Financial markets, weather stations, and fitness trackers all produce data that changes with time. pandas treats time as a main column, not an afterthought. It gives you a clean toolkit to group, smooth, and shift data without clumsy loops. In this chapter you will learn how to build time‑aware indices, summarise high‑frequency data into meaningful chunks, and slide statistical windows across your records to uncover patterns that a single number would miss.