有没有相关的论文或文献参考？
这个数据集是基于什么背景创建的？
数据集的作者是谁？
能帮我联系到这个数据集的作者吗？
这个数据集如何下载？
Football_Civica|国际足球数据集|历史数据数据集
收藏github2024-06-18 更新2024-06-19 收录
下载链接：
https://github.com/criscris77/Football_Civica
下载链接
链接失效反馈资源简介：
该数据集包含从1872年第一场官方比赛至2024年的47,126场国际足球比赛结果。
This dataset encompasses the results of 47,126 international football matches, spanning from the first official match in 1872 to the year 2024.
创建时间：
2024-06-13
原始信息汇总
数据集概述
数据集名称
- Football_Civica
数据集来源
- CIVICA数据工程最终项目
数据集内容
- 包含47,126场国际足球比赛结果
- 时间跨度：1872年（首场官方比赛）至2024年
AI搜集汇总
数据集介绍
构建方式
在构建Football_Civica数据集时，研究者们系统性地收集了自1872年国际足球比赛开始以来的所有官方比赛结果，直至2024年。这一过程涉及对历史记录的详尽梳理与验证，确保每一场比赛的日期、参赛队伍、比分等关键信息均被准确记录。通过这种方式，数据集不仅涵盖了广泛的赛事，还保证了数据的完整性和可靠性。
特点
Football_Civica数据集的显著特点在于其跨越了长达一个半世纪的时间跨度，包含了47,126场国际足球比赛的详细结果。这一特点使得该数据集成为研究足球运动发展、队伍表现变化以及国际足球历史的重要资源。此外，数据集的高质量记录和广泛覆盖范围，使其在体育分析、历史研究以及数据科学应用中具有极高的价值。
使用方法
Football_Civica数据集的使用方法多样，适用于多种研究与应用场景。研究者可以利用该数据集进行时间序列分析，探讨足球运动在不同历史时期的演变；也可以进行队伍间的比较研究，分析各队伍在国际比赛中的表现趋势。此外，数据科学家可以运用此数据集进行机器学习模型的训练，以预测未来比赛结果或分析比赛策略的有效性。
背景与挑战
背景概述
Football_Civica数据集是由CIVICA数据工程项目团队创建的，涵盖了自1872年首次国际足球比赛至2024年的47,126场比赛结果。该数据集的构建旨在为足球历史研究、比赛分析以及预测模型提供丰富的数据支持。通过整合跨越一个半世纪的比赛记录，Football_Civica不仅为学术界提供了宝贵的研究资源，也为体育分析领域带来了新的视角和方法。
当前挑战
Football_Civica数据集在构建过程中面临多重挑战。首先，数据的时间跨度极大，从1872年至今，涉及多个历史时期的记录格式和数据质量问题。其次，国际足球比赛的规则和组织结构在不同历史阶段有所变化，这增加了数据标准化和处理的复杂性。此外，数据集的规模庞大，确保数据的准确性和一致性是一个持续的挑战。这些因素共同构成了Football_Civica在数据处理和分析方面的主要难题。
常用场景
经典使用场景
Football_Civica数据集在足球历史研究中占据重要地位，其经典使用场景包括对国际足球比赛趋势的长期分析。研究者利用该数据集，可以深入探讨不同国家队的表现变化、主场与客场优势的演变，以及重大赛事对球队排名的影响。此外，该数据集还支持对足球战术和策略的历史演变进行量化研究，为现代足球战术的发展提供历史视角。
解决学术问题
Football_Civica数据集解决了足球历史研究中的多个关键学术问题。首先，它为研究国际足球比赛的历史演变提供了详尽的数据支持，有助于揭示足球运动在全球范围内的传播与发展。其次，通过对比赛结果的统计分析，研究者可以探讨不同文化、经济和政治背景对球队表现的影响，从而丰富社会科学领域的跨学科研究。此外，该数据集还为预测模型和机器学习算法提供了丰富的训练数据，推动了体育数据分析技术的发展。
衍生相关工作
Football_Civica数据集的发布催生了多项相关经典工作。研究者基于该数据集开发了多种预测模型，用于比赛结果和球员表现的预测，显著提升了预测准确性。此外，该数据集还激发了对足球历史数据的深度挖掘，如对特定时期或特定地区的足球发展进行专题研究。学术界和业界的多项研究成果均受益于Football_Civica数据集的丰富性和完整性，推动了足球数据分析领域的持续进步。
以上内容由AI搜集并总结生成
数据主题
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集
ChemBL
ChemBL是一个化学信息学数据库，包含大量生物活性数据，涵盖了药物发现和开发过程中的各种化学实体。数据集包括化合物的结构信息、生物活性数据、靶点信息等。
www.ebi.ac.uk 收录
Canadian Census
**Overview** The data package provides demographics for Canadian population groups according to multiple location categories: Forward Sortation Areas (FSAs), Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs), Federal Electoral Districts (FEDs), Health Regions (HRs) and provinces. **Description** The data are available through the Canadian Census and the National Household Survey (NHS), separated or combined. The main demographic indicators provided for the population groups, stratified not only by location but also for the majority by demographical and socioeconomic characteristics, are population number, females and males, usual residents and private dwellings. The primary use of the data at the Health Region level is for health surveillance and population health research. Federal and provincial departments of health and human resources, social service agencies, and other types of government agencies use the information to monitor, plan, implement and evaluate programs to improve the health of Canadians and the efficiency of health services. Researchers from various fields use the information to conduct research to improve health. Non-profit health organizations and the media use the health region data to raise awareness about health, an issue of concern to all Canadians. The Census population counts for a particular geographic area representing the number of Canadians whose usual place of residence is in that area, regardless of where they happened to be on Census Day. Also included are any Canadians who were staying in that area on Census Day and who had no usual place of residence elsewhere in Canada, as well as those considered to be 'non-permanent residents'. National Household Survey (NHS) provides demographic data for various levels of geography, including provinces and territories, census metropolitan areas/census agglomerations, census divisions, census subdivisions, census tracts, federal electoral districts and health regions. In order to provide a comprehensive overview of an area, this product presents data from both the NHS and the Census. NHS data topics include immigration and ethnocultural diversity; aboriginal peoples; education and labor; mobility and migration; language of work; income and housing. 2011 Census data topics include population and dwelling counts; age and sex; families, households and marital status; structural type of dwelling and collectives; and language. The data are collected for private dwellings occupied by usual residents. A private dwelling is a dwelling in which a person or a group of persons permanently reside. Information for the National Household Survey does not include information for collective dwellings. Collective dwellings are dwellings used for commercial, institutional or communal purposes, such as a hotel, a hospital or a work camp. **Benefits** - Useful for canada public health stakeholders, for public health specialist or specialized public and other interested parties. for health surveillance and population health research. for monitoring, planning, implementation and evaluation of health-related programs. media agencies may use the health regions data to raise awareness about health, an issue of concern to all canadians. giving the addition of longitude and latitude in some of the datasets the data can be useful to transpose the values into geographical representations. the fields descriptions along with the dataset description are useful for the user to quickly understand the data and the dataset. **License Information** The use of John Snow Labs datasets is free for personal and research purposes. For commercial use please subscribe to the [Data Library](https://www.johnsnowlabs.com/marketplace/) on John Snow Labs website. The subscription will allow you to use all John Snow Labs datasets and data packages for commercial purposes. **Included Datasets** - [Canadian Population and Dwelling by FSA 2011](https://www.johnsnowlabs.com/marketplace/canadian-population-and-dwelling-by-fsa-2011) - This Canadian Census dataset covers data on population, total private dwellings and private dwellings occupied by usual residents by forward sortation area (FSA). It is enriched with the percentage of the population or dwellings versus the total amount as well as the geographical area, province, and latitude and longitude. The whole Canada's population is marked as 100, referring to 100% for the percentages. - [Detailed Canadian Population Statistics by CMAs and CAs 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-cmas-and-cas-2011) - This dataset covers the population statistics of Canada by Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs). It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. - [Detailed Canadian Population Statistics by FED 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-fed-2011) - This dataset covers the population statistics of Canada from 2011 by Federal Electoral District of 2013 Representation Order. It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. - [Detailed Canadian Population Statistics by Health Region 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-health-region-2011) - This dataset covers the population statistics of Canada by health region. It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. - [Detailed Canadian Population Statistics by Province 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-province-2011) - This dataset covers the population statistics of Canada by provinces and territories. It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. **Data Engineering Overview** **We deliver high-quality data** - Each dataset goes through 3 levels of quality review - 2 Manual reviews are done by domain experts - Then, an automated set of 60+ validations enforces every datum matches metadata & defined constraints - Data is normalized into one unified type system - All dates, unites, codes, currencies look the same - All null values are normalized to the same value - All dataset and field names are SQL and Hive compliant - Data and Metadata - Data is available in both CSV and Apache Parquet format, optimized for high read performance on distributed Hadoop, Spark & MPP clusters - Metadata is provided in the open Frictionless Data standard, and its every field is normalized & validated - Data Updates - Data updates support replace-on-update: outdated foreign keys are deprecated, not deleted **Our data is curated and enriched by domain experts** Each dataset is manually curated by our team of doctors, pharmacists, public health & medical billing experts: - Field names, descriptions, and normalized values are chosen by people who actually understand their meaning - Healthcare & life science experts add categories, search keywords, descriptions and more to each dataset - Both manual and automated data enrichment supported for clinical codes, providers, drugs, and geo-locations - The data is always kept up to date – even when the source requires manual effort to get updates - Support for data subscribers is provided directly by the domain experts who curated the data sets - Every data source’s license is manually verified to allow for royalty-free commercial use and redistribution. **Need Help?** If you have questions about our products, contact us at [info@johnsnowlabs.com](mailto:info@johnsnowlabs.com).
Databricks 收录
Titanic Dataset
Titanic Data Analysis: A Journey into Passenger Profiles and Survival Dynamics
kaggle 收录
中国行政区划shp数据
中国行政区划数据是重要的基础地理信息数据，目前不同来源的全国行政区划数据非常多，但能够开放获取的高质量行政区域数据少之又少。基于此，锐多宝的地理空间制作一套2013-2023年可开放获取的高质量行政区划数据。该套数据以2022年国家基础地理信息数据中的县区划数据作为矢量基础，辅以高德行政区划数据、天地图行政区划数据，参考历年来民政部公布的行政区划为属性基础，具有时间跨度长、属性丰富、国界准确、更新持续等特性。 中国行政区划数据统计截止时间是2023年2月12日，包含省、市、县、国界、九段线等矢量shp数据。该数据基于2020年行政区划底图，按时间顺序依次制作了2013-2023年初的行政区划数据。截止2023年1月1日，我国共有34个省级单位，分别是4个直辖市、23个省、5个自治区和2个特别行政区。截止2023年1月1日，我国共有333个地级单位，分别是293个地级市、7个地区、30个自治州和3个盟，其中38个矢量要素未纳入统计（比如直辖市北京等、特别行政区澳门等、省直辖县定安县等）。截止2023年1月1日，我国共有2843个县级单位，分别是1301个县、394个县级市、977个市辖区、117个自治县、49个旗、3个自治旗、1个特区和1个林区，其中9个矢量要素未纳入县级类别统计范畴（比如特别行政区香港、无县级单位的地级市中山市东莞市等）。
CnOpenData 收录
网易云音乐数据集
该数据集包含了网易云音乐平台上的歌手信息、歌曲信息和歌单信息，数据通过爬虫技术获取并整理成CSV格式，用于音乐数据挖掘和推荐系统构建。
github 收录