Hi Dan, Thank you so much for sending me your code that provides me desired results. But, I don't understand why I am getting the follow warning message, In FUN(newX[, i], ...) : no non-missing arguments, returning NA. Any thoughts?
Regards, Pradip data2x <- within(data1, oidflag <- apply(data1[,-1], 1, max, na.rm=TRUE)) Warning message: In FUN(newX[, i], ...) : no non-missing arguments, returning NA > data2x id mrjdate cocdate inhdate haldate oidflag 1 1 2004-11-04 2008-07-18 2005-07-07 2007-11-07 2008-07-18 2 2 <NA> <NA> <NA> <NA> <NA> 3 3 2009-10-24 <NA> 2011-10-13 <NA> 2011-10-13 4 4 2007-10-10 <NA> <NA> <NA> 2007-10-10 5 5 2006-09-01 2005-08-10 <NA> <NA> 2006-09-01 6 6 2007-09-04 2011-10-05 <NA> <NA> 2011-10-05 7 7 2005-10-25 <NA> <NA> 2011-11-04 2011-11-04 Pradip K. Muhuri, PhD SAMHSA/CBHSQ 1 Choke Cherry Road, Room 2-1071 Rockville, MD 20857 Tel: 240-276-1070 Fax: 240-276-1260 -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Daniel Nordlund Sent: Sunday, November 09, 2014 5:33 AM To: r-help@r-project.org Subject: Re: [R] Getting the most recent dates in a new column from dates in four columns using the dplyr package (mutate verb) On 11/8/2014 8:40 PM, Muhuri, Pradip (SAMHSA/CBHSQ) wrote: > Hello, > > > > The example data frame in the reproducible code below has 5 columns (1 column > for id and 4 columns for dates), and there are 7 observations. I would like > to insert the most recent date from those 4 date columns into a new column > (oiddate) using the mutate() function in the dplyr package. I am getting > correct results (NA in the new column) if a given row has all NA's in the > four columns. However, the issue is that the date value inserted into the > new column (oidflag) is incorrect for 5 of the remaining 6 rows (with a > non-NA value in at least 1 of the four columns). > > > > I would appreciate receiving your help toward resolving the issue. Please > see the R console and the R script (reproducible example)below. > > > > Thanks in advance. > > > > Pradip > > > > > > ###### from the console ######## > > print (data2) > > id mrjdate cocdate inhdate haldate oidflag > > 1 1 2004-11-04 2008-07-18 2005-07-07 2007-11-07 2011-11-04 > > 2 2 <NA> <NA> <NA> <NA> <NA> > > 3 3 2009-10-24 <NA> 2011-10-13 <NA> 2011-11-04 > > 4 4 2007-10-10 <NA> <NA> <NA> 2011-11-04 > > 5 5 2006-09-01 2005-08-10 <NA> <NA> 2011-11-04 > > 6 6 2007-09-04 2011-10-05 <NA> <NA> 2011-11-04 > > 7 7 2005-10-25 <NA> <NA> 2011-11-04 2011-11-04 > > > > > > ################## Reproducible code and data > ##################################### > > > > library(dplyr) > > library(lubridate) > > library(zoo) > > # data object - description of the > > > > temp <- "id mrjdate cocdate inhdate haldate > > 1 2004-11-04 2008-07-18 2005-07-07 2007-11-07 > > 2 NA NA NA NA > > 3 2009-10-24 NA 2011-10-13 NA > > 4 2007-10-10 NA NA NA > > 5 2006-09-01 2005-08-10 NA NA > > 6 2007-09-04 2011-10-05 NA NA > > 7 2005-10-25 NA NA 2011-11-04" > > > > # read the data object > > > > data1 <- read.table(textConnection(temp), > > colClasses=c("character", "Date", "Date", "Date", > "Date"), > > header=TRUE, as.is=TRUE > > ) > > # create a new column > > > > data2 <- mutate(data1, > > oidflag= ifelse(is.na(mrjdate) & is.na(cocdate) & > is.na(inhdate) & is.na(haldate), NA, > > max(mrjdate, cocdate, inhdate, > haldate,na.rm=TRUE ) > > ) > > ) > > > > # convert to date > > data2$oidflag = as.Date(data2$oidflag, origin="1970-01-01") > > > > # print records > > > > print (data2) > > > > > > Pradip K. Muhuri, PhD > > SAMHSA/CBHSQ > > 1 Choke Cherry Road, Room 2-1071 > > Rockville, MD 20857 > > Tel: 240-276-1070 > > Fax: 240-276-1260 > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@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. > I am not familiar with the mutate() function from dplyr, but you can get your wanted results as follows: data2 <- within(data1, oidflag <- apply(data1[,-1], 1, max, na.rm=TRUE)) Hope this is helpful, Dan Daniel Nordlund Bothell, WA USA ______________________________________________ R-help@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. ______________________________________________ R-help@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.
