R for Data Science, 2nd Edition

Chapter 17. Dates and Times

Introduction

This chapter will show you how to work with dates and times in R. At first glance, dates and times seem simple. You use them all the time in your regular life, and they don’t seem to cause much confusion. However, the more you learn about dates and times, the more complicated they seem to get!

To warm up, think about how many days there are in a year and how many hours there are in a day. You probably remembered that most years have 365 days, but leap years have 366. Do you know the full rule for determining if a year is a leap year?¹ The number of hours in a day is a little less obvious: most days have 24 hours, but in places that use daylight saving time (DST), one day each year has 23 hours and another has 25.

Dates and times are hard because they have to reconcile two physical phenomena (the rotation of Earth and its orbit around the sun) with a whole raft of geopolitical phenomena including months, time zones, and DST. This chapter won’t teach you every last detail about dates and times, but it will give you a solid grounding of practical skills that will help you with common data analysis challenges.

We’ll begin by showing you how to create date-times from various inputs, and then once you’ve got a date-time, you’ll learn how you can extract components such as year, month, and day. We’ll then dive into the tricky topic of working with time spans, which come in a variety of flavors depending on what you’re trying to do. We’ll conclude ...