Styjun

I have multiple for loops that pull dates from one data frame and match them to specific rows/columns in another data frame. I'm looking for help turning this into a single function or loop.

I've tried nested for loops without any luck.

The loops I have look like this and do what I need them to do:

for(x in id_vector) 
 datafileslist[[x]]$m3start <- rep(dates_df[[x,3]], nrow(datafileslist[[x]]))


for(x in id_vector) 
 datafileslist[[x]]$m3end <- rep(dates_df[[x,4]], nrow(datafileslist[[x]]))


for(x in id_vector) 
 datafileslist[[x]]$m6start <- rep(dates_df[[x,5]], nrow(datafileslist[[x]]))

...and so on. While this works, there is a lot of repetition (I have 16 for loops).

I've tried this instead:

for(x in seq_along(id_vector)) 
 for(z in 3:18) 
 for(y in 20:35) 
 datafileslist[[x]][[y]] <- rep(dates_df[[x,z]], nrow(datafileslist[[x]]))
 
 

But I need matched pairs of z and y to run once in tandem (3, 20; 4, 21; ... 18, 35) through each id, which the above code does not do. Any ideas on how I can do this?

The dates_df looks like this:

id m3start m3end
s01 2016-09-19 2016-12-17
s02 2016-11-03 2017-01-31

There are 60 ids and 16 combos of start/end dates (m3, m6, m9, etc.).

The data files list is a list of data frames, one data frame per id, with 50,000+ observations of around 20 variables for each id. I'm trying to add columns with start and end dates for each date range from the dates_df data frame to the data frame for each id.

The output should look like something like this:

id group m3start m3end m6start
s01 int 2016-09-19 2016-12-17 2018-09-08
s01 int 2016-09-19 2016-12-17 2018-09-08
s01 int 2016-09-19 2016-12-17 2018-09-08

When I run the nested for loops, I get the same dates across m3start, m3end, m6start, m6end, etc.

id group m3start m3end m6start
s01 int 2020-01-12 2020-01-12 2020-01-12
s01 int 2020-01-12 2020-01-12 2020-01-12
s01 int 2020-01-12 2020-01-12 2020-01-12

Consider merge inside an lapply on list of data frames:

new_datafileslist <- lapply(datafileslist, function(df) merge(df, dates_df, by="id"))