Lookup value from multiple sets of columns - r

Question

This is kind of VOOLKUP problem in excel. I have a data set like the following.
dat1 <- read.table(header=TRUE, text="
ID Name1 Name2
1384 Rem_Ps Tel_Nm
1442 Teq_Ls Sel_Nm
1340 Fem_Bs Tem_Mn
1419 Few_Bn Ten_Gf
1359 Fem_Bs Tem_Mn
1237 Qwl_Po Mnt_Pj
1288 Tem_na Tem_Rt
1261 Sem_Na Tel_Tr
1382 Rem_Ps Tel_Nm
1316 Fem_Bs Tem_Mn
1279 Sem_Na Yem_Rt
1366 Sel_Ve Mkl_Po
1269 Rem_Ps Tel_Nm
")
dat1
ID Name1 Name2
1 1384 Rem_Ps Tel_Nm
2 1442 Teq_Ls Sel_Nm
3 1340 Fem_Bs Tem_Mn
4 1419 Few_Bn Ten_Gf
5 1359 Fem_Bs Tem_Mn
6 1237 Qwl_Po Mnt_Pj
7 1288 Tem_na Tem_Rt
8 1261 Sem_Na Tel_Tr
9 1382 Rem_Ps Tel_Nm
10 1316 Fem_Bs Tem_Mn
11 1279 Sem_Na Yem_Rt
12 1366 Sel_Ve Mkl_Po
13 1269 Rem_Ps Tel_Nm
The above dataset would lookup value from the following data set. Both of the lookup values Name1 and Name2 would use dat2 seven columns QC1 to NC3 to lookup the values. More clarification: If Name1 is found from the seven columns and Name2 is also found in the seven columns, only then we will consider the option as valid. For example: the second row has two values Teq_ls and Sel_Nm. As Teq_ls is not found the seven columns, we will toss this row.
dat2 <- read.table(header=TRUE, text="
ID1 REQ REM QC1 QC2 QC3 QC4 NC1 NC2 NC3
AB1 1123 44ed Fem_Bs Ten_Gf NA NA Tem_Mn Tem_Mn NA
AB2 123 331s Tem_Rt Qwl_Po NA Ten_Gf NA Tem_Mn Mnt_Pj
AB3 123 334q Ten_Gf Tem_Mn Sem_Na Tem-Mn Tel_Tr NA NA
AB4 1234 33ey Sem_Na NA NA NA Tem_Rt NA Yem_Rt
AB5 13243 ed43 Rem_Ps NA NA Tem_Mn NA Tel_Nm NA
AB6 123 34rt NA Ten_Gf NA Sel_Ve Mkl_Po Tem_Rt NA
")
dat2
ID1 REQ REM QC1 QC2 QC3 QC4 NC1 NC2 NC3
1 AB1 1123 44ed Fem_Bs Ten_Gf <NA> <NA> Tem_Mn Tem_Mn <NA>
2 AB2 123 331s Tem_Rt Qwl_Po <NA> Ten_Gf <NA> Tem_Mn Mnt_Pj
3 AB3 123 334q Ten_Gf Tem_Mn Sem_Na Tem-Mn Tel_Tr <NA> <NA>
4 AB4 1234 33ey Sem_Na <NA> <NA> <NA> Tem_Rt <NA> Yem_Rt
5 AB5 13243 ed43 Rem_Ps <NA> <NA> Tem_Mn <NA> Tel_Nm <NA>
6 AB6 123 34rt <NA> Ten_Gf <NA> Sel_Ve Mkl_Po Tem_Rt <NA>
The result would be like this.
ID Name1 Name2 ID1 REQ REM
1384 Rem_Ps Tel_Nm AB5 13243 ed43
1340 Fem_Bs Tem_Mn AB1 1123 44ed
1359 Fem_Bs Tem_Mn AB1 1123 44ed
1237 Qwl_Po Mnt_Pj AB2 123 331s
1261 Sem_Na Tel_Tr AB3 123 334q
1382 Rem_Ps Tel_Nm AB5 13243 ed43
1316 Fem_Bs Tem_Mn AB1 1123 44ed
1279 Sem_Na Yem_Rt AB4 1234 33ey
1366 Sel_Ve Mkl_Po AB6 123 34rt
1269 Rem_Ps Tel_Nm AB5 13243 ed43

Answer 1

Let's do it in base:
z <- which(apply(dat1, 1, function(x) apply(dat2, 1, function(z) x[[2]] %in% z & x[[3]] %in% z)), arr.ind = TRUE)
cbind(dat1[z[,2],], dat2[z[,1],])
ID Name1 Name2 ID1 REQ REM QC1 QC2 QC3 QC4 NC1 NC2 NC3
1 1384 Rem_Ps Tel_Nm AB5 13243 ed43 Rem_Ps <NA> <NA> Tem_Mn <NA> Tel_Nm <NA>
3 1340 Fem_Bs Tem_Mn AB1 1123 44ed Fem_Bs Ten_Gf <NA> <NA> Tem_Mn Tem_Mn <NA>
5 1359 Fem_Bs Tem_Mn AB1 1123 44ed Fem_Bs Ten_Gf <NA> <NA> Tem_Mn Tem_Mn <NA>
6 1237 Qwl_Po Mnt_Pj AB2 123 331s Tem_Rt Qwl_Po <NA> Ten_Gf <NA> Tem_Mn Mnt_Pj
8 1261 Sem_Na Tel_Tr AB3 123 334q Ten_Gf Tem_Mn Sem_Na Tem-Mn Tel_Tr <NA> <NA>
9 1382 Rem_Ps Tel_Nm AB5 13243 ed43 Rem_Ps <NA> <NA> Tem_Mn <NA> Tel_Nm <NA>
10 1316 Fem_Bs Tem_Mn AB1 1123 44ed Fem_Bs Ten_Gf <NA> <NA> Tem_Mn Tem_Mn <NA>
11 1279 Sem_Na Yem_Rt AB4 1234 33ey Sem_Na <NA> <NA> <NA> Tem_Rt <NA> Yem_Rt
12 1366 Sel_Ve Mkl_Po AB6 123 34rt <NA> Ten_Gf <NA> Sel_Ve Mkl_Po Tem_Rt <NA>
13 1269 Rem_Ps Tel_Nm AB5 13243 ed43 Rem_Ps <NA> <NA> Tem_Mn <NA> Tel_Nm <NA>