Introduction

The roots of pandas lay in analyzing financial time series data. The author, Wes McKinney, was not satisfied with the available Python tools at that time, and decided to build pandas to support his own needs at the hedge fund he was working at. Broadly speaking, time series are simply points of data gathered over time. Most typically, the time is evenly spaced between each data point. Pandas has excellent functionality with regards to manipulating dates, aggregating over different time periods, sampling different periods of time, and much more.