Hello All,
wonder if you have a suggestion for the following:
we have
a<-data.frame(ID=c(1,2,3,4,5,6,7),date=as.POSIXct(seq(as.Date('2011-01-01'),as.Date('2011-01-07'),by
= 1),format='%m/%d/%Y %H:%M'),z=rnorm(7,1,1))
b<-data.frame(ID=c(1,2,3,11,12,13,14,15),date=as.POSIXct(seq(as.Date('2011-01-01'),as.Date('2011-01-08'),by
= 1),format='%m/%d/%Y %H:%M'),z=rnorm(8,1,1))
c<-data.frame(ID=c(1,2,3,4,5,6,7,8,9,10),date=as.POSIXct(c(seq(as.Date('2011-01-01'),as.Date('2011-01-05'),by
= 1),seq(as.Date('2011-01-11'),as.Date('2011-01-15'),by = 1)),format='%m/%d/%Y
%H:%M'),z=rnorm(10,1,1))
d<-data.frame(ID=c(1,2,3,21,22,23,24,25,26,27,28),date=as.POSIXct(c(as.Date('2011-01-01'),as.Date('2011-11-01'),as.Date('2011-01-03'),seq(as.Date('2011-01-01'),as.Date('2011-01-08'),by
= 1)),format='%m/%d/%Y %H:%M'),z=rnorm(11,1,1))
#this function will do the obvious and give the IDs that are in all of the data
frames based on the ID column
intersect_all <- function(a,b,...){
Reduce(intersect, list(a,b,...))
}
intersect_all(a$ID,b$ID,c$ID,d$ID)
#I would like to extend this (or use another function) where the function would
give all the rows (ie based on both columns as a condition) that are in all of
the data frames, so the result should be as below as these 2 rows are in all of
the data frames (the fact that the rows that are common in all data frames ie 1
and 3 in my example are I only set up for the sake of convenience, in reality
their row number in each of the data frames may be different) . The value of z
is of no particular importance, but once the common rows are identified I would
want to subset the data frames to get these results:
a[c(1,3),]
b[c(1,3),]
c[c(1,3),]
d[c(1,3),]
much appreciate your input,
thanks
Andras
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