similar to: BACKUP SYSTEM WITH SAMBA

Dear R helpers   After executing the R code, where the last few lines of the code are something like given below.     ## Part of my R code     n = 20   ........ .........   final_output = data.frame(Numbers = numbers, ABC = data1, XYZ = data2, PQR = data3)           write.csv(data.frame(Scenario = paste("Sc_", 1:n, sep = ""), final_output'), 'result.csv', row.names

While doing some performance testing with the new version of pqR (see pqR-project.org), I've encountered an extreme, and quite unnecessary, inefficiency in the current R Core implementation of R, which I think you might want to correct. The inefficiency is in access to columns of a data frame, as in expressions such as df$col[i], which I think are very common (the alternatives of

Hi, I am new in R, i have a matrix like this MyMatrix <- *ABC PQR XYZ* 10 20 30 40 50 60 70 80 90 And, i have an array containing some conditions like this, MyArray <- c("*ABC*>50","*PQR*<50","*ABC*<30 &* XYZ*<40") "ABC>50" "PQR<50" "ABC<30 & XYZ<40"

Could you please tell me what is the function or method to get count of elements in all the columns in a matrix ? for eg :- ABC XYZ PQR ------ ----- ------ 2 3 4 4 5 5 4 3 2 Result will be like ABC XYZ PQR ------ ----- ------ 2 4 3 Could you please help me

Dear R helpers   I have some variables say ABC, DEF, PQR, LMN and XYZ. I am choosing any three varaibles at random at a time for my analysis and name these files as input1.csv, input2.csv and input3.csv. So if I choose variables say ABC, DEF and PQR, I am passing the specifications of these variables to input1.csv, input2.csv and input3.csv respectively.   This means in another case even if I

Hi, I am running rsync as daemon and using rsyncd.conf as follows log file = /etc/rsyncid.log [usda] path=/my_path/ uid = web gid = wweb use chroot = yes read only = no auth users = myuser secrets file = /etc/rsyncd.secrets hosts allow = abc.br.usda.com pqr.br.usda.com xyz.br.usda.com strict modes = no if I rsync data

Dear R forum I have a data.frame as cashflow_df = data.frame(instrument = c("ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC", "ABC", "PQR", "PQR",

Hi, Here i have been an matrix like this, *NAME AGE PALCE TRUE/FALSE* ABC 20 INDIA XYZ 30 FRANCE PQR 40 USA MNO 30 KENIYA DEF 25 AUSTRALIA GTY 34 CANADA BNH 38 JAPAN Here, *TRUE/FALSE *Column containing empty values. So my requirement what is, need to change all the TRUE/FALSE

> maybe there?s a reason for it, but the discrepancy between the > handling of `[` and `$` in deparsing seems odd to me: > > > substitute(a[1], list(a = quote(x * y))) > x * y[1] > > > substitute(a$b, list(a = quote(x * y))) > (x * y)$b > > The former is still executed in the right order (`*` first, then > `[`), which is not what you?d expect looking at the

I am using samba 3.0.7 on Ferdora Core (2.6.5-3) I performed the following operation at the client side mount //abc/abc_share /xyz cd /xyz mkdir pqr where "abc" is the remote server "abc_share" is the remote share "xyz" is the local directory What I want to know is, at the last statement, when an "mkdir" is given, exactly which function at the

Hi, Here i have been a matrix like this, *NAME AGE PALCE TRUE/FALSE* ABC 20 INDIA XYZ 30 FRANCE PQR 40 USA MNO 30 KENIYA DEF 25 AUSTRALIA Here,* TRUE/FALSE* Column containing empty values. So my requirement what is , need to change all the *TRUE/FALSE *column value into "*TRUE*" where *AGE =

Hi, here i have a Max and Min values Min <-3 Max <-6 and also a matrix like this, ABC XYZ PQR ------ ------- ------- 2 4 3 5 4 8 7 1 3 In this i need to check each particular column values are between Max and Min value. If the coulmn value not coming between Max and

Hi guys , samba newbie here ! I have worked hard at trying to get samba run .. but heck!.. it doesn't ! I can see the linux server in my network neighbourhood .. on clicking on it .. I get the user/password box. I entered the user(xyz) password(abc) , and it says ... "account is not authorised to login from this station" I have added user 'xyz' using the smbadduser

Hi list, We have a network with some XP and some Windows 7 computer, we use samba 3.6.6 on debian 6.0.6 from debian-backports. It's a pdc with passdb backend = ldapsam. In our logs there are lots of: ARCServer slapd[1263]: SASL [conn=46778] Failure: realm changed: authentication aborted I found out that at that time this emerges the tcpdump says: 12:59:54.656399 IP client.49551 >

Dear R Forum, I have a data.frame as df = data.frame(date = c("2013-04-15", "2013-04-14", "2013-04-13", "2013-04-12", "2013-04-11"), ABC_f = c(62.80739769,81.04525895,84.65712455,12.78237251,57.61345256), LMN_d = c(21.16794336,54.6580401,63.8923307,87.59880367,87.07693716), XYZ_p = c(55.8885464,94.1358684,84.0089114,98.99746696,64.71083712),

Dear all, how can i search multiple text or string patterns in a text file. i have written the following script but it is for only single searches at a time. how can i get multiple searches e.g "xyz","abc","pqr".....at a time and can save the results to an out file. script:: x<- "abc" z<-NULL;for (i in 1:1235){{if

Hi, Here i have an matrix like this, ABC PQR XYZ MNO ------ ------- ------ -------- 3 6 7 15 2 12 24 15 20 5 1 2 25 50 15 35 i need to get the "MODE" - for each column-wise "VARIANCE" - for

A new version of pqR is now available at pqR-project.org, which fixes several bugs that are also present in the latest R Core patch release (r66002). A number of bugs found previously during pqR development are also unfixed in the latest R Core release. Here is the list of these bugs that are unfixed in r66002 (including documentation deficiencies), taken from the pqR bug fix and documentation

Suharto, If you're interested in performance with subscripting, you might want to look at pqR (pqR-project.org). It has some substantial performance improvements for subscripting over R Core versions. This is especially true for the current development version of pqR (probably leading to a new release in about a month). You can look at a somewhat-stable snapshot of recent pqR development

I have released a new, faster, version of R, which I call pqR (for "pretty quick" R), based on R-2.15.0. Among many other improvements, pqR supports automatic use of multiple cores to perform numerical computations in parallel with other numerical computations, and with the interpretive thread. It also implements a true reference counting scheme to reduce the amount of unnecessary