Time series data is generated by a variety of processes, including the Internet of Things (IoT) sensors, machine/server logs, and monthly sales data from Customer Relationship Management (CRM) system. Some common characteristics of time series data is that the data points are generated at a fixed frequency and that there is an inherent trend and seasonality associated with the data.

In this chapter, we will take a tour of some topics that are necessary to develop expertise in using pandas. Knowledge of these topics is very useful for the preparation of data as input to programs for data analysis, prediction, or visualization.

The topics that we'll discuss in this chapter are as follows:

• Handling time series data and dates
• Manipulation of time series data—rolling, resampling, shifting, lagging, and time element separation
• Formatting—changing the date format and converting text to a date
• Plotting time series using matplotlib

By the end of this chapter, you should be proficient in these critical areas.