Pandas for Everyone: Python Data Analysis, First Edition

11. The datetime Data Type

11.1 Introduction

One of the biggest reasons for using Pandas is its ability to work with time-series data. We observed some of this capability earlier, when we concatenated data in Chapter 4 and saw how the indices automatically aligned themselves. This chapter focuses on the more common tasks when working with data that involve dates and times.

Objectives

This chapter will cover:

1. Python’s built-in datetime library

2. Converting strings into a date

3. Formatting dates

4. Extracting date components

5. Performing calculations with dates

6. Working with dates in a DataFrame

7. Resampling

8. Working with time zones

11.2 Python’s datetime Object

Python has a built-in datetime object that is found in the datetime ...