Time-series data is defined by observations that are ordered in time. Each row (or record) must carry a timestamp showing when the measurement occurred, allowing models to learn temporal patterns such as trends or seasonality. Having a sequential time index distinguishes time-series data from other tabular data. A unique key unrelated to time, the presence of class labels, or normalizing feature values can apply to many data types and do not by themselves make a dataset time-series.
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