similar to: New flag bit for serialized used by pqR

Currently, I load the RData file then ls() and str(). But loading the file takes too long if the file is big. Most of the time, I only interested what the variables are in the the file and the attributes of the variables (like if it is a data.frame, matrix, what are the colnames/rownames, etc.) I'm wondering if there is any facility in R to help me avoid loading the whole file.

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

There are websites using python to convert a pdb to a pqr. I was wondering if there is a simpler way to do it. We have a protein in pdb format, and want to convert that to a pqr file so that the program apbs can open it. We want to accomplish this conversion in R. Thank you for your help. -- View this message in context: http://n4.nabble.com/Converting-pdb-to-pqr-tp1475426p1475426.html Sent

I am trying to write a program that uses R and takes a pdb file, and converts it to a pqr file. This task is simple generally, using the website, http://pdb2pqr-1.wustl.edu/pdb2pqr/. How do you use R to input a pdb file (that is on hand) into the upload pdb file input, and run the website and give the return file to be a pqr file. Thanks for your help. -- View this message in context:

I have rewritten the R parser in the new version of pqR that I recently released (pqR-2015-09-14, at pqR-project.org). The new version of the parser is much cleaner, is faster (sometimes quite substantially faster), has a better interface to the read-eval-print loop, and provides a better basis for future extensions. The deparser has also been substantially revised in pqR, and is better

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",

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

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"

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

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),

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

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

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

Dmitriy Selivanov (selivanov.dmitriy at gmail.com) wrote: > Consider following example: > > a = matrix(1:2, nrow = 2, dimnames = list(c("row1", "row2"), c("col1"))) > a[1, ] > # 1 > > It returns *unnamed* vector `1` where I would expect named vector. In fact > it returns named vector when number of columns is > 1. > Same issue applicable

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

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

In testing pqR on Solaris SPARC systems, I have found two bugs that are also present in recent R Core versions. You can see the bugs and fixes at the following URLs: https://github.com/radfordneal/pqR/commit/739a4960a4d8f3a3b20cfc311518369576689f37 https://github.com/radfordneal/pqR/commit/339b7286c7b43dcc6b00e51515772f1d7dce7858 The first bug, in nls, is most likely to occur on a 64-bit

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 =

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, my data frame is x<-data.frame(ID=c("abc/def","abc/def/ghi","abc","mno/pqr/st/ab")) I want to split my column ID using "/" as the place to split. How can I do that without telling the code how many sub-columns. I could use nchar(gsub("[^/]","",x$ID)) to get how many "/" are in each row of the column, but could