这个问题是我觉得我以一种不清楚的方式提出的先前问题的改编。我正在检查列V1和V2是否按行有共同的代码。代码由正斜杠" /"分隔。下面的函数应该从V1获取一个单元格,在同一行上从V2获取一个单元格,并将其转换为向量。向量的每个元素都是一个代码。然后该函数应检查所获得的两个向量是否具有共同的元素。这些元素最初是4位代码。如果在两个向量之间存在任何匹配的4位代码,则该函数应返回4.如果没有共同的元素,则该函数应减少每个代码的位数,然后再次检查。每次该函数减少位数时,它也会减少最后返回的分数。我希望函数返回的值写在我选择的列中。
这是我的首发条件
structure(list(ID = c(2630611040, 2696102020, 2696526020), V1 = c("7371/3728",
"2834/2833/2836/5122/8731", "3533/3541/3545/5084"), V2 = c("7379",
"3841", "3533/3532/3531/1389/8711")), .Names = c("ID", "V1",
"V2"), class = "data.frame", row.names = c(NA, 3L))
ID V1 V2
1 2630611040 7371/3728 7379
2 2696102020 2834/2833/2836/5122/8731 3841
3 2696526020 3533/3541/3545/5084 3533/3532/3531/1389/8711
我想得到这个
ID V1 V2 V3
1 2630611040 7371/3728 7379 3
2 2696102020 2834/2833/2836/5122/8731 3841 0
3 2696526020 3533/3541/3545/5084 3533/3532/3531/1389/8711 4
我的功能是这个
coderelat<-function(a, b){
a<-unique(as.integer(unlist(str_split(a, "/")))) #Transforming cells into vectors of codes
b<-unique(as.integer(unlist(str_split(b, "/"))))
a<-a[!is.na(a)]
b<-b[!is.na(b)]
if (length(a)==0 | length(b)==0) { # Check that both cells are not empty
ir=NA
return(ir)
} else {
for (i in 3:1){
diff<-intersect(a, b) # See how many products the shops have in common
if (length(diff)!=0) { #As you find a commonality, give ir the corresponding scoring
ir=i+1
break
} else if (i==1 & length(diff)==0) { #If in the last cycle, there is still no commonality put ir=0
ir=0
break
} else { # If there is no commonality and you are not in the last cycle, reduce the nr. of digits and re-check commonality again
a<- unique(as.integer(substr(as.character(a), 1, i)))
b<- unique(as.integer(substr(as.character(b), 1, i)))
}
}
}
return(ir)
}
当我手动提供单个单元格时,该功能有效。但是当我写这样的东西时,它并没有起作用:
df$V4<-coderelat(df$V1, df$V2)
我真的很感激任何帮助,因为我不知道如何使这项工作。
非常感谢提前。 的Riccardo
答案 0 :(得分:3)
这是使用data.tables的解决方案。
get.match <-function(a,b) {
A <- unique(strsplit(a,"/",fixed=TRUE)[[1]])
B <- unique(strsplit(b,"/",fixed=TRUE)[[1]])
for (i in 4:1) if(length(intersect(substr(A,1,i),substr(B,1,i)))>0) return(i)
return(0L)
}
library(data.table)
setDT(df)[,V3:=get.match(V1,V2),by=ID]
df
# ID V1 V2 V3
# 1: 2630611040 7371/3728 7379 3
# 2: 2696102020 2834/2833/2836/5122/8731 3841 0
# 3: 2696526020 3533/3541/3545/5084 3533/3532/3531/1389/8711 4