Time Series Data Introduction

Time-series data is data that includes timestamps and is captured over some time, usually as a sequential set of data points. Time series modeling involves analyzing this data and predicting future values to derive patterns and trends using machine learning models.

Time-series data is the sequential data captured over a certain period, often at evenly spaced intervals — for example, the weather of a region over a month, and stock market data over a week.

Some examples of time series data are:

• Data in the automated stock trading industry, such as stock prices recorded at minute intervals to analyze market trends and execute trades.
• Data explaining people's wages, such as monthly wage records to analyze trends and changes in income levels.