Time spans.

1. Time spans

Time spans are hard because they don't have a constant meaning. You saw an example in the previous exercise. Even though we say two datetimes are a day apart, that doesn't mean they are exactly 86400 seconds apart. To do addition with datetimes and timespans you need to be specific about what you mean by a time span. For example, to add one day to a datetime, you need to define what you mean by "one day".

2. Time spans in lubridate

lubridate does this by providing two different kinds of time span: periods and durations. Periods are designed to match our human concept of a time span. For example if we take a datetime and add a period of one day, we get the same time the next day, regardless of whether that is 86400 seconds in the future or not. Durations are simply a fixed length of time in seconds, more like how a stopwatch measures time. If we take a datetime and add a duration of one day, we get the datetime 86400 seconds in the future.

3. Creating a time span

To create a period in lubridate you use the function of the appropriate unit in plural form. For example if we want a period of 1 day, we use the days function. Calling days results in a period of one day. The period constructors take a single argument x which by default is 1, but you can specify some other multiple of the time span. A duration is constructed similarly, except the duration functions all start with d. So, to construct a duration of 2 days, you use the ddays function. You'll notice periods and durations print a little differently to help remind you of their meaning.

4. Arithmetic with time spans

Once you have a time span you can multiply it by a number, add it to or subtract it from other time spans, or add it to or subtract it from a datetime.

5. Functions to create time spans

There's a constructor for each unit of time. Just remember they are plural - that is they end in s and that durations are always prefaced with a d.

6. Let's practice!

In the exercises you'll explore how periods and durations differ and how you can use them to generate sequences of datetimes.

This exercise is part of the course

Working with Dates and Times in R

IntermediateSkill Level

4.9+

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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 Exercise 2: How long has it been?Exercise 3: How many seconds are in a day?Exercise 4: Time spans.

Current Exercise

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