Doing a “fuzzyjoin” (and non-fuzzyjoin) in combination with a merge in data.table

Question

I am using multiple databases. For each of these databases I have created a key called matchcode. This matchcode is a combination of a country code and

Answer 1

Hope this works for you:

dfA[, yearA := year]

res1 <- dfA[dfB, on = .(iso, year), roll = 1, nomatch = 0]
res2 <- dfA[dfB, on = .(iso, year), roll = -1, nomatch = 0]
res <- rbind(res1, res2[yearA > year])
setnames(res, c('year', 'matchcode', 'i.matchcode'), c('yearB', 'matchcodeA', 'matchcodeB'))

#    A B C D E F G iso yearB matchcodeA yearA K L M N O P Q matchcodeB
# 1: 1 0 0 0 1 0 1 NLD  2014    NLD2014  2014 1 0 0 0 1 0 1    NLD2014
# 2: 0 0 0 1 1 0 0 AUS  2011    AUS2010  2010 0 0 0 1 1 0 0    AUS2011
# 3: 1 0 1 0 0 1 0 AUS  2007    AUS2006  2006 1 0 1 0 0 1 0    AUS2007
# 4: 0 0 1 0 0 0 1 USA  2011    USA2010  2010 0 0 1 0 0 0 1    USA2010
# 5: 0 1 0 1 0 0 0 USA  2013    USA2012  2012 0 1 0 1 0 0 0    USA2013
# 6: 0 1 0 1 1 0 1 BEL  2009    BEL2008  2008 0 1 0 1 1 0 1    BEL2009
# 7: 0 1 1 1 0 1 0 NLD  2009    NLD2010  2010 0 1 1 1 0 1 0    NLD2009
# 8: 0 1 0 1 0 1 1 USA  2007    USA2008  2008 0 1 0 1 0 1 1    USA2007
# 9: 0 1 0 1 0 0 0 USA  2011    USA2012  2012 0 0 1 0 0 0 1    USA2010
# 10: 1 0 1 0 0 1 0 BLG  2007    BLG2008  2008 1 0 1 0 0 1 0    BLG2007
# 11: 1 0 1 0 0 1 0 BEL  2009    BEL2010  2010 0 1 0 1 1 0 1    BEL2009