judegomolina / atp-data-storytelling

Storytelling Project for ATP matches from 2000 to 2016.

ATP Data Storytelling

This is a project dedicated to analyze ATP matches from 2000 to 2016, making focus on some interesting aspects such as:

• The Big 3.
• Wining Probability vs. Ranking Difference.
• The Importance of the First Set.

This dataset was taken from Kaggle and includes a "Metadata.txt" file giving a short description of the features, you can find more information about it in https://www.kaggle.com/jordangoblet/atp-tour-20002016 .

Getting Started

The following steps will let you obtain a functional version of this project in your own machine.

Requirements

The main requirement for running this project in your computer is having Python and Jupyter Notebook installed, you'll also require to install the following Python Libraries:

• Numpy
• Pandas
• Matplotlib
• Seaborn
• Fuzzywuzzy

Installation

After verifying that you meet all the above mentioned requirements you just need to make a clone of this repository in your computer and everything will be set for you to run the project. Remember to make sure that the "ATP Data Storytelling.ipynb" file and the "data.csv" file are in the same directory.

Running the Project

Now that everything is ready you just need to open the "ATP Data Storytelling.ipynb" file and then in Kernel click on "Restart & Run All" just to make sure everything is ok. Finally, you can check every step I went through during the analysis and find out what the conclussions were.