R loop to calculate date intervals - r

Question

I have a dataframe (customer) that looks like this:
email order_no date
a#stack.com 0012 2014-02-13
a#stack.com 0013 2014-03-13
a#stack.com 0014 2014-06-13
b#stack.com 0015 2014-05-13
b#stack.com 0016 2014-05-20
b#stack.com 0017 2014-07-20
I want to create a new field that appends the interval between orders for each customer. The first step would be to order by date ascending:
customer <- arrange(customer, date)
The next step would be to iterate through each customer and calculate the order interval so the result set looks like this:
email order_no date days_interval
a#stack.com 0012 2014-02-13 0
a#stack.com 0013 2014-03-13 30
a#stack.com 0014 2014-06-13 90
b#stack.com 0015 2014-05-13 0
b#stack.com 0016 2014-05-20 7
b#stack.com 0017 2014-07-20 60
Can this be achieved without using a for loop?
What's the most efficient way of doing this.
With a FOR Loop, this is what you do:
for (i in 2:nrow(customer)){
if(customer$email[i]==customer$email[i-1]){
customer$interval[i] <- as.integer(difftime(customer$date[i],customer$date[i-1]))
}
}
Is this feasible without using a for loop?

Answer 1

diff should work for you. It takes a vector of length n and returns a vector of length n-1 with the differences between the vector's items. Below is an example.
> data <- data.frame(name=c("jeff","steve","jim"),date=today()+seq(-3:-5))
> data
name date
1 jeff 2015-04-28
2 steve 2015-04-29
3 jim 2015-04-30
> diff(data$date)
Time differences in days
[1] 1 1
You just need to combine this with your current work. Such as with
customer$days_interval <- c(0, diff(customer$date))

Answer 2

Here's what I'd do, using dplyr and lubridate:
library(dplyr)
library(lubridate)
df %>%
group_by(email) %>%
mutate(date = ymd(date)) %>%
arrange(date) %>%
mutate(days_interval = difftime(date, lag(date), unit="days"))
Here's what I get:
email order_no date days_interval
1 a#stack.com 12 2014-02-13 NA days
2 a#stack.com 13 2014-03-13 28 days
3 a#stack.com 14 2014-06-13 92 days
4 b#stack.com 15 2014-05-13 NA days
5 b#stack.com 16 2014-05-20 7 days
6 b#stack.com 17 2014-07-20 61 days