similar to: apply(ing) to sum subset of a vector

Dear R-users, For a data frame (say in this example X) I want to look up the corresponding value in a 'look-up data frame' (in this example Y). The for-loop works but is very time-consuming because 'X' in reality is very big. Therefore I would like to have a solution with apply. However, I do not succeed. Any suggestions? Thanks in advance, Hanneke

sapply() stems from S / S+ times and hence has a long tradition. In spite of that I think that it should be enhanced... As the subject mentions, sapply() produces a matrix in cases where the list components of the lapply(.) results are of the same length (and ...). However, it unfortunately "stops there". E.g., if you *nest* two sapply() calls where the inner one produces a matrix, very

Hi, I have a DF like this: DF = data.frame(read.table(textConnection(" A B C 1 b1 1999 0.25 2 c1 1999 0.25 3 d1 1999 0.25 4 a2 1999 0.25 5 c2 1999 0.25 6 d2 1999 0.25 7 a3 1999 0.25 8 b3 1999 0.25 9 d3 1999 0.25 10 a4 1999 0.25 11 b4 1999 0.25 12 c4 1999 0.25 13 b1 2001 0.5 14 a2 2001 0.5 15 b1 2004 0.33 16 c1 2004 0.33 17 a2 2004 0.33 18 c2 2004

Hello! # I have a data frame: mydf<-data.frame(c1=rep(NA,5),c2=rep(NA,5),c3=rep(NA,5)) # I have an index whose length is always the same as nrow(mydf): myindex<-c(1,2,3,2,1) # I need c1 to have 1s in rows 1 and 5 (based on the information in myindex) # I need c2 to have 1s in rows 2 and 4 (also based on myindex) # I need c3 to have 1 in row 3 # In other words, I am trying to achieve this

# Newbie alert # I am wanting to multiply the rows in a dataframe by a vector. # However, the default behavior appears to be for the vector to be applied # column wise. For example: vct <- 1:4 df <- data.frame(c1 = 5:10, c2= 6:11, c3=7:12, c4=8:13) multTheTwo <- vct * df multTheTwo # This results in the vector getting cycled columnwise # c1 c2 c3 c4 # 1 5 18 7 24 # 2 12 28 16 36 # 3

These are supported on GK20A and GM107. Signed-off-by: Ilia Mirkin <imirkin at alum.mit.edu> --- Was a bit torn on where to place the enums... we're about to gut all the xml definitions so this seemed appropriate for now. Tested on GK20A only. src/gallium/drivers/nouveau/nv50/nv50_formats.c | 64 +++++++++++++++++++++++++ src/gallium/drivers/nouveau/nvc0/nvc0_screen.c | 10 ++++

Why not fix the new names instead to be like the old names? Seems like that would be way simpler... On Feb 15, 2016 12:38 AM, "Ben Skeggs" <skeggsb at gmail.com> wrote: > From: Ben Skeggs <bskeggs at redhat.com> > > We've previously had identical naming between vertex and texture > formats, so it mostly made sense to define these together. > > However,

Hi, I observed below behavior with Instruction combiner (visitMul Canonicalization) It tries to convert "(X+C1)*C2" to "X*C2+C1*C2" While transforming if operation is guaranteed to not overflow it does not reflect same property to transformed instructions. Consider following scenarios: 1) If input is ((X+C1)*C2)<nsw> Then post canonicalization output should be

> On Mar 11, 2018, at 3:32 PM, Neha Aggarwal <aggarwalneha2000 at gmail.com> wrote: > > Hello All, > I am facing a unique problem and am unable to find any help in R help pages > or online. I will appreciate your help for the following problem: > I have 2 data-frames, samples below and there is an expected output > > R Dataframe1: > C1 C2

My data frame consists of character variables, factors, and proportions, something like c1 <- c("A", "B", "C", "C") c2 <- factor(c(1, 1, 2, 2), labels = c("Y","N")) x <- c(0.5234, 0.6919, 0.2307, 0.1160) y <- c(0.9251, 0.7616, 0.3624, 0.4462) df <- data.frame(c1, c2, x, y) pct <- function(x) round(100*x, 1) I want to

Hi, I have a long matrix of the following form which I would like to subset according to the third column: [x y z]: a1 c1 1 a1 c1 2 a2 c1 1 a1 c2 1 a1 c2 2 . . . The first two columns a characters ai and cj. I would like to keep all the rows where there are two entries for z, 1 and 2. That is, I want: a1 c1 1 a1 c1 2 a1 c2 1 a1 c2 2 . . . I try to use something like

Hi, I have a data frame where one column is a list of lists. I would like to subset the data frame based on membership of the lists in that column and be able to 'denormalise' the data frame so that a row is duplicated for each of its list elements. Example code follows: # The data is read in in this form with the c2 list values in single strings which I then split to give lists: > f1

Hello, I am relatively new to R, and I am trying to select the last observation within a group, where the group is defined by two variables. One of the variables is a date. In the below example, C3 varies within C2, which varies within C1. I need to select the last observation in C3 for 4 groups (C1*C2): 1x, 1y, 2x, and 2y. In my real dataset, C2 is a date (mm/dd/yy) C1 C2 C3 1 x 1 1

Hello, I am dealing with numeric vectors 10^5 to 10^6 elements long. The values are sorted (with duplicates) in the vector (v). I am obtaining the length of vectors such as (v < c) or (v > c1 & v < c2), where c, c1, c2 are some scalar variables. What is the most efficient way to do this? I am using sum(v < c) since TRUE's are 1's and FALSE's are 0's. This

Colleagues, I have created a list in the following manner: TEST <- list(c("A1", "A2"), c("B1", "B2"), c("C1", "C2")) I now want to delete one element from the list, e.g., the third. The command TEST[[3]] yields (as expected): [1] "C1" "C2" The command TEST[[-3]] yields: Error:

## Hi, I'm having trouble understanding how the cbind function decides what method to apply to its arguments. Easy cut and paste code below. > > > > ## create two columns > c1 <- c("A","A","B","B") > c2 <- 1:4 > > ## cbind outputs a matrix with elements that are characters, seems reasonable > out <-

can list names attributes be preserved through S4 class containment? seems to be so but only if the containment relationship is direct ... see below. > setClass("c1", contains="list") [1] "c1" > l1 = list(a=1, b=2) > o1 = new("c1", l1) > names(o1) # pleasant surprise [1] "a" "b" > setClass("c2",

Dear R community, I am trying to code a fairly complex equation for optim(). My current approach is too slow for optim(). I have a function that takes a double integral (hopefully correctly) across two terms, e.g., doubleint <- function(c1,c2) {integrate(function(y) { sapply(y, function(y) { integrate(function(x) {a*(c1+x)+b*(c2+x)}, boundsx[1], boundsx[2])$value }) },

hello gurus, i have a data frame like this HTN HTN_FDR Dyslipidemia CAD t1d_ptype[1:25] 1 Y Y Y T1D 2 T1D 3 Ctrl_FDR 4 T1D 5 Y Ctrl 6 Ctrl 7

R experts, I have three columns. c1 and c2 are numeric variables whereas c3 are the clusters classes (nominal variable, 10 different: cluster1, cluster2, cluster3, cluster4, cluster5 ....). I'd like to plot c1 against c2 (easy!) in a 2D plot and put different color depending to the cluster class automatically regardless the number of clusters. Could anyone give a hand? Josep Maria, matrix