In order to prepare data for machine learning models, it must be handled differently and with more care. The employment of a model to predict future values based on previously observed values is known as time series forecasting. Non-stationary data, such as economics, weather, stock prices, and retail sales, are commonly represented as time series. Pandas, a popular Python package, can be used for the majority of this work, and this tutorial will walk you through the process of analysing time-series data with it.