Python Analysis
The following visualizations are a result of a cleaning and merging process of different datasets, like:
- "athlete_events.csv": it has data about the athletes from 1896 to 2016.
- "olympics.csv": gives us a through insight over the countries' performance up to 2016.
- "tokyo_athletes": data related to the athletes who participated in the Tokyo Games.
- "tokyo_genders": categorizes genders for each discipline.
- "tokyo_medals": summarizes the count of medals per country
And of course i went into detail later in an accompagning document that gives info about each dataset and its columns, but also about each DataFrame that was created later using the above mentioned.
These enabled me to portray a general insight of a few aspects of the games, such as:
+ The next Bar Graph shows info about the 30 most successfull countries in the Olympics, ordered by the Total amount of medals won.
+ Same as before but here in this Bar Graph i included only the count for Arab countries.
+ Here it shows the top popular sports that knew the highest rate of medals won, and again ordered by the total amount of medals registered per Sport.
+ This is another Bar Graph that shows the distibution of female and male medal count throught the years.
+ Next comes a Scatterplot which shows the participation of each gender per country.
+ Same as before but this time i highlighted the difference of gender participation when it comes to Sports.
+ For the rank of medals won by 20 most successful athletes i used a Horizontal Bar Graph.
+ Here we can see the ratio of medals won per number of participations.
+ In a Box Graph i plotted the distibution of height among male Basketball athletes throught the years.
+ And same goes for male Swimmers
+ This time i reverted to female Gymnasts.
+ And lastly for the height graphs, we have an insight of the difference between male and female athletes per year.
+ Here i'm using a Pointplot to show the distribution of weight bewteen male and female weightlifting athletes.
+ Same done but for the Gymnasts.
+ Lastly i'm using a Line Plot to show the mean age of athletes in 5 popular sports.