Hi Lucy, No problem.
Just a correction to my earlier email. dat1<-read.table("Landeck_vec.txt",sep="",header=TRUE,stringsAsFactors=FALSE) dat2<-read.table("Kaurnetal_vec.txt",sep="",header=TRUE,stringsAsFactors=FALSE) colnames(dat1)[1]<-"Date" (Rui: #dat2 Date format is inconsistent.) dat2$Date<-gsub("\\.","\\/",dat2$Date) dat1$Date<-as.POSIXct(dat1$Date,format="%d.%m.%Y") dat2$Date<-as.POSIXct(dat2$Date,format="%d/%m/%Y") str(dat1) #'data.frame': 22623 obs. of 2 variables: # $ Date : POSIXct, format: "1900-04-01" "1900-04-02" ... # $ Event: int 0 0 0 0 0 0 0 0 0 0 ... str(dat2) #'data.frame': 36598 obs. of 2 variables: # $ Date : POSIXct, format: "1900-01-01" "1900-01-02" ... # $ Precip: chr "0" "0" "0" "0" ... Precip is "character", which I convert it to numeric #dat2<-within(dat2,{Precip<-as.numeric(Precip)}) #Warning message: #In eval(expr, envir, enclos) : NAs introduced by coercion The reason is that there are datapoints which has some unusual characters. which(is.na(dat2$Precip)) # [1] 7060 8584 8798 11235 12848 13701 14006 14038 14098 14311 16016 16748 #[13] 18575 19307 19489 19702 19764 21196 dat2[8584,] # Date Precip #8584 1923-09-01 NA When I looked into the data, I found this: 01/09/1923 L�cke count(is.na(dat2$Precip)) # x freq #1 FALSE 36580 #2 TRUE 18 #Removed those rows. dat3<-subset(dat2,!is.na(Precip)) nrow(dat3) #[1] 36580 dat4<-merge(dat1,dat3,by="Date") dat5<-subset(dat4,Event!=0) nrow(dat5) #[1] 132 rownames(dat5)<-1:nrow(dat5) head(dat5) # Date Event Precip #1 1901-06-02 1 0.0 #2 1905-06-02 1 0.0 #3 1906-08-03 1 15.6 #4 1908-05-08 1 0.0 #5 1911-06-02 1 3.0 #6 1911-09-15 1 23.2 A.K. ----- Original Message ----- From: lucy88 <lucy.fog...@gmail.com> To: r-help@r-project.org Cc: Sent: Thursday, October 4, 2012 7:18 AM Subject: [R] R combining vectors into a data frame but without a continuous common variable Hello, I have two different files which I'd like to combine to make one data frame but I've no idea how to do it! The first file has two columns; one is the date, the following is a binary code for debris flow events. Then my other file has also two columns; the date and then precipitation data. The thing is, is that the two date columns don't all contain the same dates. The binary one is every day from April - October from 1900 - 2005, yet the precipitation file has dates from from say, 1911 to 2004, with some missing data on certain months and during certain years. So my question is how to make a data frame which would have the date, the binary 0 or 1, and then the corresponding precip value from that particular date. I only want the precip information for the days where I have information in the binary file; the others can be disregarded. I have tried using codes which I found in answer to other questions asked but none of them work with my issue. If I'm honest I don't really know if this is what I need. I'm hoping to end up doing a logistic regression. I've uploaded the two files in case I've not been very clear... I'd be really grateful if anyone could help me and suggest a way to do it! I'm also really not very technical and am not at all comfortable with R so if you could be really basic in your advice I'd appreciate it! Many thanks in advance, Lucy Landeck_vec.txt <http://r.789695.n4.nabble.com/file/n4644986/Landeck_vec.txt> Kaurnetal_vec.txt <http://r.789695.n4.nabble.com/file/n4644986/Kaurnetal_vec.txt> -- View this message in context: http://r.789695.n4.nabble.com/R-combining-vectors-into-a-data-frame-but-without-a-continuous-common-variable-tp4644986.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.