Merging tables of different length by common columns R
r
Solution
This a simple case for `merge` with `all = TRUE`
assuming your data are in `data1` and `data2`
then
merge(data1, data2, all = TRUE)
should work.
If you want to specify what is being merged by (in case there are common columns that you do not want use)
merge(data1, data2, all = TRUE, by = c('season', 'client.ID'))
Problem
I've got two tables of different length and I need to merge them by two common columns (season and client), and fill cells with NAs when there isn't common elements. Below I'm showing a small fraction of the two original tables and the final table that I need. I've tried many things with no success. ``` season client.ID qtty 1998 13 30 1999 13 30 2000 13 29 1998 28 18 1999 28 18 2000 28 18 1998 35 21 1999 35 21 2000 35 21 season client.ID vessel.ID overLength 1998 28 29 17.1 1998 28 1809 4.26 1998 28 2215 9.45 1998 28 4173 5.8 1998 28 8151 4.5 1999 28 29 17.1 1999 28 1809 4.26 1999 28 2215 9.45 1999 28 4173 5.8 1999 28 8151 4.5 2000 28 29 17.1 2000 28 1809 4.26 2000 28 2215 9.45 2000 28 4173 5.8 2000 28 8151 4.5 1998 35 36 9.91 1999 35 36 9.91 2000 35 36 9.91 1998 35 40 9.91 1999 35 40 9.91 2000 35 40 9.91 season client.ID vessel.ID overLength qtty 1998 13 NA NA 30 1999 13 NA NA 30 2000 13 NA NA 29 1998 28 29 17.1 18 1998 28 1809 4.26 18 1998 28 2215 9.45 18 1998 28 4173 5.8 18 1998 28 8151 4.5 18 1999 28 29 17.1 18 1999 28 1809 4.26 18 1999 28 2215 9.45 18 1999 28 4173 5.8 18 1999 28 8151 4.5 18 2000 28 29 17.1 18 2000 28 1809 4.26 18 2000 28 2215 9.45 18 2000 28 4173 5.8 18 2000 28 8151 4.5 18 1998 35 36 9.91 21 1999 35 36 9.91 21 2000 35 36 9.91 21 1998 35 40 9.91 21 1999 35 40 9.91 21 2000 35 40 9.91 21 ```