Chapter 6: Working with Date and Time in Python
At the core of time-series data is time. Time-series data is a sequence of observations or data points captured in successive order. In the context of a DataFrame, time-series data has an ordered index type DatetimeIndex as you have seen in earlier chapters.
Being familiar with manipulating date and time in time-series data is an essential component of time series analysis and modeling. In this chapter, you will find recipes for common scenarios when working with date and time in time-series data.
Python has several built-in modules for working with date and time, such as the datetime, time, calendar, and zoneinfo modules. Additionally, there are other popular libraries in Python that further extend the capability to work with and manipulate date and time, such as dateutil, pytz, and arrow, to name a few.
You will be introduced to the datetime module in this chapter but then transition to use pandas for enhanced and more complex...
