similar to: how to make row.names based on column1 with duplicated values

On Wed, 28 Feb 2018, Stephen HonKit Wong wrote: > Dear All, > Suppose I have a dataframe like this with many thousands rows all with > different names: > data.frame(gene=c("a","b","c","d","c","d","c","f"),value=c(20,300,48,55,9,2,100,200)), > > I want to set column "gene" as row.names, but

Hi... I have a dataframe with n columns and n rows. I need to find how many rows contains zero raw read count across all column. Thanks -- *Yogesh Gupta* *Postdoctoral Researcher* *Department of Biological Science* *Seoul National University* *Seoul, South Korea* [[alternative HTML version deleted]]

You can enforce these assumptions by sorting on multiple columns, which leads to na.locf(df1[ order(df1$ID,df1$Value), ]) On Mon, Jan 8, 2018 at 4:19 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote: > Yes, you are right if the IDs are always sequentially-adjacent and the > first non-NA value appears in the first record for each ID. > -- > Sent from my phone. Please

Hi With the example, na.locf seems to be the easiest way. > library(zoo) > na.locf(df1) ID ID_2 Firist Value 1 a aa TRUE 2 2 a ab FALSE 2 3 a ac FALSE 2 4 b aa TRUE 5 5 b ab FALSE 5 Cheers Petr > -----Original Message----- > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Jeff > Newmiller > Sent: Monday, January

"Enforce" is overstating it... results will differ if there are no non-NA values for a given ID, and there is a potential further discrepancy if there are multiple non-NA values. But these issues were not identified by the OP, so may not be relevant in their case. -- Sent from my phone. Please excuse my brevity. On January 8, 2018 6:41:33 AM PST, Eric Berger <ericjberger at

Hi Duncan The simples spreadsheet is: Put a name in the cell, let say "a1" Put number e.g. 1 below "a1" Copy the number to enough rows Select this column and press ctrl-c result is > temp<- read.delim("clipboard") > str(temp) 'data.frame': 1513 obs. of 1 variable: $ a1: Factor w/ 2 levels "1","a1": 1 1 1 1 1 1 1 1 1 1 ...

Dear all I am struggling to fit data which form something like CDF by lognorm. Here are my data: proc <- c(0.9, 0.84, 0.5, 0.16, 0.1) size <- c(0.144, 0.172, 0.272, 0.481, 0.583) plot(size, proc, xlim=c(0,1), ylim=c(0,1)) fit<-nls(proc~SSfpl(size, 1, 0, xmid, scal), start=list(xmid=0.2, scal=.1)) lines(seq(0,1,.01), predict(fit, newdata=data.frame(sito=seq(0,1,.01))), col=2) I tried

Dear all I have 3 questions. Due to some reason I switched from Vista to Ubuntu on home PC. I was used to start with Rgui.exe. However I am not able to find it under Ubuntu and R starts as terminal (probably Rterm). Question 1. Is Rgui.exe available on linux? In Windows doc folder I can find manuals, however I did not find doc folder in Ubuntu. I found somewhere that manuals need to be

Yes, you are right if the IDs are always sequentially-adjacent and the first non-NA value appears in the first record for each ID. -- Sent from my phone. Please excuse my brevity. On January 8, 2018 2:29:40 AM PST, PIKAL Petr <petr.pikal at precheza.cz> wrote: >Hi > >With the example, na.locf seems to be the easiest way. >> library(zoo) > >> na.locf(df1) > ID

Hi Petr; Thanks for your reply. It is much appreciated. A small example is given below for 4 independent and 4 dependent variables only. The values given are regression coefficients.I have looked ggplot documents before writing to you. Unfortunately, I could not figure out as my experience in ggplot is ignorable Regards. Greg y1 y2 y3 y4 x1 -0.19 0.40 -0.06 0.13 x2 0.45 -0.75 -8.67 -0.46 x3

Hi Petr; Thanks so much. Exactly this is what I need. I will play to change color and so on but this backbound is perfect to me. I do appreciate your help and support. Regards, Greg On Thu, Feb 8, 2018 at 1:29 PM, PIKAL Petr <petr.pikal at precheza.cz> wrote: > Hi > > I copied your values to R, here it is > > > > > dput(temp) > > > > temp <-

Hi > -----Original Message----- > From: Robert Baer [mailto:rbaer at atsu.edu] > Sent: Wednesday, August 16, 2017 3:04 PM > To: PIKAL Petr <petr.pikal at precheza.cz>; Duncan Murdoch > <murdoch.duncan at gmail.com> > Cc: r-devel at r-project.org > Subject: Re: [Rd] strange behaviour read.table and clipboard > > You said, "put a name in the cell".

Hi Petr; I would like to get a plot with names as they are in the original file. They are chemical names and I have 733 in the my file. For example, let me give to chemical names "*2-hydroxybutyrate/2-hydroxyisobutyrate*" and "*palmitoyl-arachidonoyl-glycerol (16:0/20:4) [1]**" .So, what should I put [c(2,3,1)] part in the command: iris$MySpecies<-factor(iris$Species,

Dear all I used to transfer data from excel to R by simple ctrl-c and read.delim("clipboard") construction. I know it is a bad practice but it is easy and for quick exploratory work it is OK. However after changing to new R devel few days ago I encountered weird behaviour. I tried one or two columns. In case of 2 columns, header is repeated after 526 items >

Hello, I am trying to use varcomp to decompose the variance across multiple nested levels on a lme object. I am able to successfully do this and when I view the varcomp object I can see the individual values / estimates for the variance at different levels. However, I want to be able to extract each of them separately, as I need to build a confidence interval using bootstrapping on the sample

Hi all; I have 733 discrete categories that will go on y-axis in ggplot2. I used the following command to put the name of x-axis. scale_x_discrete (limits = c("SI", "HOMAIR", "AIR","HOMAB","SG","DI","FI","FG")) Since there are only 8 categories on x it was easy to do. Is there any way to do the same for 733 discrete

Dear friends - I have a data.frame with "," instead of "." and found the discussion http://r.789695.n4.nabble.com/How-to-replace-all-commas-with-semicolon-in-a-string-tt4721187.html#a4721192 so copying the code of Ulrik(I hope:-)) I tried (making some data) AX <-

Upon closer examination I see that you are not using the split version of df1 as I usually would, so here is a reproducible example: #---- df1 <- read.table( text= "ID ID_2 Firist Value 1 a aa TRUE 2 2 a ab FALSE NA 3 a ac FALSE NA 4 b aa TRUE 5 5 b ab FALSE NA ", header=TRUE, as.is=TRUE ) sdf <- split( df1, df1$ID ) # note the extra [ 1 ]

I did the same transition, facing the same issues, so I settled for installation of RKWard. This pretty much reproduces my previous experience with Tinn-R and the Rgui. HTH Ruben ________________________________ Ruben H. Roa-Ureta, Ph. D. Senior Scientist, Center for Environment and Water, Marine Studies Section, King Fahd University of Petroleum and Minerals, KFUPM Box 1927, Dhahran 31261,

How about proc <- c(0.9, 0.84, 0.5, 0.16, 0.1) size <- c(0.144, 0.172, 0.272, 0.481, 0.583) plot(size, proc, xlim=c(0,1), ylim=c(0,1)) fit<-nls(proc~plnorm(size, log(xmid), sdlog, lower=FALSE), start=list(xmid=0.2, sdlog=.1)) summary(fit) lines(fitted(fit)~size) -pd > On 10 Jul 2017, at 16:27 , PIKAL Petr <petr.pikal at precheza.cz> wrote: > > Dear all > > I am