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detecting null values in a CSV file

7 messages · Henrik Bengtsson, Hutchinson,David [PYR], Jason Thibodeau +1 more

#
What have you tried this far?  Can't you parse them as missing values,
i.e. NAs?   See ?read.csv and arguments '...', i.e. the arguments
'...' are passed to read.table() which takes argument 'na.strings' - a
character *vector* of strings that you want to be interpreted as NAs.
See ?read.table for more details.

My $.02

Henrik
On Thu, Sep 18, 2008 at 10:11 AM, Jason Thibodeau <jbloudg20 at gmail.com> wrote:
#
Try length(na.omit(<the particular data column>))

Here's an example:

data <- runif(100,0,10)
data[runif(20,0,100)] <- NA
file.contents <- matrix(data, ncol = 5, byrow = TRUE)
for (i in 1:5) {
  print (length(na.omit(file.contents[,i])))
}
 

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of Jason Thibodeau
Sent: Thursday, September 18, 2008 10:12 AM
To: r-help at r-project.org
Subject: [R] detecting null values in a CSV file

Hello all,

I have a CSV file, that is 2411 columns wide. There are certain
instances in
teh file, where null values are located. That is: two commas together,
without anything in the middle. In a certain section, the only possible
values are NULL, 0,1,and 2. I need to be able to detect these NULL's and
be
able to have them counted. For example, in a frequency table. How can I
accomplish this?

Thanks in advance for the help.
#
You can always do this if they are single valued vectors:

if ((!is.na(data_filter)) & (!is.na(trigger)) & (data_filter == trigger)) ....

This will catch the condition where either is an NA and therefore not
do the final compare which was giving your error.
On Fri, Sep 19, 2008 at 9:48 AM, Jason Thibodeau <jbloudg20 at gmail.com> wrote: