Taking differences of datetimes

1. Taking differences of datetimes

In this chapter you'll learn about arithmetic with datetimes.

2. Arithmetic for datetimes

What kind of arithmetic might you want to do with datetimes? You might want to subtract dates from each other to calculate the distances between, or you might want to add a timespan - something like a day, a week or two years - to a datetime to generate a new datetime, or you may even want to divide one timespan by another, to work out for example, how many weeks are in a certain interval. In this video, you'll revisit the subtraction of dates, before learning more about lubridate's special objects for handling time spans in later videos.

3. Subtraction of datetimes

Back in Chapter 1 you saw you could subtract one datetime from another to calculate the time between them. For example, the difference between the latest release of R, and the current date provided by Sys (dot) date. Behind the scenes it is the function difftime that is doing this calculation, and using difftime explicitly can give you more control over the results. To use difftime you simply pass in the two times that you want the difference for, and you will get the same result as using subtraction.

4. difftime()

The additional control comes from the units argument to difftime, which specifies the time unit for the difference. You can specify any one of secs, mins, hours, days or weeks. So, we can easily obtain the same time difference in seconds or weeks. If you don't specify the units argument, difftime will attempt to pick the units for you. Since, this may or may not be the units you expect it's good practice to explicitly set the units argument.

5. now() and today()

A particularly common task is to find out how long it's been since some event: perhaps how long since you ran an important report, or how long since the last update to your data. To do that you need today's date or datetime. lubridate provides two functions for just that. today gives you todays date as a Date object, and now gives you this very moment as a POSIXct object, both of which may be useful as one argument to difftime.

6. Let's practice!

OK, time to try this out!

Create Your Free Account

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.

This exercise is part of the course

Working with Dates and Times in R

IntermediateSkill Level

4.8+

Start Course for Free

R doesn't know something is a date or time unless you tell it. In this chapter you'll learn about some of the ways R stores dates and times by exploring how often R versions are released, and how quickly people download them. You'll also get a sneak peek at what you'll learn in the following chapters.

Exercise 1: Introduction to dates Exercise 2: Recognizing ISO 8601 dates Exercise 3: Specifying dates Exercise 4: Automatic import Exercise 5: Why use dates?Exercise 6: Plotting Exercise 7: Arithmetic and logical operators Exercise 8: What about times?Exercise 9: Getting datetimes into R Exercise 10: Datetimes behave nicely too Exercise 11: Why lubridate?

Dates and times come in a huge assortment of formats, so your first hurdle is often to parse the format you have into an R datetime. This chapter teaches you to import dates and times with the lubridate package. You'll also learn how to extract parts of a datetime. You'll practice by exploring the weather in R's birthplace, Auckland NZ.

Exercise 1: Parsing dates with lubridate Exercise 2: Selecting the right parsing function Exercise 3: Specifying an order with `parse_date_time()`Exercise 4: Weather in Auckland Exercise 5: Import daily weather data Exercise 6: Import hourly weather data Exercise 7: Extracting parts of a datetime Exercise 8: What can you extract?Exercise 9: Adding useful labels Exercise 10: Extracting for plotting Exercise 11: Extracting for filtering and summarizing Exercise 12: Rounding datetimes Exercise 13: Practice rounding Exercise 14: Rounding with the weather data

Getting datetimes into R is just the first step. Now that you know how to parse datetimes, you need to learn how to do calculations with them. In this chapter, you'll learn the different ways of representing spans of time with lubridate and how to leverage them to do arithmetic on datetimes. By the end of the chapter, you'll have calculated how long it's been since the first man stepped on the moon, generated sequences of dates to help schedule reminders, calculated when an eclipse occurs, and explored the reigns of monarch's of England (and which ones might have seen Halley's comet!).

Exercise 1: Taking differences of datetimes

Current Exercise

Exercise 2: How long has it been?Exercise 3: How many seconds are in a day?Exercise 4: Time spans.Exercise 5: Adding or subtracting a time span to a datetime Exercise 6: Duration or Period?Exercise 7: Arithmetic with timespans Exercise 8: Generating sequences of datetimes Exercise 9: The tricky thing about months Exercise 10: Intervals Exercise 11: Examining intervals. Reigns of kings and queens Exercise 12: Comparing intervals and datetimes Exercise 13: Converting to durations and periods

You now know most of what you need to tackle data that includes dates and times, but there are a few other problems you might encounter in practice. In this final chapter you'll learn a little more about these problems by returning to some of the earlier data examples and learning how to handle time zones, deal with times when you don't care about dates, parse dates quickly, and output dates and times.

Exercise 1: Time zones Exercise 2: Setting the timezone Exercise 3: Viewing in a timezone Exercise 4: Timezones in the weather data Exercise 5: Times without dates Exercise 6: More on importing and exporting datetimes Exercise 7: Fast parsing with fasttime Exercise 8: Fast parsing with lubridate::fast_strptime Exercise 9: Outputting pretty dates and times Exercise 10: Wrap-up