match - R: Matching by row and column -

i have 2 data frames, below:
equitydata

valuationdate   currency    opening closing 02/01/2003        chf          0    0 02/01/2003        dkk          0    0 03/01/2003        chf          0    0 02/01/2003        sek          0    0 03/01/2003        sek          0    0 04/01/2003        sek          0    0 05/01/2003        chf          0    0 03/01/2003        dkk          0    0 

which contains information trades done each day, in different currencies , historicalfx

date        chf        x      dkk     x.1     sek    x.2 02/01/2003  0.6885  0.688   0.1347  0.1346  0.1094  0.1096 03/01/2003  0.688   0.6858  0.1346  0.1345  0.1096  0.1099 04/01/2003  0.6858  0.6858  0.1345  0.1345  0.1099  0.1099 05/01/2003  0.6858  0.6858  0.1345  0.1345  0.1099  0.1099 

which contains historical fx rates, opening price below currency ticker, , closing price in column next it.

i trying corresponding fx price in equitydata data frame.

i have tried following, works, inefficient:

 openexchangematch = match(equitydata$currency,colnames(historicalfx))   closeexchangematch = match(equitydata$currency,colnames(historicalfx))+1   datematch = match(equitydata$valuationdate,historicalfx$date)   (i in 1:nrow(equitydata))   {     equitydata$openexchange[i] = historicalfx[datematch[i],openexchangematch[i]]     equitydata$closeexchange[i] = historicalfx[datematch[i],closeexchangematch[i]]   } 

any ideas on how can solve above in better way?

we create row/column index ('indx1') after subsetting second dataset ('df2' i.e. 'historicalfx'), assign 'opening' , 'closing' columns in first dataset ('df1' i.e. 'equitydata') values got using 'indx1' in 'op1' , 'cl1'

op1 <-  df2[-1][c(true, false)] cl1 <-  df2[-1][c(false, true)] names(cl1) <- names(op1) indx1 <- cbind(match(df1$valuationdate, df2$date),               match(df1$currency, names(op1))) df1$opening <- op1[indx1] df1$closing <- cl1[indx1] df1 #  valuationdate currency opening closing #1    02/01/2003      chf  0.6885  0.6880 #2    02/01/2003      dkk  0.1347  0.1346 #3    03/01/2003      chf  0.6880  0.6858 #4    02/01/2003      sek  0.1094  0.1096 #5    03/01/2003      sek  0.1096  0.1099 #6    04/01/2003      sek  0.1099  0.1099 #7    05/01/2003      chf  0.6858  0.6858 #8    03/01/2003      dkk  0.1346  0.1345 

data

df1 <- structure(list(valuationdate = c("02/01/2003", "02/01/2003",  "03/01/2003", "02/01/2003", "03/01/2003", "04/01/2003", "05/01/2003",  "03/01/2003"), currency = c("chf", "dkk", "chf", "sek", "sek",  "sek", "chf", "dkk"), opening = c(0l, 0l, 0l, 0l, 0l, 0l, 0l,  0l), closing = c(0l, 0l, 0l, 0l, 0l, 0l, 0l, 0l)), .names = c("valuationdate",  "currency", "opening", "closing"), class = "data.frame", row.names = c(na,  -8l))   df2 <- structure(list(date = c("02/01/2003", "03/01/2003", "04/01/2003",  "05/01/2003"), chf = c(0.6885, 0.688, 0.6858, 0.6858), x = c(0.688,  0.6858, 0.6858, 0.6858), dkk = c(0.1347, 0.1346, 0.1345, 0.1345 ), x.1 = c(0.1346, 0.1345, 0.1345, 0.1345), sek = c(0.1094, 0.1096,  0.1099, 0.1099), x.2 = c(0.1096, 0.1099, 0.1099, 0.1099)), .names = c("date",  "chf", "x", "dkk", "x.1", "sek", "x.2"), class = "data.frame", row.names = c(na,  -4l))