Efficiently recoding multiple variables from character to numeric values in R

Question

I am using R (version 3.2.3) to recode multiple variables (in the same dataframe) from character values ("High", "Medium", "Low" and "No Concerns") to numeric values (4,3,2 and 1). I know there are several ways to recode a variable and in my example below have been using the "recode" function in the car package. This works fine when recoding a single variable but when I specify multiple variables (columns 45 to 68) all the values are replaced with "N/A".

df[,c(45:68)] <- recode(df[,c(45:68)],"'High'=4;'Medium'=3;'Low'=2;'No Concerns'=1",as.numeric.result=TRUE)

I would appreciate any pointers on where I might be going wrong here. I'm new to the coding community so please let me know if I have provided enough detail in my question.

Welcome to StackOverflow! With regard to providing enough detail in your question: Please read the info about how to ask a good question and how to give a reproducible example. This will make it much easier for others to help you. — Jaap
– Jaap, Commented Mar 31, 2016 at 15:02
Maybe just use data.matrix: e.g. as.data.frame(Titanic) vs. data.matrix(as.data.frame(Titanic)). — lukeA
– lukeA, Commented Mar 31, 2016 at 15:06
Procrastinatus Maximus - Thanks for the advice regarding asking a good question and providing a workable example. — Matthew Cutmore
– Matthew Cutmore, Commented Mar 31, 2016 at 15:12

coffeinjunky · Accepted Answer · 2016-03-31 15:03:36Z

3

Try the following:

df[,c(45:68)] <- lapply(df[,c(45:68)], function(x) 
                 recode(x,"'High'=4;
                           'Medium'=3;
                           'Low'=2;
                           'No Concerns'=1",
                            as.numeric.result=TRUE))

What happens here is that you pass individual columns to recode. Looking at the helpfile of recode, you see that the function expects a numeric vector, character vector or a factor as input. In your code you provide a list, however. The above code provides individual columns to recode, which should work. Of course, without proper example data, it is difficult to tell, but give it a try.

answered Mar 31, 2016 at 15:03

coffeinjunky

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davsjob · Accepted Answer · 2018-10-31 15:22:58Z

2

A solution with dplyr and hablar:

library(dplyr)
library(hablar)

df <- df %>% 
  mutate_at(vars(45:68),
            funs(case_when(x == 'High'        ~ 4,
                           x == 'Medium'      ~ 3,
                           x == 'Low'         ~ 2;
                           x == 'No Concerns' ~ 1))) %>% 
  convert(num(x))

answered Oct 31, 2018 at 15:22

davsjob

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Ben · Accepted Answer · 2020-02-06 20:30:34Z

0

This worked much better for me, especially since the recode command is more sensitive to formulas:

items<-c("a","b","c")

df[items] <- lapply(df[items], function(x) ifelse(x=="STRONGLY AGREE", 6,
  ifelse(x=="AGREE", 5,
  ifelse(x=="SLIGHTLY AGREE", 4,
  ifelse(x=="SLIGHTLY DISAGREE", 3,
  ifelse(x=="DISAGREE", 2,
  ifelse(x=="STRONGLY DISAGREE", 1,0)))))))

answered Feb 6, 2020 at 20:30

Ben

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