Good morning!
I have two datasets with the same structure, one containing all my
values and the second one that update same of these values (see example
below).
I want to create a data.frame with all the values of the first dataset
except when an entry is present in the second dataset, in which case the
second dataset value is taken.
Is there a better method than my last line kludge?
Thanks for your help!
mario
t1 <- textConnection("AAA 1
BBB 2
CCC 3")
a <- read.table(t1, stringsAsFactors=FALSE)
close(t1)
t2 <- textConnection("BBB 22")
u <- read.table(t2, stringsAsFactors=FALSE)
close(t2)
m <- merge(a, u, by="V1", all.x=TRUE)
out <- data.frame(V1=m$V1, V2=ifelse(is.na(m$V2.y), m$V2.x, m$V2.y))
--
Ing. Mario Valle
Data Analysis and Visualization Group |
http://www.cscs.ch/~mvalle
Swiss National Supercomputing Centre (CSCS) | Tel: +41 (91) 610.82.60
v. Cantonale Galleria 2, 6928 Manno, Switzerland | Fax: +41 (91) 610.82.82
try this:> aV1 V2 1 AAA 1 2 BBB 2 3 CCC 3> uV1 V2 1 BBB 22> a$V2[match(u$V1, a$V1)] <- u$V2 > aV1 V2 1 AAA 1 2 BBB 22 3 CCC 3>On Sun, Jun 6, 2010 at 12:41 PM, Mario Valle <mvalle at cscs.ch> wrote:> Good morning! > I have two datasets with the same structure, one containing all my values > and the second one that update same of these values (see example below). > I want to create a data.frame with all the values of the first dataset > except when an entry is present in the second dataset, in which case the > second dataset value is taken. > > Is there a better method than my last line kludge? > Thanks for your help! > ? ? ? ? ? ? ? ? ? ? ? ?mario > > > t1 <- textConnection("AAA 1 > BBB 2 > CCC 3") > a <- read.table(t1, stringsAsFactors=FALSE) > close(t1) > t2 <- textConnection("BBB 22") > u <- read.table(t2, stringsAsFactors=FALSE) > close(t2) > m <- merge(a, u, by="V1", all.x=TRUE) > out <- data.frame(V1=m$V1, V2=ifelse(is.na(m$V2.y), m$V2.x, m$V2.y)) > > > -- > Ing. Mario Valle > Data Analysis and Visualization Group ? ? ? ? ? ?| > http://www.cscs.ch/~mvalle > Swiss National Supercomputing Centre (CSCS) ? ? ?| Tel: ?+41 (91) 610.82.60 > v. Cantonale Galleria 2, 6928 Manno, Switzerland | Fax: ?+41 (91) 610.82.82 > > ______________________________________________ > 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?
That is! Match, not merge is the solution. Ahhh, memory, memory... Thanks a lot! mario On 07-Jun-10 0:09, jim holtman wrote:> try this: > >> a > V1 V2 > 1 AAA 1 > 2 BBB 2 > 3 CCC 3 >> u > V1 V2 > 1 BBB 22 >> a$V2[match(u$V1, a$V1)]<- u$V2 >> a > V1 V2 > 1 AAA 1 > 2 BBB 22 > 3 CCC 3 >> > > > On Sun, Jun 6, 2010 at 12:41 PM, Mario Valle<mvalle at cscs.ch> wrote: >> Good morning! >> I have two datasets with the same structure, one containing all my values >> and the second one that update same of these values (see example below). >> I want to create a data.frame with all the values of the first dataset >> except when an entry is present in the second dataset, in which case the >> second dataset value is taken. >> >> Is there a better method than my last line kludge? >> Thanks for your help! >> mario >> >> >> t1<- textConnection("AAA 1 >> BBB 2 >> CCC 3") >> a<- read.table(t1, stringsAsFactors=FALSE) >> close(t1) >> t2<- textConnection("BBB 22") >> u<- read.table(t2, stringsAsFactors=FALSE) >> close(t2) >> m<- merge(a, u, by="V1", all.x=TRUE) >> out<- data.frame(V1=m$V1, V2=ifelse(is.na(m$V2.y), m$V2.x, m$V2.y)) >> >> >> -- >> Ing. Mario Valle >> Data Analysis and Visualization Group | >> http://www.cscs.ch/~mvalle >> Swiss National Supercomputing Centre (CSCS) | Tel: +41 (91) 610.82.60 >> v. Cantonale Galleria 2, 6928 Manno, Switzerland | Fax: +41 (91) 610.82.82 >> >> ______________________________________________ >> 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. >> > > >-- Ing. Mario Valle Data Analysis and Visualization Group | http://www.cscs.ch/~mvalle Swiss National Supercomputing Centre (CSCS) | Tel: +41 (91) 610.82.60 v. Cantonale Galleria 2, 6928 Manno, Switzerland | Fax: +41 (91) 610.82.82