Practice rounding

As you saw in the video, round_date() rounds a date to the nearest value, floor_date() rounds down, and ceiling_date() rounds up.

All three take a unit argument which specifies the resolution of rounding. You can specify "second", "minute", "hour", "day", "week", "month", "bimonth", "quarter", "halfyear", or "year". Or, you can specify any multiple of those units, e.g. "5 years", "3 minutes" etc.

Try them out with the release datetime of R 3.4.1.

Este exercício faz parte do curso

Working with Dates and Times in R

Instruções do exercício

Choose the right function and units to round r_3_4_1 down to the nearest day.
Choose the right function and units to round r_3_4_1 to the nearest 5 minutes.
Choose the right function and units to round r_3_4_1 up to the nearest week.
Find the time elapsed on the day of release at the time of release by subtracting r_3_4_1 rounded down to the day from r_3_4_1.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

r_3_4_1 <- ymd_hms("2016-05-03 07:13:28 UTC")

# Round down to day
___(r_3_4_1, unit = ___)

# Round to nearest 5 minutes
___(r_3_4_1, unit = ___)

# Round up to week 
___(r_3_4_1, unit = ___)

# Subtract r_3_4_1 rounded down to day
r_3_4_1 - ___(r_3_4_1, unit = ___)

Editar e executar o código

Este exercício faz parte do curso

Working with Dates and Times in R

IntermediárioNível de habilidade

4.8+

Iniciar curso de graça

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

Exercício atual

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.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