search for: ddply

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...

Dear R-Helpers: I am using trying to use *ddply* to extract min and max of a particular column in a data.frame. I am using two different forms of the function: ## var_name_to_split is a string -- something like "var1" which is the name of a column in data.frame ddply( df, .(as.name(var_name_to_split)), function(x) c(min(x[ , 3] , ma...

I have a dataframe df with two columns x and y. I want to count the number of times a unique x, y combination occurs. For example x<- c(1,2,3,4,5,1,2,3,4) y<- c(1,2,3,4,5,1,2,4,1) df<-as.data.frame(cbind(x, y)) #what is the correct way to use ddply for this example? ddply(df, c('x','y', summarize, ??) #desired output -- format and order doesn't matter # (x, y) count #-------------------- # (1, 1) 2 # (2, 2) 2 # (3, 3) 1 # (4, 4) 1 # (5, 5) 1 # (2, 3) 1 # (3, 4) 1 # (4, 1) 1 [[alternative HTML version deleted]]

While putting my R code into functions, I've encountered a ddply function nesting issue and need a bit of advice on the proper way to fix it.? I've tried several approahces, but neither worked and I need to have the ability to include the "cut", "range", and "fullseq" methods within ddply.? (For a bit of that explanation refer t...

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)...

Hello everyone, I was asked to repost this again, sorry for any inconvenience. I'm looking replacement for ddply function from plyr package. Function allows to apply function by category stored in any column/columns. Regular loops or lapplys slow down greatly because my unique combination count exceeds 9000. Is there any available solution which allow me to apply function by category? currently my code lo...

...ntinuous variables (age and weight) and I also have a grouping variable (group, with two levels). I want to run correlations for each group separately (kind of similar to "split file" in SPSS). I've been experimenting with different functions, and I was able to do this correctly using ddply function, but output is a little bit difficult to read when I do the cor.test to get all the data with p values, df, and pearson r (see below). I also tried to do it with by function. Although, with by, it shows the data for two groups separately, it seems like it calculates the same r for both gro...

Dear all, I am encountering problems with the application of ddply within the body of a self-defined function. The script is the following: moncostcarmoto <- function(costtype){ costaux_result <- data.frame() for (purp in PURPcount){for (per in PERcount){ costcarin = paste(c("CS_",co...

...w this really should be done. Essentially, I'd like to compute some summary statistics on grouped subsets of data. So, for iris data, let me try to take the mean of the Petal.Width on subsets of data as grouped by: ("some range" of sepal.length, and species). The "normal" ddply invocation would look like so: R> my <- ddply(iris, .(w=Sepal.Length < 5.5, Species), transform, grmean=mean(Petal.Width)) R> head(my) w Sepal.Length Sepal.Width Petal.Length Petal.Width Species grmean 1 FALSE 5.8 4.0 1.2 0.2 setosa 0.26...

...t;, "14.9200", "14.9200", "14.9200", "14.9200" )), .Names = c("DESCRIPTION", "CREATED.DATE", "QUANTITY", "SETTLEMENT"), row.names = c(NA, 12L), class = "data.frame") Here is the line I pass : >PosFut=ddply(futures, c("DESCRIPTION","SETTLEMENT"), summarise, POSITION= sum(QUANTITY))[,c(1,3,2)] And here the result : PosFut <- structure(list(DESCRIPTION = structure(1:3, .Label = c("CORN Jul/10", "LIVE CATTLE Aug/10", "SUGAR NO.11 Jul/10"), class = &...

Hi, I have a data set that I'd like to run logistic regressions on, using ddply to speed up the computation of many models with different combinations of variables. I would like to run regressions on every unique two-variable combination in a portion of my data set, but I can't quite figure out how to do using ddply. The data set looks like this, with "stat...

...inning to learn to write functions. I know I'm out of my depth posting here, and I'm sure my issue is mundane. But here goes. I'm analyzing the American National Election Study (nes), looking at mean values of a numeric dep_var (environ.therm) across values of a factor (partyid3). I use ddply from plyr and wtd.mean from Hmisc. The nes requires a weight var (wt). I use Rcmdr's plotMeans to obtain a line chart. The following code works: attach(nes) obj1 = ddply(nes, .(partyid3), summarise, var = wtd.mean(environ.therm, wt)) print(obj1) plotMeans(obj1$var, obj1$partyid3, error.bars=...

Hi, I am really confused how ddply work, so maybe you can help me. I created a function that sorts a vector etc. fn <- function(x){ x1 <- sort(x) x2 <- seq(length(x)) x3 <- x2/max(x2) df <- data.frame(x1,x2,x3) df } Probably this is not the best form of the function, but at least it produces what I want (data...

...l this occurs within some factor levels. ## I've used plyr here but I'm not married to this approach require(plyr) ## I've created a data.frame with two groups and then a id variable (y) df <- data.frame(x=rnorm(400, mean=20), y=1:400, z=c("A","B")) ## So using ddply I can find the highest value of x df.max1 <- ddply(df, c("z"), subset, x==sort(x, TRUE)[1]) ## Or the 2nd highest value df.max2 <- ddply(df, c("z"), subset, x==sort(x, TRUE)[2]) ## And so on.... but when I try to make a series of numbers like so ## to get the top ten val...

...Using R 2.14.1, plyr 1.7.1, R.Studio 0.94.110, Windows XP The plyr mailing list does not provide any help until now. >require(plyr) >c(sample(c(1:100), 50, replace=TRUE))->V1 >c(rep( 1:5, 10))->f1 #variable to group V1 >data.frame(cbind(V1, f1))->DF >str(DF) >ddply(DF$V1, DF$f1, "sd") >ddply(.(DF$V1), .(DF$f1), "sd") />Error in if (empty(.data)) return(.data) : / /missing value where TRUE/FALSE needed / /Thanks everyone, / //// [[alternative HTML version deleted]]

Hi Together, I have a problem with the plyr package - more precisely with the ddply function - and would be very grateful for any help. I hope the example here is precise enough for someone to identify the problem. Basically, in this step I want to identify observations that are identical in terms of certain identifiers (ID1, ID2, ID3) and just want to save those observations (in...

I have a data frame called "pose": DESCRIPTION QUANITY CLOSING.PRICE 1 WHEAT May/10 1 467.75 2 WHEAT May/10 2 467.75 3 WHEAT May/10 1 467.75 4 WHEAT May/10 1 467.75 5 COTTON NO.2 May/10 1 78.13 6 COTTON NO.2 May/10 3 78.13 7 COTTON NO.2 May/10 1 78.13

Hello all, I have arranged my data as per Dennis's suggestion in this post http://www.mail-archive.com/r-help at r-project.org/msg107156.html. the posted code works fine but when I try to apply it to my data, i get "> u2 <- ddply(xxm, .(plateid, cytokine), as.data.frame.function(f)) Error in t.test.formula(conc ~ Self_T1D, data = df, na.rm = T) : grouping factor must have exactly 2 levels". Self_T1D has two levels "N" and "Y" I have used the ddply function to do the mean and sd for the same data...

...success. Given: d<- data.frame(cbind(x=1,y=seq(20100801,20100830,1))) names(d)<-c("first", "daterep") d2<-d # I can convert the daterep column in place the classic way: d$daterep<-as.Date(strptime(d$daterep, format="%Y%m%d")) # How to do it the plyr way? ddply(d2, c("daterep"), function(df){as.Date(df, format="%Y%m%d")}) # returns: Error in as.Date.default(df, format = "%Y%m%d") : # do not know how to convert 'df' to class "Date" Thanks for any hints, ---jean -- View this message in context: http://r....

I have a bit of a quandy. I'm working with a data set for which I have sampled sites at a variety of dates. I want to use this data, and get a running average of the sampled values for the current and previous date. I originally thought something like ddply would be ideal for this, however, I cannot break up my data by date, and then apply a function that requires information about the previous dates. I had thought to use a for loop and merge, but that doesn't quite seem to be working. So, my questions are twofold 1) Is there a way to use...