[R] Plotting graph for Missing values

jim holtman jholtman at gmail.com
Mon Jan 26 03:50:30 CET 2009


YOu can save the output of the tapply and then replicate it for each
of the variables.  The data can be used to plot the graphs.

On Sun, Jan 25, 2009 at 9:38 PM, Shreyasee <shreyasee.pradhan at gmail.com> wrote:
> Hi Jim,
>
> I need to calculate the missing values in variable "patientinformation1" for
> the period of May 2006 to March 2007 and then plot the graph of the
> percentage of the missing values over these months.
> This has to be done for each variable.
> The code which you have provided, calculates the missing values for the
> months variable, am I right?
> I need to calculate for all the variables for each month.
>
> Thanks,
> Shreyasee
>
>
> On Mon, Jan 26, 2009 at 10:29 AM, jim holtman <jholtman at gmail.com> wrote:
>>
>> Here is an example of how you might approach it:
>>
>> > dos <- seq(as.Date('2006-05-01'), as.Date('2007-03-31'), by='1 day')
>> > pat1 <- rbinom(length(dos), 1, .5)  # generate some data
>> > # partition by month and then list out the number of zero values
>> > (missing)
>> > tapply(pat1, format(dos, "%Y%m"), function(x) sum(x==0))
>> 200605 200606 200607 200608 200609 200610 200611 200612 200701 200702
>> 200703
>>    21     22     16     18     16     15     16     17     14     16
>> 13
>> >
>>
>>
>> On Sun, Jan 25, 2009 at 8:51 PM, Shreyasee <shreyasee.pradhan at gmail.com>
>> wrote:
>> > Hi Jim,
>> >
>> > The dataset has 4 variables (dos, patientinformation1,
>> > patientinformation2,
>> > patientinformation3).
>> > In dos variable ther are months (May 2006 to March 2007) when the
>> > surgeries
>> > were formed.
>> > I need to calculate the percentage of missing values for each variable
>> > (patientinformation1, patientinformation2, patientinformation3) for each
>> > month.
>> > I need a common script to calculate that for each variable.
>> >
>> > Thanks,
>> > Shreyasee
>> >
>> >
>> > On Mon, Jan 26, 2009 at 9:46 AM, jim holtman <jholtman at gmail.com> wrote:
>> >>
>> >> What does you data look like?  You could use 'split' and then examine
>> >> the data in each range to count the number missing.  Would have to
>> >> have some actual data to suggest a solution.
>> >>
>> >> On Sun, Jan 25, 2009 at 8:30 PM, Shreyasee
>> >> <shreyasee.pradhan at gmail.com>
>> >> wrote:
>> >> > Hi,
>> >> >
>> >> > I have imported one dataset in R.
>> >> > I want to calculate the percentage of missing values for each month
>> >> > (May
>> >> > 2006 to March 2007) for each variable.
>> >> > Just to begin with I tried the following code :
>> >> >
>> >> > *for(i in 1:length(dos))
>> >> > for(j in 1:length(patientinformation1)
>> >> > if(dos[i]=="May-06" && patientinformation1[j]=="")
>> >> > a <- j+1
>> >> > a*
>> >> >
>> >> > The above code was written to calculate the number of missing values
>> >> > for
>> >> > May
>> >> > 2006, but I am not getting the correct results.
>> >> > Can anybody help me?
>> >> >
>> >> > Thanks,
>> >> > Shreyasee
>> >> >
>> >> >        [[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.
>> >> >
>> >>
>> >>
>> >>
>> >> --
>> >> Jim Holtman
>> >> Cincinnati, OH
>> >> +1 513 646 9390
>> >>
>> >> What is the problem that you are trying to solve?
>> >
>> >
>>
>>
>>
>> --
>> Jim Holtman
>> Cincinnati, OH
>> +1 513 646 9390
>>
>> What is the problem that you are trying to solve?
>
>



-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem that you are trying to solve?



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