100+ datasets found
  1. d

    WDFW Item Statistics By Month

    • catalog.data.gov
    • data.wa.gov
    • +2more
    Updated Mar 22, 2025
    + more versions
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    data.wa.gov (2025). WDFW Item Statistics By Month [Dataset]. https://catalog.data.gov/dataset/wdfw-item-statistics-by-month
    Explore at:
    Dataset updated
    Mar 22, 2025
    Dataset provided by
    data.wa.gov
    Description

    Data provided here is used by WDFW’s partners, government entities, schools, private businesses, and the general public. WDFW actively promotes inter-agency data exchange and resource sharing. Every effort is made to provide accurate, complete, and timely information on this site. However, some content may be incomplete or out of date. The content on this site is subject to change without notice. The Washington Department of Fish and Wildlife (WDFW) shall not be liable for any activity involving this data with regard to lost profits or savings or any other consequential damages; or the fitness for use of the data for a particular purpose; or the installation of the data, its use, or the results obtained.

  2. Smite Item Statistics Data

    • kaggle.com
    Updated Apr 23, 2024
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    Matt OP (2024). Smite Item Statistics Data [Dataset]. https://www.kaggle.com/datasets/mattop/smite-item-statistics-data/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 23, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Matt OP
    License

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

    Description

    This dataset provides comprehensive statistics on items available in Smite, a popular multiplayer online battle arena (MOBA) game. Each entry includes detailed information such as item type, tier, cost, total cost, stats provided, and any passive effects associated with the item.

    • Item: The name of the item.
    • Item Type: Categorization of the item based on its function or purpose in the game, such as physical damage, magical power, defense, utility, or consumables.
    • Item Tier: The tier or level of the item, indicating its power and effectiveness relative to other items.
    • Cost: The base cost of purchasing the item.
    • Total Cost: The total amount of in-game currency required to fully upgrade or purchase the item, including any additional costs for upgrades or enhancements.
    • Stats: A breakdown of the numerical attributes and bonuses provided by the item, including factors like health, mana, physical power, magical power, attack speed, penetration, and more.
    • Passive Effect: Any unique or passive abilities granted by the item when equipped, which may offer strategic advantages or synergies with specific character builds and playstyles.

    This dataset serves as a valuable resource for Smite players, allowing them to analyze item effectiveness, optimize builds, and make informed decisions during gameplay to gain a competitive edge on the battlefield.

    Link to notebook used to collect the data.

  3. Most stolen items in the United States in 2015

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Most stolen items in the United States in 2015 [Dataset]. https://www.statista.com/statistics/813986/most-stolen-items-us/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2015
    Area covered
    United States
    Description

    This statistic displays the most stolen items in the United States in 2015. In 2015, there were ****** incidents where clothing was stolen.

  4. d

    Comprehensive tax income item 5 percentile declaration statistics table

    • data.gov.tw
    csv
    Updated Jun 1, 2025
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    Fiscal Information Agency,Ministry of Finance (2025). Comprehensive tax income item 5 percentile declaration statistics table [Dataset]. https://data.gov.tw/en/datasets/17685
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    csvAvailable download formats
    Dataset updated
    Jun 1, 2025
    Dataset authored and provided by
    Fiscal Information Agency,Ministry of Finance
    License

    https://data.gov.tw/licensehttps://data.gov.tw/license

    Description

    Tax on Various Types of Income by Quintile of the Number of Items Reported Statistical Table Unit: Number of Items

  5. s

    SMITE 2 Game Statistics

    • smite2.live
    Updated Jul 15, 2025
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    (2025). SMITE 2 Game Statistics [Dataset]. https://smite2.live/statistics?v=ob14.0
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    Dataset updated
    Jul 15, 2025
    Description

    Collection of SMITE 2 game statistics including god performance metrics and item analytics for patch ob14.0

  6. Computer - items open simultaneously at work

    • statista.com
    Updated May 24, 2011
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    Statista (2011). Computer - items open simultaneously at work [Dataset]. https://www.statista.com/statistics/273144/computer-items-open-simultaneously-at-work/
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    Dataset updated
    May 24, 2011
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 11, 2011 - Mar 29, 2011
    Area covered
    Worldwide
    Description

    This statistic shows the number of items users have typically open on a workplace computer during work in 2011.

  7. H

    Replication data for: Item Similarity in Scale Analysis

    • dataverse.harvard.edu
    • search.datacite.org
    Updated Feb 16, 2010
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    Marco R. Steenbergen (2010). Replication data for: Item Similarity in Scale Analysis [Dataset]. http://doi.org/10.7910/DVN/DMOMCF
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 16, 2010
    Dataset provided by
    Harvard Dataverse
    Authors
    Marco R. Steenbergen
    License

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

    Description

    A statistic—the similarity coefficient—is developed for assessing the property that a set of scale items measures one and only one construct. This statistic is rooted in an explicit measurement model and is flexible enough to be used in exploratory scale analyses, even in small samples. Methods for analyzing similarity coefficients are described and illustrated in analyses of Stimson’s (1991) policy mood data and Markus’ (1990) popular individualism items. The Appendix discusses the statistical properties of similarity coefficients.

  8. w

    NQQ18 - Expenditure on Gross National Product (chain linked annually and...

    • data.wu.ac.at
    • cloud.csiss.gmu.edu
    json-stat, px
    Updated Mar 5, 2018
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    Central Statistics Office (2018). NQQ18 - Expenditure on Gross National Product (chain linked annually and referenced to 2010) by Quarter, Statistic and Expenditure Item [Dataset]. https://data.wu.ac.at/schema/data_gov_ie/N2ZjNzcyNGMtM2ZjZS00YmI0LTg0ZTEtNWFjMmRlZmJjMmVm
    Explore at:
    json-stat, pxAvailable download formats
    Dataset updated
    Mar 5, 2018
    Dataset provided by
    Central Statistics Office
    License

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

    Description

    Expenditure on Gross National Product (chain linked annually and referenced to 2010) by Quarter, Statistic and Expenditure Item

    View data using web pages

    Download .px file (Software required)

  9. Economic Census: Core Statistics: US Industry Product Data

    • catalog.data.gov
    • s.cnmilf.com
    Updated Jul 19, 2023
    + more versions
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    U.S. Census Bureau (2023). Economic Census: Core Statistics: US Industry Product Data [Dataset]. https://catalog.data.gov/dataset/economic-census-core-statistics-us-industry-product-data
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    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Area covered
    United States
    Description

    The Economic Census is the U.S. Government's official five-year measure of American business and the economy. It is conducted by the U.S. Census Bureau, and response is required by law. In October through December of the census year, forms are sent out to nearly 4 million businesses, including large, medium and small companies representing all U.S. locations and industries. Respondents were asked to provide a range of operational and performance data for their companies. This dataset presents company, establishments, value of shipments, value of product shipments, percentage of product shipments of the total value of shipments, and percentage of distribution of value of product shipments.

  10. CourseKata Dataset Items (QuestionTypes)

    • kaggle.com
    Updated Apr 21, 2024
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    Gagan Karnati (2024). CourseKata Dataset Items (QuestionTypes) [Dataset]. https://www.kaggle.com/datasets/gagankarnati/coursekata-dataset-items-questiontypes
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 21, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Gagan Karnati
    Description

    CourseKata is a platform that creates and publishes a series of e-books for introductory statistics and data science classes that utilize demonstrated learning strategies to help students learn statistics and data science. The developers of CourseKata, Jim Stigler (UCLA) and Ji Son (Cal State Los Angeles) and their team, are cognitive psychologists interested in improving statistics learning by examining students' interactions with online interactive textbooks. Traditionally, much of the research in how students learn is done in a 1-hour lab or through small-scale interviews with students. CourseKata offers the opportunity to peek into the actions, responses, and choices of thousands of students as they are engaged in learning the interrelated concepts and skills of statistics and coding in R over many weeks or months in real classes.

    1. items.csv (1335 X 19) Each row contains information about a particular question (although it does not provide the prompt). The item to which a question belongs is included. All items/questions are represented. Use this file to go deeper into particular questions that students encounter in the course.

    Questions are grouped into items (item_id). An item can be one of three item_type 's: code, learnosity or learnosity-activity (the distinction between learnosity and learnosity-activity is not important). Code items are a single question and ask for R code as a response. (Responses can be seen in responses.csv.) Learnosity-activities and learnosity items are collections of one or more questions that can be of a variety of lrn_type's: ● association ● choicematrix ● clozeassociation ● formulaV2 ● imageclozeassociation ● mcq ● plaintext ● shorttext ● sortlist

    Examples of these question types are provided at the end of this document.

    The level of detail made available to you in the responses file depends on the lrn_type. For example, for multiple choice questions (mcq), you can find the options in the responses file in the columns labeled lrn_option_0 through lrn_option_11, and you can see the chosen option in the results variable.

    Assessment Types In general, assessments, such as the items and questions included in CourseKata, can be used for two purposes. Formative assessments are meant to provide feedback to the student (and instructor), or to serve as a learning aid to help prompt students improve memory and deepen their understanding. Summative assessments are meant to provide a summary of a student's understanding, often for use in assigning a grade. For example, most midterms and final exams that you've taken are summative assessments.

    The vast majority of items in CourseKata should be treated as formative assessments. The exceptions are the end-of-chapter Review questions, which can be thought of as summative. The mean number of correct answers for end-of-chapter review questions is provided within the checkpoints file. You might see that some pages have the word "Quiz" or "Exam" or "Midterm" in them. Results from these items and responses to them are not provided to us in this data set.

  11. Fastest-growing home-based items across different categories 2020, by search...

    • statista.com
    Updated Dec 5, 2022
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    Statista (2022). Fastest-growing home-based items across different categories 2020, by search growth [Dataset]. https://www.statista.com/statistics/1154395/fastest-growing-items-worldwide-search-growth-select-categories/
    Explore at:
    Dataset updated
    Dec 5, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    As of April 2020, the fastest-growing home-based item worldwide, based on year-on-year search growth, was frozen bread. Online searches for frozen bread increased by 414 percent compared to the same period in the previous year. The coronavirus outbreak has lead many customers to reassess their shopping habits and many consumers have turned to the internet to stock up on everyday essentials. As many people stayed at home in order to effectively socially distance, a regular shop at the bakery was off the cards for many, coupled with the fact that home-baking experienced a boom in popularity. This new-found hype for home baking lead flour and yeast to be sold out in many locations, hence customers turning to frozen bread before going entirely without. Other popular home-based items include indulgent snacks and technology to help setting up a home workspace.

  12. Mexico: Waste and scrap; n.e.c. in item no 8549.91 2007-2024

    • app.indexbox.io
    Updated Jan 15, 2025
    + more versions
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    IndexBox AI Platform (2025). Mexico: Waste and scrap; n.e.c. in item no 8549.91 2007-2024 [Dataset]. https://app.indexbox.io/table/854999/484/
    Explore at:
    Dataset updated
    Jan 15, 2025
    Dataset provided by
    IndexBox
    Authors
    IndexBox AI Platform
    License

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

    Time period covered
    Jan 1, 2007 - Dec 31, 2024
    Area covered
    Mexico
    Description

    Statistics illustrates consumption, production, prices, and trade of Waste and scrap; n.e.c. in item no 8549.91 in Mexico from 2007 to 2024.

  13. Taiwan (Chinese): Waste and scrap; n.e.c. in item no 8549.91 2019-2025

    • app.indexbox.io
    Updated May 15, 2025
    + more versions
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    IndexBox AI Platform (2025). Taiwan (Chinese): Waste and scrap; n.e.c. in item no 8549.91 2019-2025 [Dataset]. https://app.indexbox.io/table/854999/490/monthly/
    Explore at:
    Dataset updated
    May 15, 2025
    Dataset provided by
    IndexBox
    Authors
    IndexBox AI Platform
    License

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

    Time period covered
    Jan 1, 2019 - Dec 31, 2025
    Area covered
    Taiwan
    Description

    Statistics illustrates consumption, production, prices, and trade of Waste and scrap; n.e.c. in item no 8549.91 in Taiwan (Chinese) from Jan 2019 to May 2025.

  14. w

    NAH29 - T29 Social Protection Accounts by Item and Year

    • data.wu.ac.at
    json-stat, px
    Updated Mar 5, 2018
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    Central Statistics Office (2018). NAH29 - T29 Social Protection Accounts by Item and Year [Dataset]. https://data.wu.ac.at/schema/data_gov_ie/OTc0Y2EzNmMtMmYyOC00Nzg1LTkyYjYtYTg2NTFlYTZkZmVk
    Explore at:
    px, json-statAvailable download formats
    Dataset updated
    Mar 5, 2018
    Dataset provided by
    Central Statistics Office
    License

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

    Description

    T29 Social Protection Accounts by Item and Year

    View data using web pages

    Download .px file (Software required)

  15. W

    NQQ21 - Expenditure on Gross National Product (chain linked annually and...

    • cloud.csiss.gmu.edu
    json-stat, px
    Updated Jun 20, 2019
    + more versions
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    Ireland (2019). NQQ21 - Expenditure on Gross National Product (chain linked annually and referenced to 2011) by Expenditure Item, Quarter and Statistic [Dataset]. https://cloud.csiss.gmu.edu/uddi/pt_BR/dataset/ional-product-chain-linked-annually-and-referenced-to-2011-by-expenditure-item-quarter-and-stat
    Explore at:
    px, json-statAvailable download formats
    Dataset updated
    Jun 20, 2019
    Dataset provided by
    Ireland
    License

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

    Description

    Expenditure on Gross National Product (chain linked annually and referenced to 2011) by Expenditure Item, Quarter and Statistic

    View data using web pages

    Download .px file (Software required)

  16. Americans' must-have items for a tailgating party 2014

    • statista.com
    Updated Sep 14, 2014
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    Statista (2014). Americans' must-have items for a tailgating party 2014 [Dataset]. https://www.statista.com/statistics/271700/americans-must-have-items-for-a-tailgating-party/
    Explore at:
    Dataset updated
    Sep 14, 2014
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2014
    Area covered
    United States
    Description

    This statistic sums up the results from the annual Weber GrillWatch Survey, conducted in February 2014. Grill owners in the United States were asked about the most important items for a proper tailgating party. Some ** percent of survey respondents indicated to consider food as a must-have item for a decent tailgating party.

  17. Micronesia: Waste and scrap; n.e.c. in item no 8549.91 2007-2024

    • app.indexbox.io
    Updated Jul 31, 2024
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    IndexBox AI Platform (2024). Micronesia: Waste and scrap; n.e.c. in item no 8549.91 2007-2024 [Dataset]. https://app.indexbox.io/table/854999/583/
    Explore at:
    Dataset updated
    Jul 31, 2024
    Dataset provided by
    IndexBox
    Authors
    IndexBox AI Platform
    License

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

    Time period covered
    Jan 1, 2007 - Dec 31, 2024
    Area covered
    Micronesia
    Description

    Statistics illustrates consumption, production, prices, and trade of Waste and scrap; n.e.c. in item no 8549.91 in Micronesia from 2007 to 2024.

  18. MENA: Waste and scrap; n.e.c. in item no 8549.91 2007-2024

    • app.indexbox.io
    Updated Jul 17, 2024
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    IndexBox AI Platform (2024). MENA: Waste and scrap; n.e.c. in item no 8549.91 2007-2024 [Dataset]. https://app.indexbox.io/table/854999/993/
    Explore at:
    Dataset updated
    Jul 17, 2024
    Dataset provided by
    IndexBox
    Authors
    IndexBox AI Platform
    License

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

    Time period covered
    Jan 1, 2007 - Dec 31, 2024
    Area covered
    MENA
    Description

    Statistics illustrates consumption, production, prices, and trade of Waste and scrap; n.e.c. in item no 8549.91 in MENA from 2007 to 2024.

  19. Consumers considering a clothing items subscription in the U.S. 2017, by...

    • statista.com
    Updated Sep 25, 2024
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    Statista (2024). Consumers considering a clothing items subscription in the U.S. 2017, by gender [Dataset]. https://www.statista.com/statistics/721818/consideration-to-subscribe-to-clothing-item-by-gender/
    Explore at:
    Dataset updated
    Sep 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2017 - Feb 2017
    Area covered
    United States
    Description

    This statistic provides information on the likelihood of consumers to consider a clothing items subscription in the United States as of February 2017, sorted by gender. According to the source, 15 percent of U.S. male respondents reported being likely to consider a clothing items subscription.

  20. Reunion: Waste and scrap; n.e.c. in item no 8549.91 2007-2024

    • app.indexbox.io
    Updated Jun 20, 2025
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    IndexBox AI Platform (2025). Reunion: Waste and scrap; n.e.c. in item no 8549.91 2007-2024 [Dataset]. https://app.indexbox.io/table/854999/638/
    Explore at:
    Dataset updated
    Jun 20, 2025
    Dataset provided by
    IndexBox
    Authors
    IndexBox AI Platform
    License

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

    Time period covered
    Jan 1, 2007 - Dec 31, 2024
    Area covered
    Reunion
    Description

    Statistics illustrates consumption, production, prices, and trade of Waste and scrap; n.e.c. in item no 8549.91 in Reunion from 2007 to 2024.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
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data.wa.gov (2025). WDFW Item Statistics By Month [Dataset]. https://catalog.data.gov/dataset/wdfw-item-statistics-by-month

WDFW Item Statistics By Month

Explore at:
Dataset updated
Mar 22, 2025
Dataset provided by
data.wa.gov
Description

Data provided here is used by WDFW’s partners, government entities, schools, private businesses, and the general public. WDFW actively promotes inter-agency data exchange and resource sharing. Every effort is made to provide accurate, complete, and timely information on this site. However, some content may be incomplete or out of date. The content on this site is subject to change without notice. The Washington Department of Fish and Wildlife (WDFW) shall not be liable for any activity involving this data with regard to lost profits or savings or any other consequential damages; or the fitness for use of the data for a particular purpose; or the installation of the data, its use, or the results obtained.

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