7 datasets found
  1. B

    Data Cleaning Sample

    • borealisdata.ca
    • dataone.org
    Updated Jul 13, 2023
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    Rong Luo (2023). Data Cleaning Sample [Dataset]. http://doi.org/10.5683/SP3/ZCN177
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 13, 2023
    Dataset provided by
    Borealis
    Authors
    Rong Luo
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Sample data for exercises in Further Adventures in Data Cleaning.

  2. m

    Dataset of development of business during the COVID-19 crisis

    • data.mendeley.com
    • narcis.nl
    Updated Nov 9, 2020
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    Tatiana N. Litvinova (2020). Dataset of development of business during the COVID-19 crisis [Dataset]. http://doi.org/10.17632/9vvrd34f8t.1
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    Dataset updated
    Nov 9, 2020
    Authors
    Tatiana N. Litvinova
    License

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

    Description

    To create the dataset, the top 10 countries leading in the incidence of COVID-19 in the world were selected as of October 22, 2020 (on the eve of the second full of pandemics), which are presented in the Global 500 ranking for 2020: USA, India, Brazil, Russia, Spain, France and Mexico. For each of these countries, no more than 10 of the largest transnational corporations included in the Global 500 rating for 2020 and 2019 were selected separately. The arithmetic averages were calculated and the change (increase) in indicators such as profitability and profitability of enterprises, their ranking position (competitiveness), asset value and number of employees. The arithmetic mean values of these indicators for all countries of the sample were found, characterizing the situation in international entrepreneurship as a whole in the context of the COVID-19 crisis in 2020 on the eve of the second wave of the pandemic. The data is collected in a general Microsoft Excel table. Dataset is a unique database that combines COVID-19 statistics and entrepreneurship statistics. The dataset is flexible data that can be supplemented with data from other countries and newer statistics on the COVID-19 pandemic. Due to the fact that the data in the dataset are not ready-made numbers, but formulas, when adding and / or changing the values in the original table at the beginning of the dataset, most of the subsequent tables will be automatically recalculated and the graphs will be updated. This allows the dataset to be used not just as an array of data, but as an analytical tool for automating scientific research on the impact of the COVID-19 pandemic and crisis on international entrepreneurship. The dataset includes not only tabular data, but also charts that provide data visualization. The dataset contains not only actual, but also forecast data on morbidity and mortality from COVID-19 for the period of the second wave of the pandemic in 2020. The forecasts are presented in the form of a normal distribution of predicted values and the probability of their occurrence in practice. This allows for a broad scenario analysis of the impact of the COVID-19 pandemic and crisis on international entrepreneurship, substituting various predicted morbidity and mortality rates in risk assessment tables and obtaining automatically calculated consequences (changes) on the characteristics of international entrepreneurship. It is also possible to substitute the actual values identified in the process and following the results of the second wave of the pandemic to check the reliability of pre-made forecasts and conduct a plan-fact analysis. The dataset contains not only the numerical values of the initial and predicted values of the set of studied indicators, but also their qualitative interpretation, reflecting the presence and level of risks of a pandemic and COVID-19 crisis for international entrepreneurship.

  3. AdventureWorks2022- Excel Format (.xlsx)

    • kaggle.com
    zip
    Updated Sep 1, 2024
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    Titus P R (2024). AdventureWorks2022- Excel Format (.xlsx) [Dataset]. https://www.kaggle.com/datasets/tituspr/adventureworks2022-excel-format/code
    Explore at:
    zip(41930707 bytes)Available download formats
    Dataset updated
    Sep 1, 2024
    Authors
    Titus P R
    Description

    The Adventure Works dataset is a comprehensive and widely used sample database provided by Microsoft for educational and testing purposes. It's designed to represent a fictional company, Adventure Works Cycles, which is a global manufacturer of bicycles and related products. The dataset is often used for learning and practicing various data management, analysis, and reporting skills.

    Key Features of the Adventure Works Dataset:

    1. Company Overview: - Industry: Bicycle manufacturing - Operations: Global presence with various departments such as sales, production, and human resources.

    2. Data Structure: - Tables: The dataset includes a variety of tables, typically organized into categories such as: - Sales: Information about sales orders, products, and customer details. - Production: Data on manufacturing processes, inventory, and product specifications. - Human Resources: Employee details, departments, and job roles. - Purchasing: Vendor information and purchase orders.

    3. Sample Tables: - Sales.SalesOrderHeader: Contains information about sales orders, including order dates, customer IDs, and total amounts. - Sales.SalesOrderDetail: Details of individual items within each sales order, such as product ID, quantity, and unit price. - Production.Product: Information about the products being manufactured, including product names, categories, and prices. - Production.ProductCategory: Data on product categories, such as bicycles and accessories. - Person.Person: Contains personal information about employees and contacts, including names and addresses. - Purchasing.Vendor: Information on vendors that supply the company with materials.

    4. Usage: - Training and Education: It's widely used for teaching SQL, data analysis, and database management. - Testing and Demonstrations: Useful for testing software features and demonstrating data-related functionalities.

    5. Tools: - The dataset is often used with Microsoft SQL Server, but it's also compatible with other relational database systems.

    The Adventure Works dataset provides a rich and realistic environment for practicing a range of data-related tasks, from querying and reporting to data modeling and analysis.

  4. Adventure Works 2022 CSVs

    • kaggle.com
    zip
    Updated Nov 2, 2022
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    Algorismus (2022). Adventure Works 2022 CSVs [Dataset]. https://www.kaggle.com/datasets/algorismus/adventure-works-in-excel-tables
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    zip(567646 bytes)Available download formats
    Dataset updated
    Nov 2, 2022
    Authors
    Algorismus
    License

    http://www.gnu.org/licenses/lgpl-3.0.htmlhttp://www.gnu.org/licenses/lgpl-3.0.html

    Description

    Adventure Works 2022 dataset

    How this Dataset is created?

    On the official website the dataset is available over SQL server (localhost) and CSVs to be used via Power BI Desktop running on Virtual Lab (Virtaul Machine). As per first two steps of Importing data are executed in the virtual lab and then resultant Power BI tables are copied in CSVs. Added records till year 2022 as required.

    How this Dataset may help you?

    this dataset will be helpful in case you want to work offline with Adventure Works data in Power BI desktop in order to carry lab instructions as per training material on official website. The dataset is useful in case you want to work on Power BI desktop Sales Analysis example from Microsoft website PL 300 learning.

    How to use this Dataset?

    Download the CSV file(s) and import in Power BI desktop as tables. The CSVs are named as tables created after first two steps of importing data as mentioned in the PL-300 Microsoft Power BI Data Analyst exam lab.

  5. w

    Fire statistics data tables

    • gov.uk
    • s3.amazonaws.com
    Updated Oct 23, 2025
    + more versions
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    Ministry of Housing, Communities and Local Government (2025). Fire statistics data tables [Dataset]. https://www.gov.uk/government/statistical-data-sets/fire-statistics-data-tables
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    Dataset updated
    Oct 23, 2025
    Dataset provided by
    GOV.UK
    Authors
    Ministry of Housing, Communities and Local Government
    Description

    On 1 April 2025 responsibility for fire and rescue transferred from the Home Office to the Ministry of Housing, Communities and Local Government.

    This information covers fires, false alarms and other incidents attended by fire crews, and the statistics include the numbers of incidents, fires, fatalities and casualties as well as information on response times to fires. The Ministry of Housing, Communities and Local Government (MHCLG) also collect information on the workforce, fire prevention work, health and safety and firefighter pensions. All data tables on fire statistics are below.

    MHCLG has responsibility for fire services in England. The vast majority of data tables produced by the Ministry of Housing, Communities and Local Government are for England but some (0101, 0103, 0201, 0501, 1401) tables are for Great Britain split by nation. In the past the Department for Communities and Local Government (who previously had responsibility for fire services in England) produced data tables for Great Britain and at times the UK. Similar information for devolved administrations are available at https://www.firescotland.gov.uk/about/statistics/">Scotland: Fire and Rescue Statistics, https://statswales.gov.wales/Catalogue/Community-Safety-and-Social-Inclusion/Community-Safety">Wales: Community safety and https://www.nifrs.org/home/about-us/publications/">Northern Ireland: Fire and Rescue Statistics.

    If you use assistive technology (for example, a screen reader) and need a version of any of these documents in a more accessible format, please email alternativeformats@communities.gov.uk. Please tell us what format you need. It will help us if you say what assistive technology you use.

    Related content

    Fire statistics guidance
    Fire statistics incident level datasets

    Incidents attended

    https://assets.publishing.service.gov.uk/media/68f0f810e8e4040c38a3cf96/FIRE0101.xlsx">FIRE0101: Incidents attended by fire and rescue services by nation and population (MS Excel Spreadsheet, 143 KB) Previous FIRE0101 tables

    https://assets.publishing.service.gov.uk/media/68f0ffd528f6872f1663ef77/FIRE0102.xlsx">FIRE0102: Incidents attended by fire and rescue services in England, by incident type and fire and rescue authority (MS Excel Spreadsheet, 2.12 MB) Previous FIRE0102 tables

    https://assets.publishing.service.gov.uk/media/68f20a3e06e6515f7914c71c/FIRE0103.xlsx">FIRE0103: Fires attended by fire and rescue services by nation and population (MS Excel Spreadsheet, 197 KB) Previous FIRE0103 tables

    https://assets.publishing.service.gov.uk/media/68f20a552f0fc56403a3cfef/FIRE0104.xlsx">FIRE0104: Fire false alarms by reason for false alarm, England (MS Excel Spreadsheet, 443 KB) Previous FIRE0104 tables

    Dwelling fires attended

    https://assets.publishing.service.gov.uk/media/68f100492f0fc56403a3cf94/FIRE0201.xlsx">FIRE0201: Dwelling fires attended by fire and rescue services by motive, population and nation (MS Excel Spreadsheet, 192 KB) Previous FIRE0201 tables

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  6. Superstore Dataset

    • kaggle.com
    zip
    Updated Sep 25, 2023
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    Shivam Amrutkar (2023). Superstore Dataset [Dataset]. https://www.kaggle.com/datasets/yesshivam007/superstore-dataset
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    zip(2119716 bytes)Available download formats
    Dataset updated
    Sep 25, 2023
    Authors
    Shivam Amrutkar
    License

    https://cdla.io/sharing-1-0/https://cdla.io/sharing-1-0/

    Description

    The Superstore Sales Data dataset, available in an Excel format as "Superstore.xlsx," is a comprehensive collection of sales and customer-related information from a retail superstore. This dataset comprises* three distinct tables*, each providing specific insights into the store's operations and customer interactions.

  7. Health insurance dataset | India-2022

    • kaggle.com
    Updated May 28, 2023
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    balaji adithya (2023). Health insurance dataset | India-2022 [Dataset]. https://www.kaggle.com/datasets/balajiadithya/health-insurance-dataset-india-2022
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 28, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    balaji adithya
    License

    http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/

    Area covered
    India
    Description

    Context

    This public dataset contains data concerning the public and private insurance companies provided by IRDAI(Insurance Regulatory and Development Authority of India) from 2013-2022. This is a multi-index data and can be a great practice to hone manipulation of pandas multi-index dataframes. Mainly, the business of the companies (total premiums and number of policies), subscription information(number of people subscribed), Claims incurred and the Network hospitals enrolled by Third Party Administrators are attributes focused by the dataset.

    Content

    The Excel file contains the following data | Table No.| Contents| | --- | --- | |**A**|**III.A: HEALTH INSURANCE BUSINESS OF GENERAL AND HEALTH INSURERS**| |62| Health Insurance - Number of Policies, Number of Persons Covered and Gross Premium| |63| Personal Accident Insurance - Number of Policies, Number of Persons Covered and Gross Premium| |64| Overseas Travel Insurance - Number of Policies, Number of Persons Covered and Gross Premium| |65| Domestic Travel Insurance - Number of Policies, Number of Persons Covered and Gross Premium| |66| Health Insurance - Net Premium Earned, Incurred Claims and Incurred Claims Ratio| |67| Personal Accident Insurance - Net Premium Earned, Incurred Claims and Incurred Claims Ratio| |68| Overseas Travel Insurance - Net Earned Premium, Incurred Claims and Incurred Claims Ratio| |69| Domestic Travel Insurance - Net Earned Premium, Incurred Claims and Incurred Claims Ratio| |70| Details of Claims Development and Aging - Health Insurance Business| |71| State-wise Health Insurance Business| |72| State-wise Individual Health Insurance Business| |73| State-wise Personal Accident Insurance Business| |74| State-wise Overseas Insurance Business| |75| State-wise Domestic Insurance Business| |76| State-wise Claims Settlement under Health Insurance Business| |**B**|**III.B: HEALTH INSURANCE BUSINESS OF LIFE INSURERS**| |77| Health Insurance Business in respect of Products offered by Life Insurers - New Busienss| |78| Health Insurance Business in respect of Products offered by Life insurers - Renewal Business| |79| Health Insurance Business in respect of Riders attached to Life Insurance Products - New Business| |80| Health Insurance Business in respect of Riders attached to Life Insurance Products - Renewal Business| |**C**|**III.C: OTHERS**| |81| Network Hospital Enrolled by TPAs| |82| State-wise Details on Number of Network Providers |

  8. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
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Rong Luo (2023). Data Cleaning Sample [Dataset]. http://doi.org/10.5683/SP3/ZCN177

Data Cleaning Sample

Explore at:
167 scholarly articles cite this dataset (View in Google Scholar)
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Jul 13, 2023
Dataset provided by
Borealis
Authors
Rong Luo
License

CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically

Description

Sample data for exercises in Further Adventures in Data Cleaning.

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