Data to information journey

During our initial search for potential data to use, we looked through many different injury reports from different sources. Most of the injury reports were very complex and specific in terms of the injury description and recovery process, which we knew would be too complicated in terms of comparing between leagues. However, we were able to find injury reports that were more broad in terms of type of injury, which we knew would cater more to our goal of comparing trends between leagues. We put the 3 injury reports into an excel sheet and downloaded them as csv files, to which we then downloaded to colab. We decided our main goals to be comparing the amount of injuries in general, the amount of injuries per position, and the amount of different types of injuries between and within leagues. Therefore, we seperated the data into a player list, a position list, and a type list. We then further separated the position list into lists for each position, and further separated the type list into lists for each body part injured. After this, we had the basis of our information ready for visualizations.