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doing data analysis on data set 120-years-of-olympic-history-athletes-and-results in kaggle https://www.kaggle.com/hmselkholy/olympics-analysis

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data-analysis-olympics's Introduction

Olympics Data Exploration

Dataset

I used data sets of "120-years-of-olympic-history-athletes-and-results" in Kaggele which has information about players , their teams , medals and gender

The data consists of information regarding 271116 rows and includes :

Event related :
- City
- Year
Athlete related:
- Sport
- Age
- Weight
- Height
- Medal
- Name
- Team
- region
- notes

Summary of Findings

we find most hosting cities as follows

Most contributors at 25 years old

Olympics popularity increases every year but the winter season has less players
from 1994 olympics has one season every year

there are most contributors

those are independent teams

We find Arts very has different age distribution due to less physical effort

Basketball must have higher players than others

Gym's most players are shorter

Most sports popularity are increasing but arts has no longer any players since 1948

those are best players for each medal

women appear to have similar trend in winter like men but men have larger trend in summer

we can focus on players from 20to30 years with Height/Weight ratio 2to2.50 to support for medals

Key Insights for Presentation

I focused on distribution of :

age
height
weight

and separated outliers by their sport for further analysis to find sports with different distribution

I focused on frequency of players and started to generate several plots depending on :

sex
year
medals
season
height and weight
- to reach that:
  - women trend grew to be similar to men over winter season
  - most winning players prefect height ,weight and age
  - sports that are stopped in olympics like arts

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