Hi!
An alternative with 'assign':
for ( i in 71:75) {
setwd(paste("C:/Awork/geneAssociation/removed8samples/neuhausen", i,
sep=""))
temp.df<-read.csv("seg.pr3.csv", head=T)
temp.df$id<-paste0("sn",i,sep="")
assign(paste0("seg",i,sep=""),temp.df)
}
rm(temp.df,i) # Clean up
HTH,
Kimmo
Hello Ding,
try this:
seg <- list()
for ( d in 71:75) {
s <- paste0("seg",d)
sn <- paste0("sn",d)
Dir<-paste("C:/Awork/geneAssociation/removed8samples/neuhausen", i, sep="")
setwd(Dir)
seg[[s]] <- read.csv("seg.pr3.csv", head=T)
seg[[s]]$id <- sn
}
Greetings,
Albrecht
--
Albrecht
Hi Mohammad,
The plot you attached suggests that the underlying distribution may be
a mixture. Is there anything in your data that would explain this,
such as laden/unladen, uphill/downhill, different road surface?
Jim
On Mon, Apr 16, 2018 at 11:31 PM, Mohammad Areida wrote:
> Hi, I do not know
Hi Rui,
Thank you very much!! It worked very well, I am looking into how to use
lapply and do.call.
Ding
-Original Message-
From: Rui Barradas [mailto:ruipbarra...@sapo.pt]
Sent: Monday, April 16, 2018 2:16 PM
To: Ding, Yuan Chun; r-help@r-project.org
Subject: Re: [R] how to write a
Hello,
The following might do it. Without data it's untested.
wd <- function(i){
paste0("C:/Awork/geneAssociation/removed8samples/neuhausen7", i,
"/seg.pr3.csv")
}
seg <- lapply(1:5, function(i) {
DF <-read.csv(wd(i))
DF$id <- paste0("sn7", i)
DF
})
seg <- do.call(rbind, seg
Hi All..,
I need to do the following repetitive jobs:
seg71 <-
read.csv("C:/Awork/geneAssociation/removed8samples/neuhausen71/seg.pr3.csv",
head=T)
seg71$id <-"sn71"
seg72 <-
read.csv("C:/Awork/geneAssociation/removed8samples/neuhausen72/seg.pr3.csv",
head=T)
seg72$id <-"sn72"
seg73 <-
rea
Hi, I do not know how to post in general again, however my csv contains
around 5-250k data Points depending on vehicle/road type and pressure
exerted on geotechnical structures. I have used R to develope histograms of
said csv files and will attach such Picture to you in this mail and the csv
used.
There are plenty of options for reading csv files. For built-in solutions
look at ?read.csv or at read_csv from the package reader.
If the measurements are ordered in columns rather than in rows, reading the
data can be very slow.
HTH
Ulrik
Mohammad Areida schrieb am Mo., 16. Apr. 2018, 13:25:
Hi,
You may use the keyword to google for what you want to do to start with. Slowly
you will learn...this forum is,really helpful but we should provide or show
some effort..all the best!
I like this forum very much and always feel thankful to very helpful and
committed members.
Sent from my S
Dear Mohammad
Perhaps if you showed us what you tried people could offer more helpful
advice? When you say you want to call it forth do you mean you want to
read in the file using read.csv?
Michael
On 16/04/2018 11:23, Mohammad Areida wrote:
Hi, I'm working on R trying to find a distributio
Hi, I'm working on R trying to find a distribution that fits data from a csv
file. The csv contains data on pressure exerted by a certain vehicle in terms
of pressure [kPa] and I have around 3000 data points.
I want to call forth this csv and by using (fitdistr) or if you could recommend
a fun
Hello everybody,
I have encountered a problem with the inverse Gaussian distribution. It is very
likely that it will not work regardless of the data input. I have programmed
this regression and it works fine no matter which distribution the response
comes from.
If you run this example (first tri
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