Python代写 | CS 486 – Machine Learning Fall Lab 01 – ATP World Rankings

CS 486 – Machine Learning Fall
Lab 01 – ATP World Rankings

This collection has been scrapped from the ATP Tour Website. It consists of tennis player (current and
former) and statistical parameters on world no.1 over the last two decades which gives room to draw
meaningful insights.
In this lab, your task is to understand the dataset and determine the best player over the last two
decades. You are expected to use techniques in pandas to manipulate the dataset, visualize it and reach
a conclusion. (Note: There is no expected answer and we would like to understand your perspective while
looking at the dataset.)
The dataset is available on Canvas:
Name: ATP_World_Rankings.csv
Your implementation must:
● Choose your name and accept the assignment. If you do not
see your name, contact the instructor / TA.
● Use a Jupyter notebook or Python script to complete your implementation.
● Read the data, which you may assume is in the same directory as the notebook / script.
● Inspect the dataset to determine the total winning percentage for each player.
● Show visual representation of the number of weeks each player has been at rank 1. (Criteria:
Consider players – Rank. 1 for more than 50 weeks.) (bar plot).
● Show relationship between win percentage and earnings for each player. (scatter plot).
● Using a histogram show distribution of total professional matches (wins + losses) across all
● Show step by step analysis done to reach a conclusion.


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