From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Jeff Newmiller
Sent: Wednesday, May 22, 2013 5:27 PM
To: Ye Lin; R help
Subject: Re: [R] group data based on row value
dat$group <- cut( dat
dat$group <- cut( dat$Var, breaks=c(-Inf,0.1, 0.6,Inf))
levels(dat$group) <- LETTERS[1:3]
---
Jeff NewmillerThe . . Go Live...
DCN:Basics: ##.#. ##.#. Live Go...
Hi,
Try:
dat<- read.table(text="
Var
0
0.2
0.5
1
4
6
",sep="",header=TRUE)
res1<-within(dat,group<-factor(findInterval(Var,c(-Inf,0.1,0.6),rightmost.closed=TRUE),labels=LETTERS[1:3]))
res1
# Var group
#1 0.0 A
#2 0.2 B
#3 0.5 B
#4 1.0 C
#5 4.0 C
#6 6.0 C
#or
res2<-with
hey, I want to divide my data into three groups based on the value in one
column with group name.
dat:
Var
0
0.2
0.5
1
4
6
I tried:
dat <- cbind(dat, group=cut(dat$Var, breaks=c(0.1,0.6)))
But it doesnt work, I want to group those <0.1 as group A, 0.1-0.6 as group
B, >0.6 as group C
Thanks fo
x1$group<- paste0("Key",i);x1}))
res
# ID Value group
#1 AL1 1 Key1
#2 AL2 2 Key1
#3 CA1 3 Key2
#4 CA4 4 Key2
A.K.
- Original Message -
From: Ye Lin
To: Rui Barradas
Cc: R help
Sent: Monday, April 15, 2013 11:50 AM
Subject: Re: [R] group data
Wha
What if more generally that the group name doest have anything to do with
the ID, eg. for ID=AL1 and AL2, I want to name the group as "Key1", how can
I approach that?
Thanks,
On Thu, Apr 11, 2013 at 11:54 AM, Rui Barradas wrote:
> Hello,
>
> Try the following.
>
>
> dat <- read.table(text = "
I think I just misinterpret~Thanks for your help~
On Thu, Apr 11, 2013 at 11:54 AM, Rui Barradas wrote:
> Hello,
>
> Try the following.
>
>
> dat <- read.table(text = "
>
> ID Value
> AL1 1
> AL2 2
> CA1 3
> CA4 4
> ", header = TRUE, stringsAsFactors = FALSE)
>
> dat$State <- substr(dat$ID
Hi,
dat1<- read.table(text="
ID Value
AL1 1
AL2 2
CA1 3
CA4 4
",sep="",header=TRUE,stringsAsFactors=FALSE)
dat2<- dat1
dat1$State<-gsub("\\d+","",dat1$ID)
dat1
# ID Value State
#1 AL1 1 AL
#2 AL2 2 AL
#3 CA1 3 CA
#4 CA4 4 CA
#or
library(stringr)
dat2$State<-s
Thanks!
But What if I have a very large data with 1000+rows, anyway to identify all
"AL1" and "AL2" under "ID" and mark them as "AL" under new column "State"?
Thanks.
On Thu, Apr 11, 2013 at 11:54 AM, Rui Barradas wrote:
> Hello,
>
> Try the following.
>
>
> dat <- read.table(text = "
>
> ID
Hello,
Try the following.
dat <- read.table(text = "
ID Value
AL1 1
AL2 2
CA1 3
CA4 4
", header = TRUE, stringsAsFactors = FALSE)
dat$State <- substr(dat$ID, 1, 2)
Note that this dependes on having State being defined by the first two
characters of ID.
Hope this helps,
Rui Barradas
Hey,
I have a dataset and I want to identify the records by groups for further
use in ggplot.
Here is a sample data:
ID Value
AL1 1
AL2 2
CA1 3
CA4 4
I want to identify all the records that in the same state (AL1 AND A2),
group them as "AL", and do the same for CA1 and CA4. How can I have
5)
# year decade
#1 1598 1590-1600
#2 1599 1590-1600
#3 1600 1590-1600
#4 1601 1600-1610
#5 1602 1600-1610
A.K.
- Original Message -
From: catalin roibu
To: r-help@r-project.org
Cc:
Sent: Sunday, April 7, 2013 3:47 AM
Subject: [R] group data in classes
Hello all!
I have a problem to
brs <- seq(1590,2000,by=10)
lbs <- paste(brs[-length(brs)],brs[-1],sep="-")
y <- cut(x,breaks=brs,labels=lbs) # Where "x" is your data vector.
grpd <- data.frame(year=x,decade=y)
head(grpd)
yeardecade
1 1598 1590-1600
2 1599 1590-1600
3 1600 1590-1600
4 1601 1600-1610
5 1602 1600-1610
6 16
Hello all!
I have a problem to group my data (years) in 10 years classes. For example
for year
year decade
1598 1590-1600
1599 1590-1600
1600 1590-1600
1601 1600-1610
---
my is like this>
[1] 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610 1611
1612
[16] 1613 1614 1615
Actually to get exactly what I want I need to add
no.dimnames(AvgDemand )
where
no.dimnames <- function(a) {
## Remove all dimension names from an array for compact printing.
d <- list()
l <- 0
for(i in dim(a)) {
d[[l <- l + 1]] <- rep("", i)
}
di
Hello,
the more general thing I'd like to learn here is how to compute Function of
Data on the basis of grouping determiend by n variables.
In terms of the reason why I am interested in this, I need to compute the
average of my data based on the value of the month and day across years. I
have com
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