similar to: Summing data frame columns on identical data

Dear all, I have 30 arrays, each with dimensions 720,360,12. The naming format for each of these 30 objects is: mrunoff_5221, mrunoff_5222... mrunoff_5250. For example: > str(mrunoff_5221) ? num [1:720, 1:360, 1:12] NA NA NA NA NA NA NA NA NA NA ...? (the initial NA's are nothing to worry about) I am looking for a way by which I can extract each of the third dimension of these grids

Hi all, Thanks for the really great help I've received on this board in the past. I have a very particular graph that I'm trying to plot, and I'm not really sure how to do it. I think I should be able to use ggplot for this, but I'm not really sure how. I have a data.frame which contains fifty sub frames containing one hundred data points each. I can do a histogram of each of

Dear all, I am trying to make a series of waffle plot-like figures for my data to visualize the ratios of amino acid residues at each position. For each one of 37 positions, there may be one to four different amino acid residues. So the data consist of the positions, what residues are there, and the ratios of residues. The ratios of residues at a position add up to 100, or close to 100 (more on

#Hello, #I have three data frames, X,Y and Z with two columns each and different numbers of rows. # creation of data frame X X.alleles <- c(1,5,6,7,8) X.Freq <- c(0.35, 0.15, 0.05 , 0.10, 0.35) Loc1 <- cbind( X.alleles,X.Freq) X <- data.frame(Loc1) #creation of data frame Y Y.alleles <- c(1,4,6,8) Y.Freq <- c(0.35, 0.35, 0.10, 0.20 )

Hi All, I've been doing circles with this all morning, although I'm sure there's a simple solution. I have a data.frame "pop" as follows: > pop ind xloc yloc gonad 1 1 5 2 12 2 1 5 4 25 3 1 3 3 30 4 1 5 4 10 5 1 1 4 08 . . . . . 10 1 1 4 11 And I need the following steps: 1. Sum

Hello, I have an input file: http://r.789695.n4.nabble.com/file/n3700031/testOut.txt testOut.txt where col 1 is chromosome, column2 is start of region, column 3 is end of region, column 4 and 5 is base position, column 6 is total reads, column 7 is methylation data, and column 8 is the strand. I would like a summary output file such as:

Dear all, ## I have 4 tables like this: satu <- array(c(5,15,20,68,29,54,84,119), dim=c(2,4), dimnames=list(c("Negative", "Positive"), c("Black", "Brown", "Red", "Blond"))) dua <- array(c(50,105,30,8,29,25,84,9), dim=c(2,4), dimnames=list(c("Negative", "Positive"),

If I use the Ineq library and the Gini function in this way: >Gini(c(100,0,0,0)) I obtain the result 0.75 instead of 1 (that is the perfect inequality). I think Gini's formula in Ineq is based on a formula as reported here: http://mathworld.wolfram.com/GiniCoefficient.html but in the case of perfect inequality: x_1=.......=x_n-1 =0 x_n>0 these formula are equal to 1 - 1/n, not to

Dear R users, I wish to utilise processed and saved objects as arguments of a function. Specifically, I have created objects using *"assign"* & *"paste"* functions with an incremental index i, the names of the objects are: fund1, fund2, fund3,....., fund80,..... (where the numerical value increments according to the index i & class of these objects are

I have hundreds of text files which has data like a data frame with three columns.The column names are same in all the files.I need to merge all files into a single big file. My files are like this file1 "new.col" "ppm.p." "freq.p." "1_3_diaminopropane" 3.13859 5.67516 "1_3_diaminopropane" 3.137 6.65388 "1_3_diaminopropane" 3.13541 8.0142

Hello, I?ve tried several times to learn R, but have never gotten past a particular gate. My data are organized by column in Excel, with column headers in the first row. The columns are of unequal lengths. I export them as CSV, then import the CSV file into R. I wish to summarize the data by column. R inserts NA for missing values, then refuses to operate on columns with NA. R is importing

Hi folks, Wish y'all a Happy New Year 2010! I need some help with the following: Say I have lots of data sets, on which I have to apply a certain function on the same set of columns in each of the data set. Let's take, for ex, the typical data set is: df1 <- as.data.frame(cbind(rnorm(10),rnorm(10))) names(df1)[1] <- "A" names(df1)[2] <- "B" There are many

Hi, Is it possible use a loop to process many data frames in the same way? For example, if I have three data frames, all with same variables df_bs_id1 <- read.csv("test1.csv",header =TRUE) df_bs_id2 <- read.csv("test2.csv",header =TRUE) df_bs_id3 <- read.csv("test3.csv",header =TRUE) How could I would implement a code loop that , for instance, would

I have the following data: x <- as.factor(c(1,1,1,2,2,2,3,3,3)) y <- as.factor(c(10,10,10,20,20,20,30,30,30)) z <- c(100,100,NA,200,200,200,300,300,300) I could create the cross tab of x and y with Sum of z as its elements using the xtabs function as follows: # X Vs. Y with Sum Z xtabs(z ~ x + y) y x 10 20 30 1 200 0 0 2 0 600 0 3 0 0 900 How do I replace

hi all, I want to get a cumsum according to the order of some variable. However, it doesnt' work. For example, ********************** test<-data.frame(cbind(x=c(3,5,2,6,7),y=c(8,1,4,9,0))) test[order(test$x),]$sumy<-cumsum(test[order(test$x),]$y) ********************** R complians Warning message: In `[<-.data.frame`(`*tmp*`, order(test$x), , value = list(x = c(2, : provided 3

Hi there, Thanks for your time in advance. I am trying to read in multiple files. For example, data.1940 <- read.table("c:/data/1940.csv",header=TRUE,sep=",") data.1950 <- read.table("c:/data/1950.csv",header=TRUE,sep=",") data.1960 <- read.table("c:/data/1960.csv",header=TRUE,sep=",") How can I write a loop to read the

Dear all I have a function in which I would like to change some values to NA according to some condition. dropout<-function(y, nahr=FALSE,...) { <some stuff for computing an index> if (nahr) y[index]<<-NA invisible(index) } in case y is a vector all works OK but if it is a part of data frame by calling dropout(df$y) or dropout(df[,number]) no change is done. Please can you

Hi, I wonder if someone can suggest how to create a new data.frame Y from X where X$PL_Pos is summed by each unique X$MyDate. Y should end up with two (or more) columns Y$MyDate and Y$PL_Sum with its value being the cumsum of all the values in X for that date. - a 'daily cumsum'. Thanks, Mark TStoDate = function (TSDate) { X = strptime(TSDate + 19e6L, "%Y%m%d")

I am web scraping a page at http://catalog.ihsn.org/index.php/catalog#_r=&collection=&country=&dtype=&from=1890&page=1&ps=100&sid=&sk=&sort_by=nation&sort_order=&to=2017&topic=&view=s&vk= From this url, I have built up a dataframe through the following code: dflist <- map(.x = 1:417, .f = function(x) { Sys.sleep(5) url <-

I am using a binomial mixture model to estimate abundance (N) and detection probability (p) using simulated count data: -Each site has a simulated abundance that follow a Poisson distribution with lambda = 5 -There are 200 simulated sampled sites -3 repeated counts at each site - only 50 percent of the animals are counted during each count (i.e, detection probability p =0.5, see codes) We removed