Time-Series Data refers to a sequence of data points collected or recorded at specific time intervals. This type of data is often used in various fields, such as finance, economics, and environmental science, to analyze trends over time. For example, daily stock prices or monthly rainfall measurements are common examples of time-series data. Analyzing time-series data helps identify patterns, seasonal variations, and potential future trends. Techniques like moving averages and exponential smoothing are commonly employed to forecast future values based on historical data. Understanding these patterns can assist businesses and researchers in making informed decisions.