Random sample by group and filtering on the basis of result - r

Question

I have a dataframe that is generated by the following code
l_ids = c(1, 1, 1, 2, 2, 2, 2)
l_months = c(5, 5, 5, 88, 88, 88, 88)
l_calWeek = c(201708, 201709, 201710, 201741, 201742, 201743, 201744)
value = c(5, 6, 3, 99, 100, 1001, 1002)
dat <- setNames(data.frame(cbind(l_ids, l_months, l_calWeek, value)),
c("ids", "months", "calWeek", "value"))
and looks like this:
+----+-------+----------+-------+
| Id | Month | Cal Week | Value |
+----+-------+----------+-------+
| 1 | 5 | 201708 | 4.5 |
| 1 | 5 | 201709 | 5 |
| 1 | 5 | 201710 | 6 |
| 2 | 88 | 201741 | 75 |
| 2 | 88 | 201742 | 89 |
| 2 | 88 | 201743 | 90 |
| 2 | 88 | 201744 | 51 |
+----+-------+----------+-------+
I would like to randomly sample a calendar week from each id-month group (the months are not calendar months). Then I would like to keep all id-month combination prior to the sample months.
An example output could be: suppose the sampling output returned cal week 201743 for the group id=2 and month=88 and 201709 for the group id=1 and month=5, then the final ouput should be
+----+-------+----------+-------+
| Id | Month | Cal Week | Value |
+----+-------+----------+-------+
| 1 | 5 | 201708 | 4.5 |
| 1 | 5 | 201709 | 5 |
| 2 | 88 | 201741 | 75 |
| 2 | 88 | 201742 | 89 |
2 | 88 | 201743 | 90 |
+----+-------+----------+-------+
I tried to work with dplyr's sample_n function (which is going to give me the random calendar week by id-month group, but then I do not know how to get all calendar weeks prior to that date. Can you help me with this. If possible, I would like to work with dplyr.
Please let me know in case you need further information.
Many thanks

Answer 1

require(dplyr)
set.seed(1) # when sampling please set.seed
sampled <- dat %>% group_by(ids) %>% do(., sample_n(.,1))
sampled_day <- sampled$calWeek
dat %>% group_by(ids) %>%
mutate(max_day = which(calWeek %in% sampled_day)) %>%
filter(row_number() <= max_day)
#You can also just filter directly with row_number() <= which(calWeek %in% sampled_day)
# A tibble: 3 x 4
# Groups: ids [2]
ids months calWeek value
<dbl> <dbl> <dbl> <dbl>
1 1.00 5.00 201708 5.00
2 2.00 88.0 201741 99.0
3 2.00 88.0 201742 100
This depends on the row order! So make sure to arrange by day first. You'll need to think about ties, though. I have edited my previous answer and simply filtered with <=

Answer 2

That should do the trick:
sample_and_get_below <- function(df, when, size){
res <- filter(df, calWeek == when) %>%
sample_n(size)
filter(df, calWeek > when) %>%
rbind(res, .)
}
sample_and_get_below(dat, 201741, 1)
ids months calWeek value
1 2 88 201741 99
2 2 88 201742 100
3 2 88 201743 1001
4 2 88 201744 1002