[R] Applying a user-defined function

Tue Jan 8 18:38:27 CET 2013

On Jan 8, 2013, at 9:11 AM, Muhuri, Pradip (SAMHSA/CBHSQ) wrote:

> Hello List,
>
> My goal is to apply a user-defined function on several columns of a  
> data frame. When testing the code on a reproducible example below, I  
> get the following error message.
>
>> #now Write a new function using the above cut ()/quantile function  
>> to apply on different columns of the data frame
>>
>> CutQuintiles <- function(x) {
> +   cut (test1$x,quantile (test1$x, (0:5/5)),include.lowest=TRUE)
> + }
>>
>> #apply the CutQuintile () on every odd-numbered columns of the  
>> "test1" data frame
>> newcols <- sapply(test1 [, seq (1,6,2)], CutQuintiles)
> Error in cut.default(test1$x, quantile(test1$x, (0:5/5)),  
> include.lowest = TRUE) :
>  'x' must be numeric
>
> I would appreciate receiving your advice.
>

Take the "test$" out of that function's code. You are reaching outside  
the function when you should only be working on the "x" object that  
gets passed into it.

> Thanks,
>
> Pradip
>
> ###### The reproducible example begins here
>
> test1 <- read.table (text=
> "State,ObtMj_P,ObtMj_SE,ExpPrevMed_P,ExpPrevMed_SE,ParMon_P,ParMon_SE
> Alabama,49.60,1.37,80.00,0.91,12.10,0.68
> Alaska,55.00,1.41,81.80,1.08,12.40,0.90
> Arizona,52.50,1.56,79.60,1.20,15.80,1.08
> Arkansas,50.50,1.22,78.00,0.78,12.80,0.72
> California,51.10,0.65,80.50,0.53,13.00,0.41
> Colorado,55.10,1.26,81.70,1.03,12.10,0.72
> Connecticut,56.30,1.28,85.00,0.93,14.60,0.77
> Delaware,53.60,1.30,79.50,1.04,14.70,0.97
> District of Columbia,53.50,1.22,76.20,1.03,14.30,1.13
> Florida,52.70,0.67,78.90,0.52,14.10,0.45
> Georgia,52.50,1.15,79.30,1.02,15.90,0.98
> Hawaii,49.40,1.33,83.80,1.12,16.00,1.06
> Idaho,48.30,1.23,82.40,0.99,11.90,0.74
> Illinois,52.70,0.63,81.00,0.46,13.60,0.40
> Indiana,49.60,1.16,80.90,0.91,12.60,0.82
> Iowa,46.30,1.37,82.10,1.01,13.60,0.87
> Kansas,44.30,1.43,79.20,0.98,12.90,0.79
> Kentucky,52.90,1.37,78.70,1.05,14.60,0.98
> Louisiana,49.70,1.23,76.80,1.06,14.50,0.76
> Maine,55.60,1.44,82.90,0.93,16.70,0.83
> Maryland,53.90,1.46,83.60,0.95,14.00,0.80
> Massachusetts,55.40,1.41,81.00,1.15,14.70,0.80
> Michigan,52.40,0.62,80.50,0.47,15.00,0.43
> Minnesota,51.50,1.20,84.40,0.87,14.40,0.86
> Mississippi,43.20,1.14,76.60,0.91,12.30,0.78
> Missouri,48.70,1.20,80.30,0.90,13.70,0.12
> Montana,56.40,1.16,83.70,0.95,12.10,0.68
> Nebraska,45.70,1.51,83.40,0.95,12.40,0.90
> Nevada,54.20,1.17,80.60,1.07,15.80,1.08
> New Hampshire,56.10,1.30,83.30,0.93,12.80,0.72
> New Jersey,53.20,1.45,83.70,0.95,13.00,0.41
> New Mexico,57.60,1.34,78.90,1.03,12.10,0.72
> New York,53.70,0.67,82.60,0.48,14.60,0.77
> North Carolina,52.20,1.26,81.90,0.84,14.70,0.97
> North Dakota,48.60,1.34,84.20,0.88,14.30,1.13
> Ohio,50.90,0.61,82.70,0.49,14.10,0.45
> Oklahoma,47.20,1.42,78.80,1.33,15.90,0.98
> Oregon,54.00,1.35,80.60,1.14,16.00,1.06
> Pennsylvania,53.00,0.63,79.90,0.47,11.90,0.74
> Rhode Island,57.20,1.20,79.50,1.02,13.60,0.40
> South Carolina,50.50,1.21,79.50,0.95,12.60,0.82
> South Dakota,43.40,1.30,81.70,1.05,13.60,0.87
> Tennessee,48.90,1.35,78.40,1.35,12.90,0.79
> Texas,48.70,0.62,79.00,0.48,14.60,0.98
> Utah,42.00,1.49,85.00,0.93,14.50,0.76
> Vermont,58.70,1.24,83.70,0.84,16.70,0.83
> Virginia,51.80,1.18,82.00,1.04,14.00,0.80
> Washington,53.50,1.39,84.10,0.96,14.70,0.80
> West Virginia,52.80,1.07,79.80,0.93,15.00,0.43
> Wisconsin,49.90,1.50,83.50,1.02,14.40,0.86
> Wyoming,49.20,1.29,82.00,0.85,12.30,0.78
> ", sep=",", row.names='State',  header=TRUE, as.is=TRUE)
>
>
> # Verify if The following function ctagorizes the "obtmj_p" values  
> into one of the 5 equal sized groups- works fine.
>
> cut (test1$obtmj_p,quantile (test1$obtmj_p,  
> (0:5/5)),include.lowest=TRUE)
>
>
> #now Write a new function using the above cut ()/quantile function  
> to apply on different columns of the data frame
>
> CutQuintiles <- function(x) {
>  cut (test1$x,quantile (test1$x, (0:5/5)),include.lowest=TRUE)
> }
>
> #apply the CutQuintile () on every odd-numbered columns of the  
> "test1" data frame
> newcols <- sapply(test1 [, seq (1,6,2)], CutQuintiles)
>
> # name 3 new columns based on the odd-numbered columns
> names(newcols) <- paste (names(test1 [, seq (1,6,2)]), "_cat")
>
> ######
> Pradip K. Muhuri, PhD
> Statistician
> Substance Abuse & Mental Health Services Administration
> The Center for Behavioral Health Statistics and Quality
> Division of Population Surveys
> 1 Choke Cherry Road, Room 2-1071
> Rockville, MD 20857
>
> Tel: 240-276-1070
> Fax: 240-276-1260
> e-mail: Pradip.Muhuri at samhsa.hhs.gov<mailto:Pradip.Muhuri at samhsa.hhs.gov 
> >
>
> The Center for Behavioral Health Statistics and Quality your  
> feedback.  Please click on the following link to complete a brief  
> customer survey:   http://cbhsqsurvey.samhsa.gov<http://cbhsqsurvey.samhsa.gov/ 
> >
>
>
> 	[[alternative HTML version deleted]]
>
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> and provide commented, minimal, self-contained, reproducible code.

David Winsemius, MD
Alameda, CA, USA