similar to: reshape -> reshape 2: function cast changed?

Carlos, en principio si sería algo así, sólo que en vez de quedarme con todas las columnas var1 a var4 tuviera sólo 3, ya que en mis datos no hay ningún caso que tenga el valor 1 en más de 3 variables.. Había llegado a una solución (mucho menos elegante que usando reshape), que implicaba un for sobre las filas. Jorge, creo que tu solución me vale. Muchas gracias a los dos.. Saludos El

Buenos días. Hoy ando un poco (o bastante) espeso y no doy con la tecla de una cosa que seguro que es muy simple.. Pongo un ejemplo. var1 <- c(rep(0,3),rep(1,2)) var2 <- c(rep(1,2),0,0,1) var3 <- c(rep(1,2),rep(0,3)) var4 <- c(rep(1,2),rep(0,3)) datos <- data.frame(fila=1:5,var1, var2, var3, var4) datos datos fila var1 var2 var3 var4 1 1 0 1 1 1 2 2 0

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Dear all, I am trying (!!!) to generate pdfs that have 8 plots on one page: df = data.frame( day = c(1,2,3,4), var1 = c(1,2,3,4), var2 = c(100,200,300,4000), var3 = c(10,20,300,40000), var4 = c(100000,20000,30000,4000), var5 = c(10,20,30,40), var6 = c(0.001,0.002,0.003,0.004), var7 = c(123,223,123,412), var8 = c(213,123,234,435), all = as.factor(c(1,1,1,1)))

> library(reshape2) > x = melt(airquality, id=c('month', 'day')) With reshape I can cast with multiple functions: > library(reshape) > cast(x, month+variable~., c(mean,sd)) month variable mean sd 1 5 ozone 23.615385 22.224449 2 5 solar.r 181.296296 115.075499 3 5 wind 11.622581 3.531450 4 5 temp 65.548387

Hi, I ran your code, but the results were not as expected. After I ran the code by "source", it return No id variables; using all as measure variables > p2 and no line or legend is on the graph (as attached) Am I doing anything wrong? John library(ggplot2) library(reshape2) dfm<-melt(df) dfm$variable<-factor(dfm$variable, levels=levels(dfm$variable)[c(2,1,3,4)])

Hello, I would like to reshape a dataframe into an array. This is kind a similar task as Excel performs with a Pivot table. To illustrate it: LOC <- factor(c(1,2,2,3,1,1)) SPEC1 <- c(0,0,23,0,12,11) SPEC2 <- c(1,2,0,0,0,4) df <- data.frame(LOC,SPEC1,SPEC2) # original dataframe a <-

I'm in the middle of my own little intellectual exercise comparing dcast() and reshape() and have successfully stumped myself. I want to melt() a data frame, then dcast() it into a new form. After doing so, I want to duplicate the process using reshape(). So far, I can do the melt and cast require(reshape2) Raw <- data.frame(site = c(1, 1, 1, 1, 2, 2, 2, 2), id =

I seem to be doing something really stupid or missing something really obvious but what? I have a simple three column data.frame that I would like to reshape to wide preferably using reshape2. An example from http://stackoverflow.com/questions/9617348/reshape-three-column-data-frame-to-matrix looked perfect except I wanted a data frame but it seemed okay. I just changed acast to dcast and it

Hi R-users, I have a data set like this (first ten rows): id patient_id date code class eala ID1564262 1562 6.4.2006 12:00 5555 1 NA ID1564262 1562 6.4.2006 12:00 5555 1 NA ID1564264 1365 14.2.2006 14:35 5555 1 50 ID1564265 1342 7.4.2006 14:30 2222 2 50 ID1564266 1648 7.4.200614:30 2222 2 50 ID1564267 1263 10.2.2006 15:45 2222 2 10 ID1564267 1263 10.2.200615:45 3333 3 10 ID1564269 5646

Hi Your approach seems to me rather complicated. I would reshape data before plotting and maybe also change order of levels in resulting variable factor library(reshape2) dfm<-melt(df) dfm$variable<-factor(dfm$variable, levels=levels(dfm$variable)[c(2,1,3,4)]) p2<-ggplot(dfm, aes(x=rep(1:2,4), y=value)) p2+geom_line(aes(linetype=variable))+

Dear all, I am having trouble creating summary tables using aggregate function. given the following table: Var1 Var2 Var3 dummy S1 T1 I 1 S1 T1 I 1 S1 T1 D 1 S1 T1 D 1 S1 T2 I 1 S1 T2 I 1 S1 T2 D 1 S1 T2 D 1 S2

This is my reproducible example: example<-structure(list(SENSOR = structure(1:6, .Label = c("A", "B", "C", "D", "E", "F"), class = "factor"), VALUE = c(270, 292.5, 0, 45, 247.5, 315), DATE = structure(1:6, .Label = c(" 01/01/2010 1", " 01/01/2010 2", " 01/01/2010 3", " 01/01/2010

Hello, I am trying to reformat some data so that it is organized by group in the columns. The data currently looks like this: group X3.Hydroxybutyrate X3.Hydroxyisovalerate ADP 347 4 4e-04 3e-04 5e-04 353 3 5e-04 3e-04 6e-04 359 4 4e-04 3e-04

Dear R people, I have a matrix like this: var1 var2 var3 var4 a1 7.1 7.2 8.1 8.2 a2 10.5 10.6 ... ... a3 b1 b2 b3 b4 c1 c2 ... The matrix row names are "a1", "a2", ...... and the matrix column names are "var1", "var2", "var3" and "var4". Now I want to reshape this data into a

I need to understand how and why dcast() adds NAs to a data frame that contained no missing values. The database table of chemical concentrations has all missing values removed because they cannot contribute to data analyses. The structure of the R data frame of these data have no NA values, and neither does the data frame resulting from applying the reshape2 melt() function to it. However,

Seems like this should be easy but I'm struggling a bit. How do I rearrange a data frame to go from the first one to the second shown below ? State Date lbs TX 200701 400 TX 200702 650 TX 200703 950 TX 200704 1000 FL 200701 200 FL 200702 300 FL 200703 500 FL 200704 333 NJ 200701 409 NJ 200702 308 NJ 200703 300 NJ 200704 800 Date TX FL NJ 200701 400 200 409 200702 650

I've successfully reformatted data frames from long to wide with reshape2, but this time I'm getting errors that I want to understand and resolve. Here's the data frame structure and the results of the melt() and dcast() functions: str(waterchem) 'data.frame': 128412 obs. of 8 variables: $ site : Factor w/ 64 levels "D-1","D-2","D-3",..: 1 1

Hi, I am using R 1.9.1 on on i686 PC with SuSE Linux 9.0. I have a data.frame, e.g.: > myData <- data.frame( var1 = c( 1:4 ), var2 = c (5:8 ) ) If I add a new column by > myData$var3 <- myData[ , "var1" ] + myData[ , "var2" ] everything is fine, but if I omit the commas: > myData$var4 <- myData[ "var1" ] + myData[ "var2" ] the name

Dear mailing list members, I am a new R user, I would like to plot the follewing data var1 <- c(1,2,1,1,2,1,2,1,2,2) var2 <- round(rgamma(10,2,1)/0.1)*0.1 var3 <- c(0,1,0,1,0,0,0,0,1,0) var4 <- c(1,2,2,2,1,1,1,1,1,1) Var <- data.frame(var1,var2,var3,var4) Var <- Var[sort(Var$var1),] tt <- Var$var1+((runif(length(Var$var1))/6)-(0.5/6)) labelname <- c("time 1",