search for: colwise

Hi, I am confused by results from: > ddply(aa, names(aa), colwise(sum)) I thought ddply was just calling colwise(sum)() with each column. However ddply() returns a 13 x 5 result !! The general result I expected is similar to that of apply() , or using colwise(sum)() alone. Shouldn't ddply() produce the same ? Thanks in advance for your help,...

...re("plyr")) suppressMessages(require(ez)) source.file <- file.path(path.expand("~"), "test-data.csv") data <- read.csv(source.file, stringsAsFactors = TRUE) data$Participant <- as.factor(data$Participant) summary(data) colwise(class)(data) colwise(mode)(data) colwise(mean)(data[3:4]) colwise(sd)(data[3:4]) ops <- options(contrasts = c('contr.sum', 'contr.poly')) ezANOVA(data, dv = .(Measure.2), wid = .(Participant), within = .(Factor), type = 3, detailed = T)...

...ound(100*x, 1) I want to apply the pct function to only the numeric variables so that the proportions are computed to percentages, and retain all the columns: c1 c2 x1 x2 1 A Y 52.3 92.5 2 B Y 69.2 76.2 3 C N 23.1 36.2 4 C N 11.6 44.6 I've been approaching it with the ddply and colwise functions from the plyr package, but in that case each I need each row to be its own group and retain all columns. Am I on the right track? If not, what's the best way to do this? Thanks in advance, M. L.

...ormation about where errors within your data - hopefully this will make problems easier to track down Speed-ups * massive speed ups for splitting large arrays * fixed typo that was causing a 50% speed penalty for d*ply * rewritten rbind.fill is considerably (> 4x) faster for many data frames * colwise about twice as fast Bug fixes: * daply: now works when the data frame is split by multiple variables * aaply: now works with vectors * ddply: first variable now varies slowest as you'd expect plyr 0.1.5 (2008-02-23) --------------------------------------------------- * colwise now accepts...

...ormation about where errors within your data - hopefully this will make problems easier to track down Speed-ups * massive speed ups for splitting large arrays * fixed typo that was causing a 50% speed penalty for d*ply * rewritten rbind.fill is considerably (> 4x) faster for many data frames * colwise about twice as fast Bug fixes: * daply: now works when the data frame is split by multiple variables * aaply: now works with vectors * ddply: first variable now varies slowest as you'd expect plyr 0.1.5 (2008-02-23) --------------------------------------------------- * colwise now accepts...

...ing more files saving it as a .txt/.csv and then reading that in. I want to read in 3 columns e.g. 1 2.5 3.4 1 2.3 3.1 1 2.6 3.9 2 2.9 2.8 2 2.6 2.9 2 2.7 2.9 3 2.3 3.3 3 2.4 3.0 3 2.7 3.2 I thought I could use scan() but don't know how to extend it to multiple columns? I thought about using colwise (plyr) but think I am making this more complicated than it probably should be! Is there an easy way to do this? Any ideas gratefully received, Paul -- View this message in context: http://r.789695.n4.nabble.com/Read-in-dataset-without-saving-it-tp2248495p2248495.html Sent from the R help mailin...

I want to apply a more complicated function than what I use in my example, but the idea is the same: Suppose you have a data frame named x and you want to a function applied to each variable, we'll just use the quantile function for this example. I'm trying all sorts of apply functions, but not having luck. My best guess would be: sapply(x, FUN=quantile) -- View this message in

Dear R users, I have a dataframe which consists of variables of type numeric and factor. What is the easiest way to split up the dataframe to two dataframe which contain all variables of the type numeric resp. factors? Thank you very much for your efforts in advance! Best, Martin

...=T) head(results1,1) # id var1 var2 # 1 0m11 30.79 32.27 library(data.table) mydt <- data.table(myData) setkey(mydt,id) results2 <- mydt[,lapply(.SD,mean,na.rm=TRUE),by=id] head(results2,1) # id var1 var2 # [1,] 0m11 30.84 32.27 library(plyr) results3 <- ddply(myData,.(id),colwise(mean),na.rm=TRUE) head(results3,1) # id var1 var2 # 1 0m11 30.84 32.27 > sessionInfo() R version 2.14.0 (2011-10-31) Platform: i386-pc-mingw32/i386 (32-bit) locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 LC...

I'm trying to use ddply to compute summary statistics for many variables splitting on the variable site. however, it seems to work fine for mean() but if i use max() or min() things fall apart. whats going on? test.set<-data.frame(site=1:10,x=.Random.seed[1:100],y=rnorm(100)) means<-ddply(test.set,.(site),mean) means site x y 1 1 -97459496 -0.14826303 2

Hi All, Year Area Q Bin FD I have a large dataset I need to re-structure. It looks something like this: 2000 1 1 5 0 2000 1 1 10 1 2000 1 1 15 23 2000 1 1 20 12 2000 1 1 25 1 2000 2 1 5 1 2000 2 1 10 3 2000 2 1 15 15 2000 2 1 20 11 2000 2 1 25 3 2000 1 2 5 0 2000 1 2 10 1 2000 1 2 15 23 2000 1 2 20 12 2000 1 2 25 1 2000 2 2 5 1 2000 2 2 10 3 2000 2 2 15 15 2000 2 2 20 11

Dear all, Without a loop, I would like transform 3 numeric vectors empty of 0/1 of same length Vec1 : transform 1 to A and 0 to "" Vec2 : transform 1 to B and 0 to "" Vec3 : transform 1 to C and 0 to "" to obtain only 1 vector Vec who is the paste of the 3 vectors (Ex : ABC, BC, AC, AB,...) Any idea ? Thank you for your help -- Michel ARNAUD

...n up at http://groups.google.com/group/manipulatr. Version 1.6 ------------------------------------------------------------------------------ * documentation improved using new features of `roxygen2` * fixed namespacing issue which lead to lost labels when subsetting the results of `*lply` * `colwise` automatically strips off split variables. * `rlply` now correctly deals with `rlply(4, NULL)` (thanks to bug report from Eric Goldlust) * `rbind.fill` tries harder to keep attributes, retaining the attributes from the first occurrence of each column it finds. It also now works with variabl...

How can one simplify the folowing? t$aum[is.na(t$aum)] = 0; t$aum.core[is.na(t$aum.core)] = 0 t$num[is.na(t$num)] = 0; t$num.core[is.na(t$num.core)] = 0 Thank you. -- View this message in context: http://n4.nabble.com/Applying-a-transformation-to-multiple-data-frame-columns-tp1457641p1457641.html Sent from the R help mailing list archive at Nabble.com.

...n up at http://groups.google.com/group/manipulatr. Version 1.6 ------------------------------------------------------------------------------ * documentation improved using new features of `roxygen2` * fixed namespacing issue which lead to lost labels when subsetting the results of `*lply` * `colwise` automatically strips off split variables. * `rlply` now correctly deals with `rlply(4, NULL)` (thanks to bug report from Eric Goldlust) * `rbind.fill` tries harder to keep attributes, retaining the attributes from the first occurrence of each column it finds. It also now works with variabl...

...call(rbind,lapply(split(dat1,dat1[,1]),function(x) c(V1=x[1,1],colSums(x[,-1],na.rm=TRUE)))) ?write.table(res1,file="new.txt",row.names=FALSE,quote=FALSE) #or res2 <- with(dat1,aggregate(cbind(V2,V3,V4,V5,V6),list(V1=V1),sum,na.rm=TRUE)) #or library(plyr) res3 <- ddply(dat1,.(V1),colwise(sum,na.rm=TRUE)) A.K. Hi, in a text file like 1 2 4 7 8 9 1 4 5 8 9 1 4 5 6 9 2 3 4 8 3 6 7 8 1 5 6 9 2 5 7 9 And so on where the first column represents group's number data <- read.table("in.txt") ## first: ? ? ? ?- select rows that strat with one (check first c...

Hello R-helpers: I have data like this: sample replicate height weight age A 1.00 12.0 0.64 6.00 A 2.00 12.2 0.38 6.00 A 3.00 12.4 0.49 6.00 B 1.00 12.7 0.65 4.00 B 2.00 12.8 0.78 5.00 C 1.00 11.9 0.45 6.00 C 2.00 11.84 0.44 2.00 C 3.00 11.43 0.32 3.00 C 4.00 10.24 0.84 4.00 D

Hi R-users, I want to apply a function to each column of a data frame that is numeric. Thus I tried to check it for each column first: > apply(df, 2, function(x) is.numeric(x)) A60 A64 A66a A67 A71 A75a A80 A85 A91 A95 A96 A97 A98 A99 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE

Dear R Helpers, I have trouble applying reShape and reshape although I read the documentation and several posts, so I would very much appreciate your help on the two points below. I have a dataframe df = data.frame(Name=c("a", "a", "a", "b", "b", "c"), X1=c("12", "13", "14", "20", "25",

Dear R-users, I have a dataset as like below, and I want to subtotal the values of rice,wheat and maize by year for each fid. fid      year     rice     wheat      maize ------------------------------------------------ 1        1995      5        NA           NA 1        1995      NA        3           NA 1        1995      NA       NA           2 1        1996      4        NA           NA 1