replacing missing values with row average

An embedded and charset-unspecified text was scrubbed...
Name: not available
URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20110227/ccda30d5/attachment.pl>
Hi Daniel,

If your data is stored in a matrix, the following should work (and be
fairly efficient):

#############
dat <- matrix(rnorm(100), nrow = 10)
dat[sample(1:10, 3), sample(1:10, 3)] <- NA
## create an index of missing values
index <- which(is.na(dat), arr.ind = TRUE)
## calculate the row means and "duplicate" them to assign to appropriate cells
dat[index] <- rowMeans(dat, na.rm = TRUE)[index[, "row"]]

## for documentation see
?which # particularly the arr.ind argument
?"[" # for extraction or selecting a subset to overwrite
#############

the only reason this does not work as is with data frames is because
of how they are indexed/subset.  dat[index] does not work.  The
required modification is probably fairly minimal, but if you are happy
to use a matrix, then its a moot issue.

HTH,

Josh
Hello,

I have some dataset, which i read it from external file using the (data <-
read.csv("my file location")) and read as a dataframe

is(data)
[1] "data.frame" "list" ? ? ? "oldClass" ? "vector"
but i have also converted this into a matrix and tried to apply my code but
didnt work.

Anyways, suppose i have the following data.

? ?data <- as.data.frame(matrix(rnorm(100), nrow = 10))

And let's put some missing values

? ?data[sample(1:10, 3), sample(1:10, 3)] <- NA

I want to replace all NA's by row averages or column averages of my matrix.

I tried to use(with my original data matrix)

? ?data[is.na(data)] <- rowMeans(data, na.rm = TRUE)
But got an error message of

? ? ? Error in rowMeans(data, na.rm = TRUE) : 'x' must be numeric
Then I converted ?data<- as.matrix(data)
? ? ? ? ? ? ? ? ?data<- as.numeric(data)
And applying my code

? ? data[is.na(data)] <- rowMeans(data, na.rm = TRUE)

Error message

? ? ?Error in rowMeans(data, na.rm = TRUE) :
?'x' must be an array of at least two dimensions

Then again i tried to convert it into Arrays....but the errors continues....

I Also tried the code

? ?data[is.na(data)] <- apply(data,1,mean)

But still didnt work out.

Can anyone pls help me as to how to fix it and get out of this, please?

Thank you very much

Daniel

? ? ? ?[[alternative HTML version deleted]]

______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/
Warning: This is not a helpful answer. Actually, it's a question: Why
do you want to do this? Replacing missing values with row or column
averages and then analyzing the data as if the missing values were not
there is a dangerous thing to do it can produce biased estimates and
understate the true error, likely resulting in biased inference. Of
course, this depends on the specifics (how many are missing and
where).

R has a lot of built-in capabilities for handling missing values. I
agree: it's not easy stuff. Nor do you necessarily need to get that
complicated: Maybe your scheme is perfectly adequate for your
situation. I just wanted to caution you think about this carefully if
you aren't aware of the possible problems and haven't already done so.

-- Bert
Hello,

I have some dataset, which i read it from external file using the (data <-
read.csv("my file location")) and read as a dataframe