Imagine you have just received a dataset from a colleague or downloaded it from a public source. You open it and find columns that don’t line up, missing entries, odd symbols, and the same information scattered across multiple files. Before you can make any sense of the numbers, you need to get the data into a clean, trustworthy shape. That is exactly what this chapter is about — the process of turning raw, messy data into a reliable foundation for analysis.