/rdfxml +5
    Updated Jul 1, 2025
    + more versions
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    City of Chicago (2025). Current Employee Names, Salaries, and Position Titles [Dataset]. https://www.chicago.gov/city/en/depts/dhr/dataset/current_employeenamessalariesandpositiontitles.html
    Explore at:
    json, csv, tsv, application/rssxml, xml, application/rdfxmlAvailable download formats
    Dataset updated
    Jul 1, 2025
    Dataset authored and provided by
    City of Chicago
    Description

    This dataset is a listing of all active City of Chicago employees, complete with full names, departments, positions, employment status (part-time or full-time), frequency of hourly employee –where applicable—and annual salaries or hourly rate. Please note that "active" has a specific meaning for Human Resources purposes and will sometimes exclude employees on certain types of temporary leave. For hourly employees, the City is providing the hourly rate and frequency of hourly employees (40, 35, 20 and 10) to allow dataset users to estimate annual wages for hourly employees. Please note that annual wages will vary by employee, depending on number of hours worked and seasonal status. For information on the positions and related salaries detailed in the annual budgets, see https://www.cityofchicago.org/city/en/depts/obm.html

    Data Disclosure Exemptions: Information disclosed in this dataset is subject to FOIA Exemption Act, 5 ILCS 140/7 (Link:https://www.ilga.gov/legislation/ilcs/documents/000501400K7.htm)

  16. 2024 APS Employee Census

    • data.gov.au
    csv, pdf, sav
    Updated Jan 16, 2025
    + more versions
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    Australian Public Service Commission (2025). 2024 APS Employee Census [Dataset]. https://data.gov.au/data/dataset/2024-aps-employee-census
    Explore at:
    pdf(385719), sav(30100042), pdf(1406153), csv(264329863), csv(60289379)Available download formats
    Dataset updated
    Jan 16, 2025
    Dataset authored and provided by
    Australian Public Service Commissionhttp://www.apsc.gov.au/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Summary

    The 2024 APS Employee Census was administered to eligible Australian Public Service (APS) employees between 6 May and 7 June 2024. Overall, 140,396 APS employees responded to the APS Employee Census in 2024, a response rate of 81%.

    The APS Employee Census is an annual employee perception survey of the Australian Public Service workforce. The APS Employee Census has been conducted since 2012 and collects APS employee opinions and perspectives on a range of topics, including employee engagement, wellbeing, and leadership.

    The APS Employee Census provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error.

    Please be aware that the very large number of respondents to the APS Employee Census means these files are over 200MB in size.

    Downloading and opening these files may take some time.

    Technical notes

    Three files are available for download.

    • 2024 APS Employee Census - Questionnaire: This contains the 2024 APS Employee Census questionnaire.

    • 2024 APS Employee Census - 5 point dataset with data values: This CSV file contains individual responses to the 2024 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document. Data in this file are presented as data values.

    • 2024 APS Employee Census - 5 point dataset with data labels: This CSV file contains individual responses to the 2024 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document. Data in this file are presented as data labels.

    • 2024 APS Employee Census - 5 point dataset.sav: This file contains individual responses to the 2024 APS Employee Census for use with the SPSS software package.

    • 2024 APS Employee Census - data dictionary: This file contains a list of variables and labels within the APS Employee Census.

    To protect the privacy and confidentiality of respondents to the 2024 APS Employee Census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

    Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author.

    A recommended short citation is: 2024 APS Employee Census, Australian Public Service Commission.

    Any queries can be directed to research@apsc.gov.au.

  17. d

    Leadbook B2B Contact Data Global Coverage, 200 Million Real-Time Generated...

    • datarade.ai
    .csv
    Updated May 18, 2021
    + more versions
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    Leadbook (2021). Leadbook B2B Contact Data Global Coverage, 200 Million Real-Time Generated Contacts with Custom Filter [Dataset]. https://datarade.ai/data-products/leadbook-b2b-contact-data-global-coverage-200-million-busine-leadbook
    Explore at:
    .csvAvailable download formats
    Dataset updated
    May 18, 2021
    Dataset authored and provided by
    Leadbook
    Area covered
    Virgin Islands (British), Bangladesh, Martinique, Curaçao, Kiribati, Slovenia, Mozambique, Finland, United Arab Emirates, Belize
    Description

    Build and customise datasets to match your target audience profile, from a database of 200 million global contacts generated in real-time. Get business contact information that's verified by Leadbook's proprietary A.I. powered data technology.

    Our Industry data enables you to reach the prospects and maximize your sales and revenue by offering the most impeccable data. Our data covers several industries that provide result-oriented records to help you build and grow business. Our industry-wise data is a vast repository of verified and opt-in contacts.

    Executives and Professionals Contact Data to connect with prospects to effectively market B2B products and services. All of our email addresses come with a 97% deliverability or better guarantee.

    Simply specify location, industry, employee headcount, job function and/or seniority attributes, then the platform will verify in real-time their business contact information, and you can download the records in a CSV file.

    All records include: - Contact name - Job title - Contact email address - Contact location - Contact LinkedIn URL - Organisation name - Organisation website - Organisation type - Organisation headcount - Primary industry

    Additional information like organization phone numbers, organization address, business registration number and secondary industries may be provided where available.

    Price starts from USD 0.40 per contact rent & USD 0.80 per contact purchase. Bulk discounts apply.

  18. 2013 APS employee census

    • demo.dev.magda.io
    csv, pdf, spss
    Updated Aug 8, 2023
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    Australian Public Service Commission (2023). 2013 APS employee census [Dataset]. https://demo.dev.magda.io/dataset/ds-dga-be113f54-1aef-4682-b06e-f062fe6dfc73
    Explore at:
    spss, pdf, csvAvailable download formats
    Dataset updated
    Aug 8, 2023
    Dataset provided by
    Australian Public Service Commissionhttp://www.apsc.gov.au/
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    The 2013 APS employee census was administered to all available Australian Public Service (APS) employees. This census approach provides a comprehensive view of the APS and ensures no eligible …Show full descriptionThe 2013 APS employee census was administered to all available Australian Public Service (APS) employees. This census approach provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The census ran from 15 May to 14 June 2013. Overall, 102,219 employees responded to the employee census, a response rate of 66%. Please be aware that the very large number of respondents to the employee census means these files are up to 200 mb in size. Downloading and opening these files may take some time. TECHNICAL NOTES Three files are available for download. 2013 APS employee census - Questionnaire: This contains the 2013 APS employee census questionnaire. 2013 APS employee census - 5 point dataset.csv: This file contains individual responses to the 2013 employee census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document. 2013 APS employee census - 5 point dataset.sav: This file contains individual responses to the 2013 employee census for use with the SPSS software package. To protect the privacy and confidentiality of respondents to the 2013 APS employee census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions. Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author. A recommended short citation is: 2013 APS employee census data, Australian Public Service Commission. Any queries can be directed to research@apsc.gov.au.

  19. 2016 APS employee census

    • data.gov.au
    csv, pdf, sav
    Updated Nov 25, 2018
    + more versions
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    Australian Public Service Commission (2018). 2016 APS employee census [Dataset]. https://data.gov.au/data/dataset/groups/aps_employee_census_2016
    Explore at:
    csv(253171624), sav(22534579), pdf(216565)Available download formats
    Dataset updated
    Nov 25, 2018
    Dataset provided by
    Australian Public Service Commissionhttp://www.apsc.gov.au/
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    The 2016 Australian Public Service (APS) employee census was administered to all available APS employees. This census approach provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The census' content is designed to establish the views of APS employees on workplace issues such as leadership, learning and development and job satisfaction. The census ran from 9 May to 10 June 2016. Overall, 96,672 APS employees responded to the employee census, a response rate of 69%.

    Please be aware that the very large number of respondents to the employee census means these files are over 200 mb in size. Downloading and opening these files may take some time.

    TECHNICAL NOTES

    Three files are available for download.

    • 2016 APS employee census - Questionnaire: This contains the 2016 APS employee census questionnaire.

    • 2016 APS employee census - 5 point dataset.csv: This file contains individual responses to the 2016 APS employee census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document.

    • 2016 APS employee census - 5 point dataset.sav: This file contains individual responses to the 2016 APS employee census for use with the SPSS software package.

    To protect the privacy and confidentiality of respondents to the 2016 APS employee census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions.

    Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author.

    A recommended short citation is: 2016 APS employee census data, Australian Public Service Commission.

    Any queries can be directed to research@apsc.gov.au.

  20. 2022 APS Employee Census

    • demo.dev.magda.io
    csv, pdf, spss
    Updated Sep 25, 2023
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    Australian Public Service Commission (2023). 2022 APS Employee Census [Dataset]. https://demo.dev.magda.io/dataset/ds-dga-00b88ee3-c65f-4e7c-a661-b61001864fa1
    Explore at:
    pdf, spss, csvAvailable download formats
    Dataset updated
    Sep 25, 2023
    Dataset provided by
    Australian Public Service Commissionhttp://www.apsc.gov.au/
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    The 2022 APS Employee Census was administered to all available Australian Public Service (APS) employees, running from 9 May to 10 June 2022. The Employee Census provides a comprehensive view of the …Show full descriptionThe 2022 APS Employee Census was administered to all available Australian Public Service (APS) employees, running from 9 May to 10 June 2022. The Employee Census provides a comprehensive view of the APS and ensures no eligible respondents are omitted from the survey sample, removing sampling bias and reducing sample error. The Census' content is designed to establish the views of APS employees on workplace issues such as leadership, employee wellbeing, and job satisfaction. Overall, 120,662 APS employees responded to the Employee Census in 2022, a response rate of 83%. Please be aware that the very large number of respondents to the employee census means these files are over 200MB in size. Downloading and opening these files may take some time. TECHNICAL NOTES Three files are available for download. 2022 APS Employee Census - Questionnaire: This contains the 2022 APS Employee Census questionnaire. 2022 APS Employee Census - 5 point dataset.csv: This file contains individual responses to the 2022 APS Employee Census as clean, tabular data as required by data.gov.au. This will need to be used in conjunction with the above document. 2022 APS Employee Census - 5 point dataset.sav: This file contains individual responses to the 2022 APS Employee Census for use with the SPSS software package. To protect the privacy and confidentiality of respondents to the 2022 APS Employee Census, the datasets provided on data.gov.au include responses to a limited number of demographic or other attribute questions. Full citation of this dataset should list the Australian Public Service Commission (APSC) as the author. A recommended short citation is: 2022 APS Employee Census data, Australian Public Service Commission. Any queries can be directed to research@apsc.gov.au.

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Fahad Rehman (2024). HR Dataset.csv [Dataset]. https://www.kaggle.com/datasets/fahadrehman07/hr-comma-sep-csv
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HR Dataset.csv

HR comma separated dataset for company employee analytics

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Mar 8, 2024
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Fahad Rehman
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Description

🟡Please Upvote my dataset If you like It.✨

This dataset contains valuable employee information over time that can be analyzed to help optimize key HR functions. Some potential use cases include:

Attrition analysis: Identify factors correlated with attrition like department, role, salary, etc. Segment high-risk employees. Predict future attrition.

Performance management: Analyze the relationship between metrics like ratings, and salary increments. recommend performance improvement programs.

Workforce planning: Forecast staffing needs based on historical hiring/turnover trends. Determine optimal recruitment strategies.

Compensation analysis: Benchmark salaries vs performance, and experience. Identify pay inequities. Inform compensation policies.

Diversity monitoring: Assess diversity metrics like gender ratio over roles, and departments. Identify underrepresented groups.

Succession planning: Identify high-potential candidates and critical roles. Predict internal promotions/replacements in advance.

Given its longitudinal employee data and multiple variables, this dataset provides rich opportunities for exploration, predictive modeling, and actionable insights. With a large sample size, it can uncover subtle patterns. Cleaning, joining with other contextual data sources can yield even deeper insights. This makes it a valuable starting point for many organizational studies and evidence-based decision-making.

.............................................................................................................................................................................................................................................

This dataset contains information about different attributes of employees from a company. It includes 1000 employee records and 12 feature columns.

The columns are:

satisfaction_level: Employee satisfaction score (1-5 scale) last_evaluation: Score on last evaluation (1-5 scale) number_project: Number of projects employee worked on average_monthly_hours: Average hours worked in a month time_spend_company: Number of years spent with the company work_accident: If an employee had a workplace accident (yes/no) left: If an employee has left the company (yes/no) promotion_last_5years: Number of promotions in last 5 years Department: Department of the employee Salary: Annual salary of employee satisfaction_level: Employee satisfaction level (1-5 scale) last_evaluation: Score on last evaluation (1-5 scale)

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