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loops - Conditional Counter In New Column - R

I'd like help creating a function or loop that adds a value to a new column based on values in the same row of other columns. The goal is to create a kind of scoring system for a survey dataset.

Here's a sample dataframe

dfp <- data.frame(id=c("resp1", "resp2", "resp3"), 
                 cat1=c("gov", "biz", "biz"), 
                 cat2=c("dem", "gop", "dem"),
                 liberal=c(0,0,0), 
                 conservative=c(0,0,0))

In the above set, I imagine "gov" and "dem" both at 1 point to the liberal column, while "biz" and "gop" add a point each to the conservative column. So, the ideal dataframe would be:

dfp <- data.frame(id=c("resp1", "resp2", "resp3"), 
                 cat1=c("gov", "biz", "biz"), 
                 cat2=c("dem", "gop", "dem"),
                 liberal=c(2,0,1), 
                 conservative=c(0,2,1))

I tried a for loop, but it didn't work.

for (i in length(dfp$liberal)){
  if (dfp[i,][,2] == "gov"){
    dfp[i,]$liberal = dfp[i,]$liberal + 1
  }
  if (dfp[i,][,3]=="gop"){
    dfp[i,]$conservative = dfp[i,]$conservative + 1
  }
}

If i get rid of the "i" iterator, the loop correctly adds the number liberal and conservative, but it adds it uniformly to all the rows.

thanks for any help and let me know if i can make this question any clearer. I'm a little new to loops, do if you also happen to have a function that would help me diagnose what i'm doing wrong, feel free to add to your explanation. thanks so much.

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1 Answer

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by (71.8m points)

You do not even need the "for" loop. Try

dfp <- data.frame(id=c("resp1", "resp2", "resp3"), 
              cat1=c("gov", "biz", "biz"), 
              cat2=c("dem", "gop", "dem"))

dfp$liberal = as.numeric(dfp$cat1=="gov") + as.numeric(dfp$cat2=="dem")

dfp$conservative = as.numeric(dfp$cat1=="biz") + as.numeric(dfp$cat2=="gop")

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