Quanti secondi ci sono in un giorno?

Quanti secondi ci sono in un giorno? In un giorno ci sono 24 ore, in un’ora 60 minuti e in un minuto 60 secondi, quindi dovrebbero essere 24*60*60 = 86400 secondi, giusto?

Non sempre! In questo esercizio vedrai un controesempio: riesci a capire cosa sta succedendo?

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Lavorare con date e orari in R

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Istruzioni dell'esercizio

Nel tuo script abbiamo già inserito il codice per definire tre orari: mezzogiorno dell’11 marzo, del 12 marzo e del 13 marzo 2017 nel fuso orario US Pacific.

Trova la differenza di tempo tra mar_13 e mar_12 in secondi. Dovrebbe confermare la tua intuizione.
Ora trova la differenza di tempo tra mar_12 e mar_11 in secondi. Sorpreso?

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# 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 = ___)

Modifica ed esegui il codice

Questo esercizio fa parte del corso

Lavorare con date e orari in R

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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: Calcolare le differenze tra datetime Exercise 2: Da quanto tempo?Exercise 3: Quanti secondi ci sono in un giorno?

Esercizio in corso

Exercise 4: Intervalli di tempo.Exercise 5: Aggiungere o sottrarre un intervallo di tempo a una data e ora Exercise 6: Duration o Period?Exercise 7: Aritmetica con gli intervalli di tempo Exercise 8: Generare sequenze di date e orari Exercise 9: Il difficile dei mesi Exercise 10: Intervalli Exercise 11: Esaminare gli intervalli. Regni di re e regine Exercise 12: Confrontare intervalli e datetime Exercise 13: Conversione in duration e 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