The goal of this assignment is to clean and transform a "wide" dataset representing arrival delays for ALASKA and AM WEST airlines across five different cities into a "long” format suitable for comparative analysis. I will be using functions in the Tidyverse R-package to accomplish this goal.

The goal is to compare the chess player’s actual score with their expected score calculated using the ELO rating system’s probability formula. This analysis will then facilitate to classify players who most over performed and those who most underperformed of course relative to their expected score.

In this project, we will manipulate a structured chess tournament file that contains the result of 64 players. Our goal is to extract some meaningful players data including player's name, state, total tournament points, pre-tournament rating, the average pre-tournament rating of all opponents they faced and then export into a clean, relational CSV file.