Imputation in R

Question

I am new in R programming language. I just wanted to know is there any way to impute null values of just one column in our dataset. Because all of imputation commands and libraries that I have seen, impute null values of the whole dataset.

Answer 1

Here is an example using the Hmisc package and impute

library(Hmisc)
DF <- data.frame(age = c(10, 20, NA, 40), sex = c('male','female'))

# impute with mean value

DF$imputed_age <- with(DF, impute(age, mean))

# impute with random value
DF$imputed_age2 <- with(DF, impute(age, 'random'))

# impute with the media
with(DF, impute(age, median))
# impute with the minimum
with(DF, impute(age, min))

# impute with the maximum
with(DF, impute(age, max))


# and if you are sufficiently foolish
# impute with number 7 
with(DF, impute(age, 7))

 # impute with letter 'a'
with(DF, impute(age, 'a'))

Look at ?impute for details on how the imputation is implemented

Answer 2

Why not use more sophisticated imputation algorithms, such as mice (Multiple Imputation by Chained Equations)? Below is a code snippet in R you can adapt to your case.

library(mice)

#get the nhanes dataset
dat <- mice::nhanes

#impute it with mice
imp <- mice(mice::nhanes, m = 3, print=F)

imputed_dataset_1<-complete(imp,1)

head(imputed_dataset_1)

#     age  bmi hyp chl
# 1   1   22.5   1 118
# 2   2   22.7   1 187
# 3   1   30.1   1 187
# 4   3   24.9   1 186
# 5   1   20.4   1 113
# 6   3   20.4   1 184

#Now, let's see what methods have been used to impute each column
meth<-imp$method
#  age   bmi   hyp   chl
#"" "pmm" "pmm" "pmm"

#The age column is complete, so, it won't be imputed
# Columns bmi, hyp and chl are going to be imputed with pmm (predictive mean matching)

#Let's say that we want to impute only the "hyp" column
#So, we set the methods for the bmi and chl column to ""
meth[c(2,4)]<-""
#age   bmi   hyp   chl 
#""    "" "pmm"    "" 

#Let's run the mice imputation again, this time setting the methods parameter to our modified method
imp <- mice(mice::nhanes, m = 3, print=F, method = meth)

partly_imputed_dataset_1 <- complete(imp, 3)

head(partly_imputed_dataset_1)

#    age  bmi hyp chl
# 1   1   NA   1  NA
# 2   2 22.7   1 187
# 3   1   NA   1 187
# 4   3   NA   2  NA
# 5   1 20.4   1 113
# 6   3   NA   2 184