similar to: help in ddply

Hi All, I have a scatter plot produced using ggplot2 and I want to add the regression line to this scatter plot. I suppose I can use geom_smooth() to do this, but for the sake of learning ( I am new both to R and ggplot2), I want to try and add it as a function (something that curve() does in the standard R plotting). I did some search and found that stat_function() can be used for this. But

Hi all: I am trying to use the ddply function to estimate the mean of 'Total','Fry','Smolt' and 'Fry.Eq' columns without success. I have the dput of my dataset below. I wonder if someone can give me a hand with this function. # dput(winter) winter <-structure(list(IDDate = structure(c(37L, 48L, 59L, 62L, 63L, 64L, 65L, 66L, 67L, 38L, 39L, 40L, 41L, 42L, 43L,

Hi R-Help, data at bottom I've been struggling with a problem where I need to order based on 1) the Frequency "Freq" and 2) keeping each group of 3 of the same type together "Var2" but I want across all groups it to go "high to low" based on the earn factor. Thank you! structure(list(Var1 = structure(c(1L, 3L, 2L, 1L, 2L, 3L, 1L, 3L, 2L, 3L, 1L, 2L, 3L, 1L,

Hi, I'm trying to understand some details about an example maintened in [1]. According that link, I have total.data as a data set (am I right?). But I don't understand how is built that table. I saved the dataset in a file, with dput(), and had something like this: structure(list(df.all = structure(list(V1 = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,

what am I doing wrong? chron(as.character(f), format=c(dates="%m/%d/%y", times="%h:%m")) f <- structure(c(51L, 60L, 66L, 87L, 90L, 115L, 23L, 35L, 37L, 6L, 12L, 55L, 84L, 96L, 109L, 17L, 29L, 41L, 3L, 74L, 94L, 102L, 30L, 8L, 46L, 69L, 107L, 15L, 25L, 39L, 1L, 71L, 95L, 19L, 56L, 62L, 76L, 85L, 99L, 111L, 42L, 4L, 52L, 61L, 67L, 91L, 13L, 24L, 36L, 38L, 7L, 81L, 82L, 57L,

Dear R users, A have a dataframe (matrix) with two collumns (plot, and diameter (d)). I want all diameters values for different combination of plots. For example I want all d values for all posible combination, 100C2 (all d values for plot 1 with all d values in the plot 2.......with all d values from plot 1 with all d values from plot 100, ...... with all d values from plot 99 with all d values

Folks, I have a data frame with columns 200401, 200402, ..., 201207, 201208. These represent years/months. What would be the best way to sum these columns by year? What about by quarter? Thanks for your time, KW -- [[alternative HTML version deleted]]

Hi all, I have a data set (df, n=10 for the sake of simplicity here) where I have two continuous 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

Hi, Try this: #mat1 is the data res<-do.call(cbind,lapply(seq_len(nrow(mat1)),function(i) {new1<-do.call(rbind,lapply(seq_len(nrow(mat1[-i,])),function(j) {x1<-rbind(mat1[i,],mat1[j,]); x2<-(abs(x1[1,1]-x1[2,1])*abs(x1[1,5]-x1[2,5]))+(abs(x1[1,2]-x1[2,2])*abs(x1[1,6]-x1[2,6]))+(abs(x1[1,3]-x1[2,3])*abs(x1[1,7]-x1[2,7]))+(abs(x1[1,4]-x1[2,4])*abs(x1[1,8]-x1[2,8]))}));new1}))

OK, so maybe last night was a little too much at one throw, so I have reduced the data to two stations- one that has precipitation and one that does not. This is going to be in the context of a larger data set. I would like to be able to issue a ggplot command and have cum sum just act on the facets (factors) to apply this. library(chron) library(ggplot2) DF <- structure(list(date_time =

I'm trying to read a binary file created by a fortran code using readBin and readChar. Everything reads fine (integers and strings) except for double precision numbers, they are read as huge or very small number (1E-250,...). I tried various endianness, swap, But nothing has worked so far. I also tried on R 64 bit for linux and windows (R 2.14) and R 2.11 on windows XP 32 bit. Any help would

I need to make about 30 figures and I am trying to create a program in R that will make my life a lot easier. First I will tell you how my data is setup. I have 30 sites and then data for each year at the site. I have 10 years of data for each site. Below is a small chunk of my data to show the format. 2000 2001 2002 2003 2004 Site A 50 75 25 55 60 Site B 58 22 68 77 30 I am trying to

Hello, I want to use lme to fit two (or more) models, and then compare the fits on each individual. I know how to write my own code to do this (for each individual, plot the raw data, followed by lines() to plot each fitted curve) but I would like to use plot(augPred(... as it produces a nice trellis plot. I thought I could do this with par(new=T) but it does not seem to work.

Hello All... I gave a task to my students that involved using mclust to look for clusters in some bivariate data of isotopes vs various mining locations. They discovered something I didn?t expect; the data (called tur) is appended below. p <- qplot(x = dD, y = dCu65, data = tur, color = mine) print(p) # simple bivariate plot of the data; looks fine mod1 <- Mclust(tur[,2:3]) mod1$G mod2

Hi all, I would like to ask you for help. I did a dotplot - using dotchart function. There are two localites (loc) with values 75 or 56 in my data ZZ. The f column has 4 levels: P1, S1, S8, R6. The dataframe is ordered by N value, pchloc value is assign to use "pch" in plot. > head(ZZ) loc f N color ordered pchloc 98 75 S1 6.39 green 1 16 99 75 S8 6.44 blue

Dear R users, I want to aggregate all *d *data from all combination of n *plots* taken by k. Thank very much! My data is like that: plot d 1 14 1 13 1 12 1 14 1 18 1 20 1 21 1 43 1 108 1 43 2 41 2 61 2 83 2 61 2 84 2 45 2 21 2 12 2 11 ... 100 10 100 12 -- --- Catalin-Constantin ROIBU Forestry engineer, PhD Forestry Faculty of Suceava

All, What would be the most efficient way to load the data at the following address into a dataframe? http://ratings.fide.com/top.phtml?list=men Thanks, David -- View this message in context: http://r.789695.n4.nabble.com/Loading-Chess-Data-tp4642006.html Sent from the R help mailing list archive at Nabble.com.

Dear all, I'm stuck with a problem using plyr to process a rather large junk of data. What I'm trying to do is applying a moving average to all the subparts of the dataframe (the example data can be found here https://dl.dropboxusercontent.com/u/2414056/testData.Rdata). require(plyr) load("testData.Rdata") applyfilter<-function(x){ return(filter(x,rep(1/5, times=5))) }

Dear R user I want to create a table (as below) to summarize the attached data (Test.csv, which can be read into R by using 'read.csv(Test.csv, header=F)' ), to indicate the day that there are any data available, e.g.value=1 if there are any data available for that day, otherwise value=0. 28/04 29/04 30/04 01/05 02/05 532703 0 1 1

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, - Stuart Andrews >