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Dear R-experts, I am struggling with the following problem, and I am looking for advice from more experienced R-users: I have a data frame with 2 identifying variables (comn and mi), and an output variable (x). comn is a variable for a company and mi is a variable for a month. comn<-c("abc", "abc", "abc", "abc", "abc", "abc",

Dear R experts, I have a dataframe imported from a csv file (with read.csv). Here is an example: yyyymm<- c("19860228", "19860331","19860430","19860531") id<-c("10000","10000","10000","10000") re<- c("C","0.25", "0.98", "1.34") mret<-data.frame(yyyymm, id, re)

Dear R-users, -I am new to R, and I am struggling with the following problem. -I am repeating the following operations hundreds of times, within a loop: I want to subset a data frame by columns. I am interested in the columns names that are given by the rows of another data frame that was built in parallel. The solution I have so far works well as long as the elements of the second data frame

...directory mode = 0700 browseable = No #compatibilité des droit dos/unix dos filemode = yes #Ajout du system de corbeille vfs options = /etc/samba/recycle.conf vfs object = /usr/lib/samba/vfs/recycle.so #repertoire de netlogon [netlogon] browseable = no writable = yes admin users = maura philippot-f public = no path = /home/samba/netlogon [profile] path=/home/samba/profile create mode = 0600 directory mode = 0700 writable = yes browseable = No #repertoire de groupe [service] comment = Repertoire de travaux commun au service path=/home/samba/services/%G create mode = 0660 director...

Dear R users, I am new to Latex and I am using the R package xtable to generate tables. I want to produce a table that is very long. in the landscape format, but I would need to rescale the table so that it fits in the page. xtable enables me to have the landscape format, but I cannot rescale it, and there seems to be a problem, if I use scalebox in Latex on my output produced with stable and the

Dear all, I am new in R and I have been faced with the following problem, that slows me down a lot. I am short of ideas to circumvent it. So, any help would be highly appreciated: I have 2 dataframes x and y. x is very big (70 million observations), whereas y is smaller (300000 observations). All the observations of y are present in x. But y has one additional variable that I would like to