I usually do this the hard way, but I'm sure one of you coding experts has something less tedious.
Using this data set below:
#Example Dataset
Q1 <- c("Agree", "Disagree", "Strongly Agree", "Strongly Disagree", "Strongly Disagree")
Q2 <- c("Disagree", "Disagree", "Agree", "Disagree", "Strongly Disagree")
Q3 <- c("Agree", "Disagree", "Strongly Agree", "Strongly Agree", "Strongly Agree")
Q4 <- c("Disagree", "Disagree", "Disagree", "Strongly Disagree", "Strongly Disagree")
data <- data.frame(Q1, Q2, Q3, Q4)
I would usually just recode it using the car package like this:
library(car)
data$Q1 <- car::recode(data$Q1, "
'Strongly Disagree' = 1;
'Disagree' = 2;
'Agree' = 3;
'Strongly Agree' = 4")
data$Q2 <- car::recode(data$Q2, "
'Strongly Disagree' = 1;
'Disagree' = 2;
'Agree' = 3;
'Strongly Agree' = 4")
data$Q3 <- car::recode(data$Q3, "
'Strongly Disagree' = 1;
'Disagree' = 2;
'Agree' = 3;
'Strongly Agree' = 4")
data$Q4 <- car::recode(data$Q4, "
'Strongly Disagree' = 1;
'Disagree' = 2;
'Agree' = 3;
'Strongly Agree' = 4")
Is there a way I can do this by column? Or, applying to the whole scale with less code?
I thought I could just specify a range of columns maybe like this, but it does not do what I want.
data <- recode(data$[1:4], "
'Strongly Disagree' = 1;
'Disagree' = 2;
'Agree' = 3;
'Strongly Agree' = 4")
Alright, this is the solution. It's that dplyr is superior.
datarecoded <- data %>% #select dataframe
mutate_at(c("Q1", "Q2", "Q3", "Q4"), #select columns
funs(dplyr::recode(.,"Strongly Disagree" =1, #enter recodes
"Disagree" =2,
"Agree" =3,
"Strongly Agree" =4)))
Result
Q1 Q2 Q3 Q4
1 3 2 3 2
2 2 2 2 2
3 4 3 4 2
4 1 2 4 1
5 1 1 4 1
You can also select a range within the dataframe.
datarecoded <- data %>%
mutate_at(c(1:3),
funs(dplyr::recode(.,"Strongly Disagree" =1,
"Disagree" =2,
"Agree" =3,
"Strongly Agree" =4)))
Result 2
Q1 Q2 Q3 Q4
1 3 2 3 Disagree
2 2 2 2 Disagree
3 4 3 4 Disagree
4 1 2 4 Strongly Disagree
5 1 1 4 Strongly Disagree