similar to: To Supporting graphpad prism in R, add external library to poratbleR

1) Definitely yes. They are on CRAN. Just type install.packages( c("dplyr", "tidyr" ) ) at the R console. 2) Don't know, but most likely the answer is yes. Since all R packages on Linux are compiled by R when installed, you either need to activate your virtual machine, compile the packages, and save the state for future use, or you have to build the package library on

Hi Jeff, 1). I have tried install.packages( c("dplyr", "tidyr" ) ) into the r-script file got below error:- > install.packages( c("dplyr", "tidyr" ) ) Installing packages into ?/tmp/1776492876238396447/lib/portableR-master/site-library? (as ?lib? is unspecified) Error in install.packages(c("dplyr", "tidyr")) : This version of R is

I really don't know about this special-purpose distribution of R... you should probably contact the developer. From the error, I wonder whether you followed the instructions on the portableR web page link that you quoted. Do you have the directories referred to there in place? -- Sent from my phone. Please excuse my brevity. On July 25, 2017 7:27:31 AM PDT, Ashish Ranjan <aranjan1645

Hi friends I just started using wine on my Linux-machine. Mostly because I want to switch finally from Windows to Linux on my computer at work. There is just one single application I want to "take with me" and that is "GraphPad Prism" (http://www.graphpad.com/prism/Prism.htm). So I installed wine0.9.20 on my Mandriva2007. Then I used wine to install Prism in its most recent

UseRs, When doing some data manipulations using the tidyverse, I am repeatedly getting the same error message in now three separate situations. I can write up a reproducible example, but want to lay out the high-level issues in case someone recognizes exactly what is happening here. The error is: Error in mut_env_parent(overscope$.top_env, lexical_env) : object 'rlang_mut_env_parent'

This sounds an awful lot like a bug. Read the Posting Guide to know what to do about bugs. And delaying making the reprex is _always_ a bad idea. -- Sent from my phone. Please excuse my brevity. On August 14, 2017 7:26:32 AM PDT, "Szumiloski, John" <John.Szumiloski at bms.com> wrote: >UseRs, > >When doing some data manipulations using the tidyverse, I am repeatedly

Thanks for the feedback Jeff. Before I pursue a bug report, let me give a full example: ###### begin console output R version 3.4.1 (2017-06-30) -- "Single Candle" Copyright (C) 2017 The R Foundation for Statistical Computing Platform: i386-w64-mingw32/i386 (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions.

Thank you very much for the support. I have just used the reshape library and my problem was solved. Kind regards, Peter -----Original Message----- From: Jeff Newmiller [mailto:jdnewmil at dcn.davis.ca.us] Sent: 10 July 2017 03:52 PM To: r-help at r-project.org; Mangalani Peter Makananisa; r-help at r-project.org Cc: Vito Ricci (vito_ricci at yahoo.com) Subject: Re: [R] dplyr help I am

Hi everyone: I?m one of the interns at RStudio this summer working on a project that helps teachers grade student code. I found an unexpected behaviour with the |==| operator when comparing |quote|d expressions. Example 1: |u <- quote(tidyr::gather(key = key, value = value, new_sp_m014:newrel_f65, na.rm = TRUE)) s <- quote(tidyr::gather(key = key, value = value,

Another approach: ######## library(tidyr) L <- list( A = data.frame( x=1:2, y=3:4 ) , B = data.frame( x=5:6, y=7:8 ) ) D <- data.frame( Type = names( L ) , stringsAsFactors = FALSE ) D$data <- L unnest(D, data) #> Type x y #> 1 A 1 3 #> 2 A 2 4 #> 3 B 5 7 #> 4 B 6 8 ######## On Wed, 2 May 2018, Eivind K.

> On Aug 14, 2017, at 8:37 AM, Szumiloski, John <John.Szumiloski at bms.com> wrote: > > Thanks for the feedback Jeff. Before I pursue a bug report, let me give a full example: > > ###### begin console output > > R version 3.4.1 (2017-06-30) -- "Single Candle" > Copyright (C) 2017 The R Foundation for Statistical Computing > Platform:

On Wed, May 2, 2018 at 11:53 AM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote: > Another approach: > > ######## > library(tidyr) > L <- list( A = data.frame( x=1:2, y=3:4 ) > , B = data.frame( x=5:6, y=7:8 ) > ) > D <- data.frame( Type = names( L ) > , stringsAsFactors = FALSE > ) > D$data <- L

Dear all, I have a question with regard to the use of hclust. I would like to be able to specify my own distance matrix instead of asking R to compute the distance matrix for me. It is computationally easier for me this way. My question is: How can I get hclust to accept this? Thanks, Ranjan -- *************************************************************************** Ranjan

I am pretty sure that this is not a question about dplyr... it is a question about tidyr. Look at the help file ?tidyr::spread. If I understand your question (I may not, because you gave no example of input/output data), the answer is no, the column names come from the column named by the key parameter and the values that fill those columns come from the column named by the value parameter.

Thanks! Yes, however, this seems a bit wasteful. Just wondering if there are other, more efficient options possible. Best wishes, Ranjan On Thu, 29 Mar 2018 22:20:19 -0400 Boris Steipe <boris.steipe at utoronto.ca> wrote: > If one is equal to the reverse of another, keep only one of the pair. > > B. > > > > > On Mar 29, 2018, at 9:48 PM, Ranjan Maitra

Dear All, I need some help arranging data that was imported. The imported data frame looks something like this (the actual file is huge, so this is example data) DF: IDKey X1 Y1 X2 Y2 X3 Y3 X4 Y4 Name1 21 15 25 10 Name2 15 18 35 24 27 45 Name3 17 21 30 22 15 40 32 55 I would like to create a new data frame with the following NewDF: IDKey X Y Name1 21 15 Name1

Dear friends, Is there a way to read data files written in lisp into R? Here is the file: https://archive.ics.uci.edu/ml/machine-learning-databases/university/university.data I would like to read it into R. Any suggestions? Thanks very much in advance for pointers on this and best wishes, Ranjan -- Important Notice: This mailbox is ignored: e-mails are set to be deleted on receipt. Please

Dear list, I have been using the Rmath library for quite a while: in the current instance, I am calling dnt (non-central t density function) repeatedly for several million. When the argument is small, I get the warning message: full precision was not achieved in 'pnt' which is nothing unexpected. (The density calls pnt, if you look at the function dnt.) However, to have this happen a

Jeff, I wanted to let you know that your function is faster than generating the directional circular permutations and weeding. Here is the time for n = 10. I compared with just doing the permutations, there is no point in proceeding further with the weeding since it is slower at the start itself. system.time(directionless_circular_permutations(10)) user system elapsed 1.576 0.000

I don't know if this is more efficient than enumerating with distinct directions and weeding... it seems kind of heavyweight to me: ####### library(gtools) directionless_circular_permutations <- function( n ) { v <- seq.int( n-1 ) ix <- combinations( n-1, 2 ) jx <- permutations( n-3, n-3 ) x <- lapply( seq.int( nrow( ix ) ) , function( i ) {