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Garrett 2016-04-21 13:29:05 -04:00
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datetimes.Rmd
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---
output: pdf_document
---
# Dates and times
This chapter will show you how to work with dates and times in R. Dates and times follow their own rules, which can make working with them difficult. For example dates and times are ordered, like numbers; but the timeline is not as orderly as the numberline. The timeline repeats itself, and has noticeable gaps due to Daylight Savings Time, leap years, and leap seconds. Datetimes also rely on ambiguous units: How long is a month? How long is a year? Time zones give you another head ache when you work with dates and times. The same instant of time will have different "names" in different time zones.
This chapter will show you how to work with dates and times in R. Dates and times follow their own rules, which can make working with them difficult. For example dates and times are ordered, like numbers; but the timeline is not as orderly as the numberline. The timeline repeats itself, and has noticeable gaps due to Daylight Savings Time, leap years, and leap seconds. Datetimes also rely on ambiguous units: How long is a month? How long is a year? Time zones give you another headache when you work with dates and times. The same instant of time will have different "names" in different time zones.
This chapter will focus on R's __lubridate__ package, which makes it much easier to work with dates and times in R. You'll learn the basic date time structures in R and the lubridate functions that make working with them easy. We will also rely on some of the packages that you already know how to use, so load this entire set of packages to begin:
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Let's instead group flights by day of the week, to see which week days are the busiest, and by hour to see which times of the day are busiest. To do this we will need to extract the day of the week and hour that each flight was scheduled to depart.
You can extract the year, month, day of the year (yday), day of the month (mday), day of the week (wday), hour, minute, second, and timezone (tz) of any date or datetime with lubridate's accessor functions. Use the function that has the name of the unit you wish to extract. Accessor function names are singular, period function names are plural.
You can extract the year, month, day of the year (yday), day of the month (mday), day of the week (wday), hour, minute, second, and time zone (tz) of any date or datetime with lubridate's accessor functions. Use the function that has the name of the unit you wish to extract. Accessor function names are singular, period function names are plural.
```{r}
(datetime <- ymd_hms("2007-08-09 12:34:56", tz = "America/Los_Angeles"))
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```{r include = FALSE}
# TIME ZONES and DAYLIGHT SAVINGS
# How long was each flight scheduled to be?
# First convert scheduled times to NYC timezone
# First convert scheduled times to NYC time zone
datetimes2 <- airports %>%
select(faa, name, tz, dst) %>%
right_join(datetimes, by = c("faa" = "dest")) %>%
@ -579,7 +576,7 @@ datetimes2 %>%
## Intervals of time
An interval of time is a specific period of time, such as midnight April 13, 2013 to midnight April 23, 2013. You can make an interval of time with lubridate's `interval()` function. Pass it the start and end datetimes of the interval. Use the tzone argument to select a timezone to display the interval in (if you wish to display the interval in a different time zone than that of the start date).
An interval of time is a specific period of time, such as midnight April 13, 2013 to midnight April 23, 2013. You can make an interval of time with lubridate's `interval()` function. Pass it the start and end datetimes of the interval. Use the tzone argument to select a time zone to display the interval in (if you wish to display the interval in a different time zone than that of the start date).
```{r}