Extraction, preparation, and analysis of the Ultimate Fighting Championship historical data.
The purpose of this project was to use python for data mining and analysis. The main objective was to perform an exploratory analysis on a historical data-set.
I built a web-scraping Python script that downloads public data from www.ufcstats.com. The raw dataset contains a historical roster of fighters in the UFC, from the year 1993 to present.
Built a script using Python that predicts a fighter's missing value based on their name. Used historical names from the U.S national database www.datagov.org to determine if a fighter belongs to the female or male division based on the relative proportion of males/females. The classifyer attained 96% precision and 70% recall.
A detailed explanation of the analysis can be found in this project's Python jupyter-notebook.