How to for loop on each column and do mean imputation using a function in R

Question

how to calculate colMedian using colMedian function. I get an error: Argument 'x' must be a matrix or a vector.

col_medians <- round(colMedians(impute_marks[,-1], na.rm=TRUE),0)
k <- which(is.na(impute_marks), arr.ind=TRUE)
impute_marks[k] <- col_medians[k[,-1]]

I need to do the below operation for all the columns other than first column in the data frame. Below code works fine. but I in for loop gives an error unknown courses when looped.

impute_marks$c1[is.na(impute_marks$c1)] <- round(mean(impute_marks$c1[!is.na(impute_marks$c1)]),0)

here, impute_marks is the name of the dataset and c1 is the column name.

using the above operation I am able to find the mean and replace all NA values in c1 (column). But I have 30+ columns. How can I write the above operation in a for loop to loop through each course and replace NA value with the mean?

my function for the operation:

impute_marks$F27SA[is.na(impute_marks$F27SA)] <- round(mean(impute_marks$F27SA[!is.na(impute_marks$F27SA)]),0)

imputing_using_mean <- function()
{
    courses <- names(impute_marks)[2:26]  
    for(i in seq_along(courses))
    {
      impute_marks$courses[[i]][is.na(impute_marks$courses[[i]])] <- round(mean(impute_marks$courses[[i]][!is.na(impute_marks$courses[[i]])]),0)
    }
}

imputing_using_mean()

score 1 · Accepted Answer · edited May 23 '17 at 12:24

1

Essentially the same as answer from @Aaron on Replace NA values by row means . Tweaked to account for the first column.

marks <- read.table(text="
  a  1 NA  3
  b  1  2  3
  c NA NA NA
  ")
col_means <- round(colMeans(marks[,-1], na.rm=TRUE), 0)
k <- which(is.na(marks), arr.ind=TRUE)
marks[k] <- col_means[k[,2]-1]

#  V1 V2 V3 V4
#1  a  1  2  3
#2  b  1  2  3
#3  c  1  2  3

edited May 23 '17 at 12:24

Community

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1

answered Jan 21 '17 at 01:28

Andrew Lavers

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Is this mean for rows? I need for means for column element – Murlidhar Fichadia Jan 21 '17 at 01:38
I tried first two statements work. till k, where it stores all the index of a column in a vector. but last statement which inputs mean value to the vector doesnt seem to work – Murlidhar Fichadia Jan 21 '17 at 01:44
Edited to use column means instead of row means – Andrew Lavers Jan 21 '17 at 02:01
I have a similar query for median and I tried but it seems to give an error, can you please help. I will update my question for median. please have a look at it – Murlidhar Fichadia Jan 21 '17 at 02:02
Ok. Thanks, I was able to solve the solution for median. I had to first convert it to as.matrix. to do the operation – Murlidhar Fichadia Jan 21 '17 at 02:08

score 0 · Answer 2 · answered Jan 21 '17 at 02:10

Below is a solution for calculating median for each column and replacing each NA values with the median calculated for each column. same goes for mean as well but the step to convert it to a matrix is not required.

# first convert it to matrix
matrix_marks <- as.matrix(impute_marks)

$calculate the median for each column
col_medians <- round(colMedians(matrix_marks[,-1], na.rm=TRUE),0)

#get the index for each NA values
k <- which(is.na(matrix_marks), arr.ind=TRUE)

finally replace those values with median value.
matrix_marks[k] <- col_medians[k[,-1]]

How to for loop on each column and do mean imputation using a function in R

2 Answers2