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rreplacedata-cleaningdplyr

Using the dplyr mutate function to replace multiple values

In the following data the levels for both variables are coded numerically

dat = read.csv("https://studio.edx.org/c4x/HarvardX/PH525.1x/asset/assoctest.csv")
head(dat)

I am replacing these codes with character strings to make for easier reading and graphing. This I am able to do successfully using the dplyr mutate function. 

dat_char = mutate(dat, allele=replace(allele, allele==0, "AA/Aa")) %>% 
mutate(allele=replace(allele, allele==1, "aa")) %>%
mutate(case=replace(case, case==0, "control")) %>%
mutate(case=replace(case, case==1, "case"))

The above code works perfectly well, but it is repetitive and fiddly to write. I am sure there is a way to perform some of these replacements simultaneously and slim down the code, but I am not sure how. For example, I have tried using vectors as the lookup and replace values.

dat_char = mutate(dat, allele=replace(allele, allele==c(0,1), c("AA/Aa", "aa"))) %>%
mutate(case=replace(case, case==c(0,1),  c("control", "case")))
head(dat_char)

This just makes a mess but it gives a sense of what I am trying to achieve.

Solution

  • You can use simple ifelse here but in case if you have multiple values to replace you can consider recode or case_when : 

    library(dplyr)

dat %>%
  mutate(allele = recode(allele, `0` = 'AA/Aa', `1` = 'aa'), 
         case = recode(case, `0` = 'control', `1` = 'case'))