Olympics Dataset - Case Study

Load the olympics dataset (olympics.csv), which was derrived from the Wikipedia entry on All Time Olympic Games Medals.

Question - 1:

Create a dataframe with following data cleanup to make this file redable.

• Create a function load_data to read CSV file and convert CSV data to dataframe.
• Skip first row
• Rename column containing 01, 02 and 03 to Gold, Silver and Bronze
• Split country name and country code and add country name as data frame index
• Remove extra unnecessary characters from country name.
• Drop the column Totals
• Return dataframe.

Question - 2:

Write a function to get first country details from dataframe we got from load_data function.

• Create a function first_country.
• Return results for first country.

Question - 3:

Which country has won the most gold medals in summer games?

• Create a function gold_medal to get name of country who won most gold medals.
• Return country name.

Question - 4:

Which country had the biggest difference between their summer and winter gold medal counts?

• Create a function biggest_difference_in_gold_medal to get name of country who has biggest difference between their summer and winter gold medal counts.
• Return country name.

Question - 5:

Write a function to update the dataframe to include a new column called "Points" for Games which is a weighted value where each gold medal counts for 3 points, silver medals for 2 points, and bronze medals for 1 point. The function should return only the column (a Series object) which you created.

• Create a function get_points.
• Return dataframe with points column and index.

Question - 6

Write a function to perform k-means clustering.

• Create a fucntion k_means
• return cluster centers