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Data Analysis FIFA World Cup Data Set

机译:数据分析FIFA世界杯数据集

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Background/objectives: To analyze a data set related to FIFA World Cup using a suitable method. Methods/statistical analysis: In this study we have taken up the data sets of the FIFA World Cup and analyzed them using Python and R programming. The analysis focused on: a) which team conceded a greater number of goals than they scored; b) the percentage of goals scored in the First Half, Second Half, Extra Time, and Penalty Shootout; the c) highest average attendance in a particular stage of the match. Findings: Python seems to be an emerging programming language and is thriving to a great extent. Due to its advantages of easy-to-learn syntax, improved readability, object-oriented programming support, integration support, and extensive libraries, this language is adaptable in many fields and hence increasing its applications.
机译:背景/目的:使用适当的方法分析与FIFA世界杯相关的数据集。方法/统计分析:在这项研究中,我们收集了FIFA世界杯的数据集,并使用Python和R编程对其进行了分析。分析的重点是:a)哪个团队承认的进球数量超过了他们的得分; b)在上半场,下半场,加时赛和点球大战中进球得分的百分比; c)在比赛的特定阶段,平均出勤率最高。结果:Python似乎是一种新兴的编程语言,并且在很大程度上得到了发展。由于其易于学习的语法,提高的可读性,面向对象的编程支持,集成支持和广泛的库等优点,该语言可在许多领域中使用,从而增加了其应用范围。

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