similar to: conditional seq

Hi, I am running the following script for a different (much larger data frame): DF = data.frame(read.table(textConnection(" A B C D E 1 1 a 1999 1 0 2 1 b 1999 0 1 3 1 c 1999 0 1 4 1 d 1999 1 0 5 2 c 2001 1 0 6 2 d 2001 0 1 7 3 a 2004 0 1 8 3 b 2004 0 1 9 3 d 2004 0 1 10 4 b 2001 1 0 11 4 c 2001 1 0 12 4 d 2001 0

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

Hi, I have a data.frame of the following type: F = data.frame(read.table(textConnection(" A B 1 1 4 2 1 3 3 1 1 4 1 4 5 1 2 6 1 2 7 1 2 8 2 1 9 2 1 10 2 1 11 2 1 12 3 2 13 3 4 14 3 1 15 3 1 16 3 1"),head=TRUE,stringsAsFactors=FALSE)) F A B 1 1 4 2 1 3 3 1 1 4 1 4 5 1 2 6 1 2 7 1 2 8 2 1 9 2 1 10 2 1 11 2 1 12 3 2 13 3 4 14 3 1 15 3 1 16 3 1

Hi list, based on the following data.frame I would like to create a variable that indicates the number of occurrences of A in the 3 years prior to the current year: DF = data.frame(read.table(textConnection(" A B 8025 1995 8026 1995 8029 1995 8026 1996 8025 1997 8026 1997 8025 1997 8027 1997 8026 1999 8027 1999 8028 1995 8029 1998 8025 1997 8027 1997 8026 1999 8027 1999

Hi, I have a large dataset with info on individuals (B) that have been involved in projects (A) during multiple years (C). The dataset contains three columns: A, B, C. Example: A B C 1 1 a 1999 2 1 b 1999 3 1 c 1999 4 1 d 1999 5 2 c 2001 6 2 d 2001 7 3 a 2004 8 3 c 2004 9 3 d 2004 I am interested in how well all the individuals in a project know each other. To

Hi list, Can anyone tell my why the following does not work? Thanks a lot! Your help is very much appreciated. DF = data.frame(read.table(textConnection(" B C D E F G 8025 1995 0 4 1 2 8025 1997 1 1 3 4 8026 1995 0 7 0 0 8026 1996 1 2 3 0 8026 1997 1 2 3 1 8026 1998 6 0 0 4 8026 1999 3 7 0 3 8027 1997 1 2 3 9 8027 1998 1 2 3 1 8027 1999

Hi, I need to perform calculations on subsets of a data frame: DF = data.frame(read.table(textConnection(" A B C D E F 1 a 1995 0 4 1 2 a 1997 1 1 3 3 b 1995 3 7 0 4 b 1996 1 2 3 5 b 1997 1 2 3 6 b 1998 6 0 0 7 b 1999 3 7 0 8 c 1997 1 2 3 9 c 1998 1 2 3 10 c 1999 6 0 0 11 d 1999 3 7 0 12 e 1995 1 2 3 13 e 1998 1 2 3 14 e 1999 6

Dear list, This is a bit of an off-topic question, but I'm hoping to get some advice from more experienced people. I've used the website "Web of Science" to manually collect publication counts responding to several keywords as a function of date, since the 1960s. http://apps.isiknowledge.com/RAMore.do?product=UA&search_mode=&SID=P1g9lFJp9 at

Hi, I have the following sequence: in <- c(0, 0, 0, 2, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 2, 0, 2, 0, 0, 2) >From this sequence I would like to get to the following sequence: out <- c(0, 0, 0, 3, 3, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 0, 2, 0, 2, 0, 0, 2) Basically,

Hi list, I would like to use the following data.frame to generate matrices over a 3 year moving window: DF = data.frame(read.table(textConnection(" A B C 80 8025 1995 80 8026 1995 80 8029 1995 81 8026 1996 82 8025 1997 82 8026 1997 83 8025 1997 83 8027 1997 84 8026 1999 84 8027 1999 85 8028 1995 85 8029 1998"),head=TRUE,stringsAsFactors=FALSE)) Function to be

Hi, I have a data frame containing two columns: x<-as.factor(c('a','a','a','a','a','b','b','b','c','d','d','d')) y<-c(1,3,6,8,12,3,4,7,5,6,7,10) X<-data.frame(x,y) X x y 1 a 1 2 a 3 3 a 6 4 a 8 5 a 12 6 b 3 7 b 4 8 b 7 9 c 5 10 d 6 11 d 7 12 d 10 I would like to

Look at the bottom of the message for my question #here is a little function that I wrote USGS <- function(input="discharge", days=7){ library(chron) library(gsubfn) #021973269 is the Waynesboro Gauge on the Savannah River Proper (SRS) #02102908 is the Flat Creek Gauge (ftbrfcms) #02133500 is the Drowning Creek (ftbrbmcm) #02341800 is the Upatoi Creek Near Columbus (ftbn) #02342500 is

Dear R Users, I have the following data frame: v1 <- c(rep(10,3),rep(11,2)) v2 <- sample(5:10, 5, replace = T) v3 <- c(0,1,2,0,2) df <- data.frame(v1,v2,v3) > df v1 v2 v3 1 10 9 0 2 10 5 1 3 10 6 2 4 11 7 0 5 11 5 2 I want to add a new column v4 such that its values are equal to the value of v2 conditional on v3=0 for each subgroup of v1. In the above example, the

Here's one way ..... Lines<-"x1 x2 x3 x4 x5 x6 NA NA 3 4 NA NA 5 3 4 NA NA NA 7 3 4 4 NA NA 11 3 4 5 NA NA 67 4 4 NA NA NA" d <- read.table(textConnection(Lines), header = TRUE, colClasses=c("integer")) closeAllConnections() res = t(apply(d, 1, function(x) ave(x,is.na(x),FUN=cumsum))) print(res) x1 x2 x3 x4 x5 x6 [1,] NA NA 3 7 NA NA [2,] 5 8 12 NA NA NA

Hi, x <- c(rep(1800000003L, 10000000), -rep(1200000002L, 15000000)) This is correct: > sum(as.double(x)) [1] 0 This is not: > sum(x) [1] 4996000 Returning NA (with a warning) would also be acceptable for the latter. That would make it consistent with cumsum(x): > cumsum(x)[length(x)] [1] NA Warning message: Integer overflow in 'cumsum'; use

Running R.app on Mac OS X 10.4 > version _ platform powerpc-apple-darwin8.6.0 arch powerpc os darwin8.6.0 system powerpc, darwin8.6.0 status major 2 minor 3.1 year 2006

Running R.app on Mac OS X 10.4 > version _ platform powerpc-apple-darwin8.6.0 arch powerpc os darwin8.6.0 system powerpc, darwin8.6.0 status major 2 minor 3.1 year 2006

Hi, First post here. Grateful for any help you can give. I have data which looks like this: id time x 1 12:01 5 1 12:02 14 1 12:03 6 1 12:04 3 2 12:01 98 2 12:02 23 2 12:03 1 2 12:04 4 3 12:01 5 3 12:02 65 3 12:03 23 3 12:04 23 But I want to add a column which is the cumulative sum of X, but only by id. I've used cumsum before, but not

Dear R-users, I have a dataset with categories and numbers. I would like to compute and add cumulative numbers to the dataset. I do not understand the structure of by(...) or tapply(...) output enough to handle it. Here a small example -------------- d<-expand.grid(a=1:5,b=1:3,c=1:2) d$n = 10 * d$a + d$b +0.1* d$c Sn<-by(d$n,list(d$a,d$c),cumsum) str(Sn) --------- List of 10 $ : num

>>>>> Tomas Kalibera >>>>> on Tue, 25 Aug 2020 09:29:05 +0200 writes: > On 8/23/20 5:02 PM, Rory Winston wrote: >> Hi >> >> I noticed a small inconsistency when using sum() vs cumsum() >> >> I have a char-based series >> >> > tryjpy$long >> >> [1]