Latihan pembulatan

Seperti yang Anda lihat dalam video, round_date() membulatkan tanggal ke nilai terdekat, floor_date() membulatkan ke bawah, dan ceiling_date() membulatkan ke atas.

Ketiganya menerima argumen unit yang menentukan tingkat ketelitian pembulatan. Anda dapat menentukan "second", "minute", "hour", "day", "week", "month", "bimonth", "quarter", "halfyear", atau "year". Atau, Anda dapat menentukan kelipatan dari satuan tersebut, misalnya "5 years", "3 minutes", dan sebagainya.

Cobalah dengan tanggal-waktu rilis R 3.4.1.

Latihan ini adalah bagian dari kursus

Bekerja dengan Tanggal dan Waktu di R

Petunjuk latihan

Pilih fungsi dan satuan yang tepat untuk membulatkan r_3_4_1 ke bawah ke hari terdekat.
Pilih fungsi dan satuan yang tepat untuk membulatkan r_3_4_1 ke 5 menit terdekat.
Pilih fungsi dan satuan yang tepat untuk membulatkan r_3_4_1 ke atas ke minggu terdekat.
Cari waktu yang telah berlalu pada hari rilis pada saat rilis dengan mengurangkan r_3_4_1 yang dibulatkan ke bawah ke hari dari r_3_4_1.

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

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 = ___)

Edit dan Jalankan Kode

Latihan ini adalah bagian dari kursus

Bekerja dengan Tanggal dan Waktu di R

SkillTag.level.intermediateSkillTag.label

4.8+

Mulai Kursus Gratis

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: Mengurai tanggal dengan lubridate Exercise 2: Memilih fungsi parsing yang tepat Exercise 3: Menentukan urutan dengan `parse_date_time()`Exercise 4: Cuaca di Auckland Exercise 5: Impor data cuaca harian Exercise 6: Impor data cuaca per jam Exercise 7: Mengekstrak bagian dari sebuah datetime Exercise 8: Apa yang dapat Anda ekstrak?Exercise 9: Menambahkan label yang berguna Exercise 10: Ekstraksi untuk pembuatan plot Exercise 11: Mengekstrak untuk pemfilteran dan peringkasan Exercise 12: Membulatkan datetime Exercise 13: Latihan pembulatan

Latihan Saat Ini

Exercise 14: Pembulatan dengan data cuaca

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