Use dev (soon to be released) lubridate

DESCRIPTION

@@ -39,6 +39,7 @@ Imports:
   viridis
 Remotes:
   hadley/forcats,
+  hadley/lubridate,
   hadley/modelr,
   hadley/stringr,
   hadley/tibble,

datetimes.Rmd

@@ -137,34 +137,27 @@ Or within a single day:
 
 ```{r}
 flights_dt %>% 
-  filter(dep_time < ymd(20130102, tz = "UTC")) %>% 
+  filter(dep_time < ymd(20130102)) %>% 
   ggplot(aes(dep_time)) + 
   geom_freqpoly(binwidth = 600) # 600 s = 10 minutes
 ```
 
-Note the two tricks I needed to create these plots:
-
-1.  When you use date-times in a numeric context (like in a histogram), 1 
-    means 1 second, so a binwidth of 86400 means one day. For dates, 1
-    means 1 day.
-   
-1.  R doesn't like to compare date-times with dates, so you can force
-    `ymd()` to generate a date-time by supplying a `tz` argument.
+Note that when you use date-times in a numeric context (like in a histogram), 1 means 1 second, so a binwidth of 86400 means one day. For dates, 1 means 1 day.
 
 ### From other types
 
 You may want to switch between a date-time and a date. That's the job of `as_datetime()` and `as_date()`:
 
 ```{r}
-# as_datetime(today())
+as_datetime(today())
 as_date(now())
 ```
 
 Sometimes you'll get date/times as numeric offsets from the "Unix Epoch", 1970-01-01. If the offset is in seconds, use `as_datetime()`; if it's in days, use `as_date()`.
 
 ```{r}
-# as_datetime(60 * 60 * 10)
-as_date(365)
+as_datetime(60 * 60 * 10)
+as_date(365 * 10 + 2)
 ```
 
 ### Exercises
@@ -302,7 +295,7 @@ You can use `update()` to show the distribution of flights across the course of
 
 ```{r}
 flights_dt %>% 
-  mutate(dep_hour = update(dep_time, month = 1, day = 1)) %>% 
+  mutate(dep_hour = update(dep_time, yday = 1)) %>% 
   ggplot(aes(dep_hour)) +
     geom_freqpoly(binwidth = 300)
 ```