similar to: average among one factor in a nested dataframe

I have a multilevel dataframe (df): ID Date Segment Slice Tract Lesion 1 CSPP005 12/4/2007 1 1 LCST 0 2 CSPP005 12/4/2007 1 1 LPC 2 3 CSPP005 12/4/2007 1 1 RPC 3 4 CSPP005 12/4/2007 1 1 RCST 1 5 CSPP005 12/4/2007 1 1 LGM 0 6 CSPP005 12/4/2007 1 1

Hello, I am try to make a density plot where plots are stacked like the one found here: http://dsarkar.fhcrc.org/lattice/book/images/Figure_14_03_stdBW.png I am facing problems, however. Using the code example below, I'd like to generate a separate panel for each val of id2. Within each panel, I'd like to have individual histograms each on separate lines based on the value of id1. ?Note

I have a multidimensional data which looks like the following: "S1-a" "S2-b" "S3-c" "S4-d" "S5-a" "S6-b" "S7-c" "S8-d" "T1-A" "T1-B" "T1-C" "T1-D" "T2-A" "T2-B" "T2-C" "T2-D" I read it from csv file and would like to have 16

Hi Eik, thank you so much - it works perfectly! Thank you and best wishes Alain   Eik Vettorazzi <E.Vettorazzi@uke.de> hat am 6. Februar 2013 um 17:01 geschrieben: > Hi Alain, > here is a one-liner for a df without the rowSum column > >

any suggestions on the following gratefully welcome, I have a dataframe, which I am subsetting via labels atpi[, creativity] where (for example) atpi = as.data.frame(matrix(1:50, ncol = 5, nrow = 10)) names(atpi) = c("Q1", "Q2", "Q3", "Q4", "Q5") and creativity = c("Q1", "Q3", "Q4") I want to add an extra column

Dear R-List, I am sure there must be a very simple way to do this - I just do not know how... This is what I want to do: #my dataframe df<-data.frame(id=c("x01","x02","x03","x04","x05","x06"),a=c(1,2,NA,4,5,6),b=c(2,4,6,8,10,NA),c=c(NA,3,9,12,NA,NA),sum=c(3,9,15,24,15,6))    id    a     b     c   sum 1 x01  1     2    NA   3 2

Dear all, Lets say I have the following data frame: > set.seed(1) > col1 <- c(rep('happy',9), rep('sad', 9)) > col2 <- rep(c(rep('alpha', 3), rep('beta', 3), rep('gamma', 3)),2) > dates <- as.Date(rep(c('2009-10-13', '2009-10-14', '2009-10-15'),6)) > score=rnorm(18, 10, 3) > df1<-data.frame(col1=col1,

I have a dataFrame variable: L1 L2 L3 ... v1 v2 ... 1 2 3 4 ... I want to process subsets of it as defined by combinations of L1-L2-L3. I do it successfully using nested loops: for (i in valuesOfL1 { for (j in valuesOfL2) { for (k in valuesOfL3) { tempData <- subset(dataFrame, (L1 == i & L2 == j & L3 == k, select=c(v1,v2) )) if

Hi, I've a beginner question. I'm trying to extract data in my dataframe according to some nested rules. I have something like the dataframe test.df: test.df = data.frame(V1=c(rep("A",10), rep("B",10), rep("C",5)), V2=c(rep(1,5), rep(2,5), rep(1,5), rep(2,5), rep(1,5))) V1 V2 1 A 1 2 A 1 3 A 1 4 A 1 5 A 1 6 A 2 7 A 2 8 A 2 9 A

Hi experts. I have a tibble? with a column containing a nested list (<list<list<double>>>? data type to be specific). Looks something like the following (but in R/Arrow? format): ID Nestedvals 001 [[1]](1,0.1)[[2]](2,0.2)[[3]](3,0.3)[[4]](4,0.4)[[5]](5,0.5) 002 [[1]](1,0.1)[[2]](2,0.2)[[3]](3,0.3)[[4]](4,0.4) 003 [[1]](1,0.1)[[2]](2,0.2)[[3]](3,0.3) 004 [[1]](1,0.1)[[2]](2,0.2)

I need you help with this problem, I have a data-frame like this: BHID=c(43,43,43,43,44,44,44,44,44) FROM=c(50.9,46.7,44.2,43.1,52.3,51.9,49.3,46.2,42.38) TO=c(46.7,44.2,43.1,40.9,51.9,49.3,46.2,42.38,36.3) AR=c(45,46,0.0,38.45,50.05,22.9,0,25,9) DF<-data.frame(BHID,FROM,TO,VALUE) #add the length DF$LENGTH=DF$FROM-DF$TO where: + BHID: is the borehole

Hello, If I have two correlation matrices (e.g. one for each of two treatments) and then perform cor() on those two correlation matrices is this third correlation matrix interpreted as the correlation between the two treatments? In my sample below I would interpret that the treatments are 0.28 correlated. Is this correct? > var1<- c(.000000000008, .09, .1234, .5670008, .00110011002200,

Hi, We got a question about interpretating R-suqared. The actual outputs for a test dataset is X=(x1,x2, ..., xn). model 1 predicted the outputs as Y1=(y11,y12,..., y1n) model n predicted the outputs as Y2=(y21,y22,..., y2n) ... model m predicted the outputs as Ym=(ym1,ym2,..., ymn) Now we have two ways to calculate R squared to evaluate the average performance of committee model. (a)

Dear all, I have a dataframe with 132 columns and 100 rows. Every 2nd column is a repeat measurement so that the columns could be titled, a a b b c c d d etc. I would like to average the repeats such that I am left with a data frame of 66 columns (of means) and 100 rows. I have been trying to use rowMeans but have not been able to average the pairs of columns, only the whole dataframe. Any

Hi, I want to create a dataframe where one of the columns does not hold individual elements, but a vector instead. For example, imagine the following dataframe without any vectors as elements . . . ex X1 X2 1 5 15 2 7 12 3 9 14 If I have a pre-existing dataframe, then setting an element in the dataframe

hi netters, i have a dataframe TEST like this: Y1 Y2 Y3 X1 4 7 8 X2 6 2 Z X3 8 0 1 i would like to change it to a numeric matrix, replacing "Z" with NA Y1 Y2 Y3 X1 4 7 8 X2 6 2 NA X3 8 0 1 i've tried the function data.matrix but it didn't work. is there any easy way to do this? thanks a lot!

Hi First post and a relative R newbie.... I am using the vioplot library to produce some violin plots. I have an input CSV with columns off irregular length that contain NAs. I want to strip the NAs out and produce a multiple violin plot automatically labelled using the headers. At the moment I do this Code:? ds1 = read.csv("http://www.lecturematerials.co.uk/data/spelling.csv")

Dear R-users,  I have a problem, I have the following dataframe:   d<-data.frame(  'y1'=c(1,2,1,2,1,NA,NA), 'y2'=c(1,2,1,1,1,2,1), 'y3'=c(1,NA,1,NA,NA,2,1), 'y4'=c(NA,2,NA,1,1,2,NA), 'a'=c(1,1,1,1,1,1,2) ) where the last variable counts the number of missing values in a row. Now, i want to set rows where a>1 to NA and arrive at something like the

Hi R folks, I have a massive array (object name "points") in the following form [,1] [,2] [1,] 1369 22 [2,] 1370 22 [3,] 1368 23 [4,] 1369 23 [5,] 1370 23 [6,] 1371 23 (10080 rows truncated) These represent pixel coordinates of interest in a jpeg image. I need to find the distance from each point to all other points of interest. The only way I can see to do this

Hi, How can I achieve this in R. Dataset is as follows: >df x 1 2 2 4 3 1 4 3 5 3 6 2 structure(list(x = c(2, 4, 1, 3, 3, 2)), .Names = "x", row.names = c("1", "2", "3", "4", "5", "6"), class = "data.frame") I want to recreate a new data frame whose rows are sum of (1&2, 3&4, 5&6)