dplyr: grouping and summarizing/mutating data with rolling time windows

Question

I have irregular timeseries data representing a certain type of transaction for users. Each line of data is timestamped and represents a transaction at that time. By the i

Answer 1

This can be done using SQL:

library(sqldf)

dd <- transform(data, date = as.Date(date))
sqldf("select a.*, count(*) n_trans30, sum(b.n_widgets) 'total_widgets30' 
       from dd a 
       left join dd b on b.date between a.date - 30 and a.date 
                         and b.id = a.id
                         and b.rowid <= a.rowid
       group by a.rowid")

giving:

  id       date n_widgets n_trans30 total_widgets30
1  1 2015-01-01         1         1               1
2  1 2015-01-01         2         2               3
3  1 2015-01-05         3         3               6
4  1 2015-01-25         4         4              10
5  2 2015-05-05         5         1               5
6  2 2015-01-01         2         1               2
7  3 2015-08-01         4         1               4
8  4 2015-01-01         5         1               5