Analysis of FIFA World Cup Data Set

Mansi Sharma; Palak Mittal; Nidhi Garg; and Dr  Prateek Jain

doi:10.17485/ijst/2019/v12i39/145565

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2019/v12i39/145565

Year: 2019, Volume: 12, Issue: 39, Pages: 1-4

Original Article

Analysis of FIFA World Cup Data Set

Mansi Sharma^1,2,*, Palak Mittal^1,2, Nidhi Garg^1,2 and Dr. Prateek Jain^1,2

¹ Department of Computer Science & Engineering, Manav Rachna International Institute of Research & Studies, aridabad, India; [email protected] , [email protected] , [email protected] , [email protected]
² Accendere CL Educate Ltd, India

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

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.
Keywords: Big Data, Analytics, Data Set, API, Machine Learning