Many thanks for this Jorge. Exactly what I was looking for. I've never
encountered any() before. Quite useful.

Thanks again!

Sam

On Wed, Mar 9, 2011 at 1:05 PM, Jorge Ivan Velez
<jorgeivanvelez@gmail.com>wrote:

> Hi Sam,
>
> How about this?
>
> test[apply(test, 1, function(x) !any(x == '#DIV/0!')), ]
>
> HTH,
> Jorge
>
>
> On Wed, Mar 9, 2011 at 3:29 PM, Sam Albers <> wrote:
>
>> Hello Venerable List,
>>
>> I am trying to loop (I think) an operation through a list of columns in a
>> dataframe to remove set of #DIV/0! values. I am trying to do this like so:
>>
>> #Data.frame
>> test <- read.csv("http://dl.dropbox.com/u/1574243/sample_data.csv",
>> header=TRUE, sep=",")
>>
>>
>> #This removes all the rows with #DIV/0! values in the mean column.
>> only.mean <- test[!test$mean=="#DIV/0!",]
>>
>> #This removes the majority of #DIV/0! values as there is a large block of
>> these values that extends over every column.
>> #However, it doesn't remove then all. Can any recommend a way where I can
>> cycle through all the columns and remove these values other than manually
>> like so:
>> mean.median <- only.mean[!only.mean$median=="#DIV/0!",] # and so on
>> through
>> each column?
>>
>> Can anyone recommend a better way of doing this?
>>
>> Thanks in advance!
>>
>> Sam
>>
>>        [[alternative HTML version deleted]]
>>
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>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>

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