Menambah atau mengurangkan rentang waktu pada datetime

Penggunaan umum rentang waktu adalah menambahkannya atau mengurangkannya dari suatu momen waktu. Misalnya, untuk menghitung waktu satu hari ke depan dari mar_11 (dari latihan sebelumnya), Anda bisa melakukan salah satu dari:

mar_11 + days(1)
mar_11 + ddays(1)

Coba di konsol, Anda akan mendapatkan hasil yang berbeda! Namun, mana yang benar? Itu tergantung tujuan Anda. Jika Anda ingin memperhitungkan bahwa satuan waktu, dalam hal ini hari, dapat memiliki panjang berbeda (misalnya karena daylight saving), gunakan periode days(). Jika Anda ingin waktu tepat 86400 detik ke depan, gunakan durasi ddays().

Dalam latihan ini Anda akan menambah dan mengurangkan rentang waktu dari tanggal dan datetime.

Latihan ini adalah bagian dari kursus

Bekerja dengan Tanggal dan Waktu di R

Petunjuk latihan

Ini hari Senin, 27 Agustus 2018 pukul 14.00 dan Anda ingin mengingatkan diri sendiri pada waktu yang sama minggu depan untuk mengirim email. Tambahkan periode satu minggu ke mon_2pm.
Ini hari Selasa, 28 Agustus 2018 pukul 09.00 dan Anda memulai kode yang biasanya memakan waktu sekitar 81 jam untuk berjalan. Kapan selesai? Tambahkan durasi 81 jam ke tue_9am.
Apa yang Anda lakukan lima tahun lalu? Kurangkan periode 5 tahun dari today().
Kurangkan durasi 5 tahun dari today(). Apakah ini akan menghasilkan tanggal yang berbeda?

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

# Add a period of one week to mon_2pm
mon_2pm <- dmy_hm("27 Aug 2018 14:00")
mon_2pm + ___

# Add a duration of 81 hours to tue_9am
tue_9am <- dmy_hm("28 Aug 2018 9:00")
tue_9am + ___

# Subtract a period of five years from today()
today() - ___

# Subtract a duration of five years from today()
today() - ___

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?Exercise 4: Rentang waktu.Exercise 5: Menambah atau mengurangkan rentang waktu pada datetime

Latihan Saat Ini

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