A time series is a dataset in which the first field (the independent variable) is time. In terms of data structures, we can think of it as a map—a set of key-value pairs, where the key is time and the value represents an event that occurred at that time. Usually, the main idea is of a sequence of snapshots of some object changing with time.
Some of the earliest datasets were time series. Figure 3-10 shows a page of Galileo's 1610 notebook, where he recorded his observations of the moons of Jupiter. This is time series data: the time is written on the left, and the changing object is Galileo's sketch of the positions of the moons relative to the planet.
Figure 3-10. Galileo's notes
More modern examples of time series include biometric, weather, seismologic, and market data.
Most time series data are accumulated by automatic processes. Consequently, those datasets tend to be very large, qualifying as big data. This topic is explored in Chapter 11, Big Data Analysis with Java.
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