Performance Analysis in Olympic Games using Exploratory Data Analysis Techniques
Yamunathangam. D1, Kirthicka. G2, Shahanas Parveen3
1Yamunathangam. D, Assistant Professor, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
2Kirthicka. G, UG Scholars, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
3Shahanas Parveen, UG Scholars, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 12 December 2018 | Revised Manuscript received on 23 December 2018 | Manuscript Published on 09 January 2019 | PP: 251-253 | Volume-7 Issue-4S November 2018 | Retrieval Number: E2044017519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Olympic games are international sports events with more than 200 nations participating in various competitions. The Sportspersons from various countries participate in competitions and make their countries proud of their excellence in sports. Despite massive population, many most populous countries fail to grab many medals at the Olympic games. The primary objective of this paper is to analyse the Olympic dataset using python to compare overall performance of countries and to evaluate the contribution of each country in Olympics. These analyses will give deeper insight into the performance of countries in Olympics over the years and helps sportspersons to quickly analyse their own and the competitor’s performance. In this paper, the exploratory data analysis techniques are used to provide comparison between performance of various countries and the contribution of each country in Olympics. Visualization of Olympics dataset in many aspects provides the status of countries in Olympics and helps countries with poor performance to produce quality players and improve nation’s performance in Olympics.
Keywords: International, Excellence, Performance Analysis, Visualization.
Scope of the Article: Data Analytic