CODEWITHSUNDEEP
r
Mnifldz
Mnifldz

Reputation: 155

Avoiding a for loop in R

Suppose I have two distinct data sets Data1 and Data2. For each entry in Data1$Incidents I want to find the rows in Data2$Incidents which match it, and also keep track of entries which have no matches. I subsequently save the entries which match into a new data frame Data1_Matches. Now for each entry in Data2$Incidents I look for the entries in Data1_Matches$Incidents which match, and then create an analogous data frame Data2_Matches.

Suppose for the sake of argument my data sets look like the following:

Day    Incidents
"Monday"    30
"Friday"    11
"Sunday"    27

My algorithm at the moment looks like the following:

Data1_Incs = as.integer(Data1$Incidents)
LEN1     = length(Data1_Incs)
No_Match = 0

for (k in 1:LEN1){
  Incs = which(Data2$Incidents == Data1_Incs[k])
  if (length(Incs) == 0){
    No_Match = c(No_Match,k)
  }
}
No_Match = No_Match[-1]

Data1_Match    <- Data1[-No_Match,]
Data1_No_Match <- Data1[ No_Match,]

Data2_Incs = Data2$Incidents
LEN2       = length(Data2_Incs)
Un_Match   = 0

for (j in 1:LEN2){
  Incs = which(as.integer(Data1_Match$Incidents) == Data2_Incs[j])
  if (length(Incs) == 0){
    Un_Match = c(Un_Match, j)
  }
}
Un_Match = Un_Match[-1]

Data2_Match    <- Data2[-Un_Match,]
Data2_No_Match <- Data2[ Un_Match,]

What is a better way for me to accomplish this task, without using a for loop? For reference Data1 has about 15,000 entries while Data2 has closer to two million.

Upvotes: 3

Views: 82

Answers (1)

Michal
Michal

Reputation: 1895

Try to use setdiff.

I wil demonstrate on the first for loop:

No_Match <- setdiff(unique(Data2$Incidents), unique(Data1$Incidents))

Not sure if this quite satisfies your requirement.

Upvotes: 3

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