Ada berapa detik dalam satu hari?

Ada berapa detik dalam satu hari? Ada 24 jam dalam sehari, 60 menit dalam sejam, dan 60 detik dalam semenit, jadi seharusnya ada 24*60*60 = 86400 detik, bukan?

Tidak selalu! Pada latihan ini Anda akan melihat contoh tandingan. Dapatkah Anda memahami apa yang terjadi?

Latihan ini adalah bagian dari kursus

Bekerja dengan Tanggal dan Waktu di R

Petunjuk latihan

Kami telah menyiapkan kode untuk mendefinisikan tiga waktu dalam skrip Anda—tengah hari pada 11 Maret, 12 Maret, dan 13 Maret tahun 2017 di zona waktu US Pacific.

Cari selisih waktu antara mar_13 dan mar_12 dalam detik. Ini seharusnya sesuai dengan intuisi Anda.
Sekarang, cari selisih waktu antara mar_12 dan mar_11 dalam detik. Terkejut?

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

# Three dates
mar_11 <- ymd_hms("2017-03-11 12:00:00", 
  tz = "America/Los_Angeles")
mar_12 <- ymd_hms("2017-03-12 12:00:00", 
  tz = "America/Los_Angeles")
mar_13 <- ymd_hms("2017-03-13 12:00:00", 
  tz = "America/Los_Angeles")

# Difference between mar_13 and mar_12 in seconds
difftime(___, ___, units = ___)

# Difference between mar_12 and mar_11 in seconds
difftime(___, ___, units = ___)

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: 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: Mengambil selisih dari datetime Exercise 2: Sudah berapa lama?Exercise 3: Ada berapa detik dalam satu hari?

Latihan Saat Ini

Exercise 4: Rentang waktu.Exercise 5: Menambah atau mengurangkan rentang waktu pada datetime Exercise 6: Duration atau Period?Exercise 7: Aritmetika dengan rentang waktu Exercise 8: Membuat deret datetime Exercise 9: Hal yang rumit tentang bulan Exercise 10: Interval Exercise 11: Menguji interval. Masa kekuasaan raja dan ratu Exercise 12: Membandingkan interval dan datetime Exercise 13: Mengonversi ke duration dan period

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