Hi
Isn't melt just what you want?
melt(mydt)
Petr
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of Abraham Mathew
> Sent: Tuesday, March 18, 2014 1:59 AM
> To: r-help@r-project.org (r-help@r-project.org)
> Subject: [R] Resh
put)
# place
#people school home sport beach
# Marc 2 4 0 0
#Joe 0 3 1 5
#Mary 4 0 0 0
A.K.
From: sylvain willart
To: arun
Cc: R help
Sent: Saturday, April 13, 2013 5:41 PM
Subject: Re: [R] Reshaping Data for
Wow !
so many thanks Arun and Rui
works like a charm
problem solved
2013/4/13 arun
> Hi,
> Try this;
> library(reshape2)
> res<-dcast(Input,people~place,value.var="time")
> res[is.na(res)]<-0
> res
> # people beach home school sport
> #1Joe 53 0 1
> #2 Marc 04
Hello,
With the following the order of both rows and columns will be different
than the order of your example output, but the table is basically the same.
xtabs(time ~ people + place, data = Input)
Hope this helps,
Rui Barradas
Em 13-04-2013 22:03, sylvain willart escreveu:
Hello
I have
Hi,
Try this;
library(reshape2)
res<-dcast(Input,people~place,value.var="time")
res[is.na(res)]<-0
res
# people beach home school sport
#1 Joe 5 3 0 1
#2 Marc 0 4 2 0
#3 Mary 0 0 4 0
#or
xtabs(time~.,Input)
# place
#people beach home s
Wonderful! thanks, Rui!
AC
On Tue, Jul 24, 2012 at 10:01 PM, Rui Barradas wrote:
> Hello,
>
> Try the following.
>
>
> # We are going to use this twice
> sl <- split(long, long$id)
>
> # Remove groups with only one row
> l2 <- lapply(sl, function(x) if(nrow(x) > 1) x)
> l2 <- do.call(rbind, l2)
On 2012-07-24 22:01, Rui Barradas wrote:
Hello,
Try the following.
# We are going to use this twice
sl <- split(long, long$id)
# Remove groups with only one row
l2 <- lapply(sl, function(x) if(nrow(x) > 1) x)
l2 <- do.call(rbind, l2)
l2
# Create a new variable
l3 <- lapply(sl, function(x) cb
Hello,
Try the following.
# We are going to use this twice
sl <- split(long, long$id)
# Remove groups with only one row
l2 <- lapply(sl, function(x) if(nrow(x) > 1) x)
l2 <- do.call(rbind, l2)
l2
# Create a new variable
l3 <- lapply(sl, function(x) cbind(x, NEW_VARIABLE=seq_len(nrow(x
l3
Hello All,
Tried some more Internet searches and came to the conclusion that one probably
does need to create a "timevar" before reshaping from long to wide. Below is
some code that creates the "timevar" and transposes the data.
connection <- textConnection("
005 1 Gemcitabine
005 2 Erlotinib
Erlotinib, Paclitaxel"
instead of "Gemcitabine, Paclitaxel, Erlotinib". That's what I mean when I say
I want the columns in alphabetical order.
Thanks,
Paul
--- On Tue, 3/20/12, R. Michael Weylandt wrote:
> From: R. Michael Weylandt
> Subject: Re: [R] Reshaping data
If I understand you right,
library(reshape2)
dcast(melt(TestData, id.var = "Subject", measure.var = "Drug"), Subject ~ value)
Michael
On Tue, Mar 20, 2012 at 9:50 AM, Paul Miller wrote:
> Hello All,
>
> I was wondering if it's possible to reshape data from long to wide in R
> without using a "
On 09/08/2011 12:02 AM, dadrivr wrote:
Hi,
I'm trying to reshape my data set from wide to tall format for multilevel
modeling. Unfortunately, the function I typically use (make.univ from the
multilevel package) does not appear to work with unbalanced data frames,
which is what I'm dealing with.
The terminology (melt, cast, recast) just isn't intuitive to me; but I
understand how to use melt now.
Thanks!
Justin Haynes wrote:
>
> look at the melt function in reshape, specifically ?melt.data.frame
>
> require(reshape)
> Raw.melt<-melt(RawData,id.vars='Year',variable_name='Month')
>
>
look at the melt function in reshape, specifically ?melt.data.frame
require(reshape)
Raw.melt<-melt(RawData,id.vars='Year',variable_name='Month')
there is an additional feature in the melt function for handling na values.
names(Raw.melt)[3]<-'CO2'
> head(Raw.melt)
Year MonthCO2
1 1958
Dnia 2011-06-15, o godz. 12:05:01
Jim Lemon napisał(a):
> On 06/15/2011 06:46 PM, filip.biele...@rega.kuleuven.be wrote:
> > Dear,
> >
> > I have a data frame melted from a list of matrices (melt from
> > reshape package), then I impute some missing values and then want
> > to tabulate the data a
On Tue, Jul 20, 2010 at 3:30 AM, John Kane wrote:
> Assuming your data is in data.frame xx
>
>
> library(reshape)
> mm1 <- melt(xx, id=c("ID"))
> cast(mm1, ID ~ variable )
> =
Hi Dennis,
Thanks for the answer, it works perfectly for two time intervals, but
if I add a third interval like this:
ID begin_t1end_t1 begin_t2end_t2
begin_t3end_t3
Thomas 11/03/0413/05/0604/02/071
Assuming your data is in data.frame xx
library(reshape)
mm1 <- melt(xx, id=c("ID"))
cast(mm1, ID ~ variable )
=
--- On Mon, 7/19/10, Thomas Jensen wrote:
> From: Thomas Jens
Hi:
Here's one solution using function reshape() in the stats package (adapted
from an R-help solution by Thomas Lumley on Nov. 26, 2002):
d <- read.table(textConnection("
+ ID begin_t1end_t1 begin_t2
end_t2
+ Thomas 11/03/0413/05/06
ilto:r-help-boun...@r-project.org] On Behalf Of Mia Bengtsson
>> Sent: Friday, May 21, 2010 3:39 AM
>> To: Dennis Murphy; Henrique Dallazuanna
>> Cc: r-help@r-project.org
>> Subject: Re: [R] reshaping data
>>
>> Thank you Dennis and Henrique for your help!
>>
>&g
> -Original Message-
> From: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of Mia Bengtsson
> Sent: Friday, May 21, 2010 3:39 AM
> To: Dennis Murphy; Henrique Dallazuanna
> Cc: r-help@r-project.org
> Subject: Re: [R] reshaping data
Thank you Dennis and Henrique for your help!
Both solutions work! I just need to find a way of removing the empty "cells"
from the final "long" dataframe since they are not NAs.
Maybe there is an easier way of doing this of the data is not treated as a
dataframe? The original data file that is
Try this:
x_long <- reshape(x, direction = 'long', varying = 2:4, sep = '', idvar =
'V1', timevar = 'V')
subset(x_long[order(x_long$V1),], V != "")
On Thu, May 20, 2010 at 2:13 PM, Mia Bengtsson wrote:
> Hello,
>
> I am a relatively new R-user who has a lot to learn. I have a large dataset
> tha
On Mar 31, 2010, at 2:37 PM, Kim Jung Hwa wrote:
Thanks Henrique and Stephan for your reply!
Henrique, I'm planning to do some arthitmetic operations on tranformed
(matrix) data and then would like to convert it back to original
format (as
a data frame)... is there an equivalent easy command
Try:
as.data.frame(with(x, tapply(Val, list(Var1, Var2), sum)))
On Wed, Mar 31, 2010 at 3:37 PM, Kim Jung Hwa wrote:
> Thanks Henrique and Stephan for your reply!
>
> Henrique, I'm planning to do some arthitmetic operations on tranformed
> (matrix) data and then would like to convert it back t
Actually, apart from melt() in reshape package.
On Wed, Mar 31, 2010 at 2:37 PM, Kim Jung Hwa wrote:
> Thanks Henrique and Stephan for your reply!
>
> Henrique, I'm planning to do some arthitmetic operations on tranformed
> (matrix) data and then would like to convert it back to original format (
Thanks Henrique and Stephan for your reply!
Henrique, I'm planning to do some arthitmetic operations on tranformed
(matrix) data and then would like to convert it back to original format (as
a data frame)... is there an equivalent easy command for this too? Thanks,
On Wed, Mar 31, 2010 at 2:26 PM
Hi Kim,
look at the reshape() command with direction="wide". Or at the reshape
package.
HTH,
Stephan
Kim Jung Hwa schrieb:
Hi All,
Can someone help me reshape following data:
Var1 Var2 Val
A X 1
A Y 2
A Z 3
B X 4
B Y 5
B Z 6
to some kind of matrix/tabular format (preferably as a matrix),
Try this:
xtabs(Val ~ Var1 + Var2, data = x)
On Wed, Mar 31, 2010 at 3:23 PM, Kim Jung Hwa wrote:
> Hi All,
>
> Can someone help me reshape following data:
>
> Var1 Var2 Val
> A X 1
> A Y 2
> A Z 3
> B X 4
> B Y 5
> B Z 6
>
> to some kind of matrix/tabular format (preferably as a matrix), may b
You can use this instead:
with(do.call(rbind, df.list), tapply(Score, list(Date, Show, Time), invisible))
On Wed, Jan 20, 2010 at 3:02 PM, Tony B wrote:
> Thank you for taking the time to reply Henrique. Although your
> solution does take away the zeroes and replaces them with NA's (which
> i pr
Thank you for taking the time to reply Henrique. Although your
solution does take away the zeroes and replaces them with NA's (which
i prefer), it unfortunately seems to reduce all of the other scores to
just '1':
> x <- with(do.call(rbind, df.list), tapply(Score, list(Date, Show, Time),
> length
Try with tapply:
with(do.call(rbind, df.list), tapply(Score, list(Date, Time, Show), length))
On Wed, Jan 20, 2010 at 10:20 AM, Tony B wrote:
> Dear all,
>
> Lets say I have several data frames as follows:
>
>> set.seed(42)
>> dates <- as.Date(c("2010-01-19", "2010-01-20"))
>> times <- c("09:30
Try this;
with(x, data.frame(Case = rep(Case, (Endyear - Startyear) + 1),
Year = unlist(mapply(seq, Startyear, Endyear
On Tue, Nov 24, 2009 at 4:14 PM, Joseph Magagnoli wrote:
> Hi all,
> I have a dataframe that has one observation per case.
> for example:
>
> Case
Dear Chuck, John, Vikas, and useRs,
thank you very much for your great suggestions.
I received three replies providing different ways to reshape my original
data.frame (original question at the bottom). There are however some
discrepancies in their results (most likely because I didn't explain my
> # 2. create one new row for each case in level.1 and level.2
>
> # the new reshaped data.frame would should look like this:
>
> # indiv factorcovar case.id
> # A level.1 4.6141051
> # A level.1 4.6141052
> # A level.2 31.0644051
> # A level.2 31.064405
Here is a very clumsy way to do it but I think it
works
fact1 <- rep("level.1", length(mydat[,1]))
fact2 <- rep("level.2", length(mydat[,1]))
lels <- c(fact1,fact2)
nams <- c("indiv", "case.id", "covar")
set1 <- mydat[, c(1,2,3)] ; names(set1) <- nams
set2 <- mydat[,c(1, 4,5)] ; names(set2) <-
On 2/20/2008 1:14 PM, ahimsa campos-arceiz wrote:
> Dear all,
>
> I'm having a few problems trying to reshape a data frame. I tried with
> reshape{stats} and melt{reshape} but I was missing something. Any help is
> very welcome. Please find details below:
>
> #
> #
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