A time-series is typically a vector (array) of discrete data samples in which each sample is comprised of a time-stamp and a value. Each time-stamp is separated by a constant value typically called the sampling interval, or period and each value is rounded or truncated to the nearest value that can be represented digitally. (See also: sampling rate)

There are a wide variety of uses for time-series data, mostly involving digital signal processing where a signal is any physical quantity that changes with time.

Because digital signal processing deals with discrete time-series data, it is possible for the original signal to have variations which are not described by a simple discrete value. Therefore, sometimes time-series data may come in the form of start, high, low, and end representing the starting value, the highest value, lowest value, and ending value respectively. An example of this is daily end-of-day stock data which has an open, high, low, and close value for the whole day.

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