Merging and Averaging Data in R by ID and Date - r

Question

I have two datasets that I would like to merge together in an unusual way. One dataset is my master set that contains an identifier and a datetime relevant to that ID. An ID can appear multiple times with different dates attached to it:
> head(Master_Data)
# A tibble: 5 x 2
ID Date
<chr> <dttm>
1 a 2018-03-31 00:00:00
2 a 2018-02-28 00:00:00
3 b 2018-06-07 00:00:00
4 c 2018-01-31 00:00:00
5 b 2018-02-09 00:00:00
The other dataset has the same ID, a different date and a score associated with that ID and date. IDs can also show up multiple times in this dataset as well with different dates and scores:
> head(Score_Data)
# A tibble: 6 x 3
ID Date Score
<chr> <dttm> <dbl>
1 a 2018-01-19 00:00:00 3
2 a 2018-01-01 00:00:00 5
3 a 2018-03-05 00:00:00 7
4 b 2018-01-31 00:00:00 1
5 b 2018-08-09 00:00:00 5
6 c 2018-01-17 00:00:00 10
What I would like to do is add an additional column to Master_Data that gives a mean of the score for that ID in the Score_Data df. The tricky part is that for each row in Master_Data, I only want to include scores in the average if the date variable in Score_Data is earlier than the date variable for a given row in Master_Data
Example:
For row 1 in Master_Data, I would want the new column to return a value of (3+5+7)/3 = 5. However, for row 2 I would only want to see (3+5)/2 = 4 since row 3 in Score_Data has a date after 2/28
Thoughts on what would be the best approach here to get this new column in Master_Data?

Answer 1

This solution would work for smaller data sets, but as the size of the data grows you'll start to notice performance issues.
library(lubridate)
library(dplyr)
master_data <- data.frame(
ID = c('a','a','b','c','b'),
Date = c('2018-03-31 00:00:00',
'2018-02-28 00:00:00',
'2018-06-07 00:00:00',
'2018-01-31 00:00:00',
'2018-02-09 00:00:00'))
master_data$Date <- ymd_hms(master_data$Date)
Score_Data <- data.frame(
ID = c('a','a','a','b','b','c'),
Date = c('2018-01-19 00:00:00',
'2018-01-01 00:00:00',
'2018-03-05 00:00:00',
'2018-01-31 00:00:00',
'2018-08-09 00:00:00',
'2018-01-17 00:00:00'),
Score = c(3,5,7,1,5,10))
Score_Data$Date <- ymd_hms(Score_Data$Date)
output <- apply(master_data, 1, function(x){
value <- Score_Data %>%
filter(ID == x[['ID']]) %>%
filter(Date < x[['Date']]) %>%
summarise(Val = mean(Score))
})
master_data$Output <- unlist(output)