search for: adply

...ble.com/How-to-replace-all-commas-with-semicolon-in-a-string-tt4721187.html#a4721192 so copying the code of Ulrik(I hope:-)) I tried (making some data) AX <- data.frame(a=chartr(".",",",rnorm(5)),b=chartr(".",",",rnorm(5)),c=rnorm(5)) library(plyr) adply(AX, 2, function(x){ if(!is.numeric(x[[1]]){ gsub(",", ".", x[[1]]) }else{ x[[1]] } }) and got the unwelcome error Error: unexpected '{' in: "adply(AX, 2, function(x){ if(!is.numeric(x[[1]]){" Here is: > sessionInfo() R version 3.4.1 (2017-06-30) Platfor...

Hello R-helpers, A fundamental question ...I'm trying to understand the differences between loop and vectorization ... I understand that it should be a natural choice to use apply / adply when it is needed to perform the same function across all rows of a data frame. Any pointers on why this is so? Unable to find the right reading place on the WWW which explains the concept. Thanks for your help. S

...a-string-tt4721187.html#a4721192 > > so copying the code of Ulrik(I hope:-)) I tried > > (making some data) > > AX <- > data.frame(a=chartr(".",",",rnorm(5)),b=chartr(".",",",rnorm(5)),c=rnorm(5)) > > > library(plyr) > > adply(AX, 2, function(x){ > if(!is.numeric(x[[1]]){ > gsub(",", ".", x[[1]]) > }else{ > x[[1]] > } > }) > > and got the unwelcome error > > Error: unexpected '{' in: > "adply(AX, 2, function(x){ > if(!is.numeric(x[[1]]){" > >...

Hi list, In a function I am writing, I need to extract the dimension names of an array. I know this can be acheived easily using dimnames() but my problem is that I want my function to be robust when the number of dimensions varies. Consider the following case: foo <- array(data = rnorm(32), dim = c(4,4,2), dimnames=list(letters[1:4], LETTERS[1:4], letters[5:6])) # What I want is to extract

...iles so that I can 1. import each data file 2. find the minimum value recorded in column 2 and the previous 5 data points 3. and average these 10 values to get a mean, minimum value. Currently I have imported the data files using the following filenames=list.files() library(plyr) import.list=adply(filenames, 1, read.csv) and I know how to write a code to calculate the minimum value and the 5 preceding values in a single column, in a single file. I think the problem I am running into is scaling this code up so that I can import multiple files and calculating mean, minimum value for the 2^...

Greetings all, I am curious to know if either of these two sets of code is more efficient? Example1: ## t-test ## colA <- temp [ , j ] colB <- temp [ , k ] ttr <- t.test ( colA, colB, var.equal=TRUE) tt_pvalue [ i ] <- ttr$p.value or Example2: tt_pvalue [ i ] <- t.test ( temp[ , j ], temp[ , k ], var.equal=TRUE) ------------- I have three loops, i, j, k. One to test the all of

Hi. I have 2 tables, with same dimensions (8000 x 5). Something like: tab1: V1 V2 V3 V4 V5 14.23 1.71 2.43 15.6 127 13.20 1.78 2.14 11.2 100 13.16 2.36 2.67 18.6 101 14.37 1.95 2.50 16.8 113 13.24 2.59 2.87 21.0 118 tab2: V1 V2 V3 V4 V5 1.23 1.1 2.3 1.6 17 1.20 1.8 2.4 1.2 10 1.16 2.6 2.7 1.6 11 1.37 1.5 2.0 1.8 13 1.24 2.9 2.7 2.0 18 I need generate a table of averages, the

...object they input (first letter) and output (second letter): * llply = from a list to a list * alply = from an array (or vector, or matrix) to a list * ldply = from a list to a data.frame * d_ply = from a data.frame, ignore output * and so on for llply, laply, ldply, l_ply, alply, aaply, adply, a_ply, dlply, daply, dply, d_ply plyr also provides: * m*ply which works in a similar way to mapply * r*ply which works in a similar way to replicate You can find out more at http://had.co.nz/plyr/, including a 20 page introductory guide, http://had.co.nz/plyr/plyr-intro.pdf. Regards, Had...

...object they input (first letter) and output (second letter): * llply = from a list to a list * alply = from an array (or vector, or matrix) to a list * ldply = from a list to a data.frame * d_ply = from a data.frame, ignore output * and so on for llply, laply, ldply, l_ply, alply, aaply, adply, a_ply, dlply, daply, dply, d_ply plyr also provides: * m*ply which works in a similar way to mapply * r*ply which works in a similar way to replicate You can find out more at http://had.co.nz/plyr/, including a 20 page introductory guide, http://had.co.nz/plyr/plyr-intro.pdf. Regards, Had...

Dear all, I have a question regarding the possibility of parallel computation in plyr version 1.7. The help files of the following functions mention the argument '.parallel': ddply, aaply, llply, daply, adply, dlply, alply, ldply, laply However, the help files of the following functions do not mention this argument: ?d_ply, ?aply, ?lply Is it because parallel computation is not supported for these latter functions? Or is it just because the documentation was not updated for these functions after addin...

...riable names if explicit names not provided (Fixes #17) * `arrays` with names should be sorted correctly once again (also fixed a bug in the test case that prevented me from catching this automatically) * `m_ply` no longer possesses .parallel argument (mistakenly added) * `ldply` (and hence `adply` and `ddply`) now correctly passes on .parallel argument (Fixes #16) * `id` uses a better strategy for converting to integers, making it possible to use for cases with larger potential numbers of combinations -- Assistant Professor / Dobelman Family Junior Chair Department of Statistics / R...

...riable names if explicit names not provided (Fixes #17) * `arrays` with names should be sorted correctly once again (also fixed a bug in the test case that prevented me from catching this automatically) * `m_ply` no longer possesses .parallel argument (mistakenly added) * `ldply` (and hence `adply` and `ddply`) now correctly passes on .parallel argument (Fixes #16) * `id` uses a better strategy for converting to integers, making it possible to use for cases with larger potential numbers of combinations -- Assistant Professor / Dobelman Family Junior Chair Department of Statistics / R...

Hi, I have a three dimensional array, e.g., my.array = array(0, dim=c(2,3,4), dimnames=list( d1=c("A1","A2"), d2=c("B1","B2","B3"), d3=c("C1","C2","C3","C4")) ) what I would like to get is then a dataframe: d1 d2 d3 value A1 B1 C1 0 A2 B1 C1 0 . . . A2 B3 C4 0 I'm sure there is one function to do

...ata was rearranged from a flat matrix to a [, , 4] array for larger input matrixes. I'm sure something clever is happening that I'm just not seeing - anyone have any insight? I can provide the code for index.frames() if you like, but it's pretty turgid stuff. For now I'm just using adply(), since it gives an output that I'd expect. Best toy.mat <- all.combinations[10:30,] > aaply(toy.mat,1, index.frames) Var1 1 2 3 4 46 3599.848 3665.454 12946.41 12946.41 51 3600.020 3666.424 12946.41 12946.41 56 3600.167 3667.301 12946.41 12946.4...

Hello All, Would like to be able to convert a matrix to a dataframe without losing an assigned dimname. Here is an example that should illustrate what I'm talking about. tableData <- state.x77[c(7, 38, 20, 46), c(7, 1, 8)] names(dimnames(tableData)) <- c("State", "") tableData State Frost Population Area Connecticut 139 3100 4862

Dear Group, I have a following dataset: > a A B C D 1 22 3 31 40 2 26 31 36 32 3 3 7 49 16 4 24 40 27 26 5 20 45 47 0 6 34 43 11 18 7 48 48 24 2 8 3 16 39 48 9 20 49 7 21 10 17 36 47 10 > dput(a) structure(list(A = c(22L, 26L, 3L, 24L, 20L, 34L, 48L, 3L, 20L, 17L), B = c(3L, 31L, 7L, 40L, 45L, 43L, 48L, 16L, 49L, 36L), C = c(31L, 36L, 49L, 27L, 47L, 11L, 24L,