This week, I began exploring the Washington Post police shootings dataset for our first project. My focus was on understanding the structure, identifying missing or inconsistent values, and familiarizing myself with key variables. Early on, I noticed inconsistent entries in fields like “weapon type” and “fleeing status.” To prepare for deeper analysis, I standardized these variables and filtered the data to include only Black and White individuals. I also reviewed the column data types and made sure categorical and numerical values were properly formatted. These initial cleaning steps laid the groundwork for my statistical analysis. As I cleaned the dataset, I started thinking about questions related to age, race, and potential disparities in how police shootings affect different groups. I documented these points as a foundation for hypothesis testing in later stages of the project.