similar to: Using apply for logical conditions

Hi, I have a dataset in which I would like to select rows based on matching conditions and return the maximum value of a variable else return one row if duplicate counts exist. My dataset looks like this: PGID PTID Year Visit Count 6755 53121 2009 1 0 6755 53121 2009 2 0 6755 53121 2009 3 0 6755 53122 2008 1 0 6755 53122 2008 2 0 6755 53122 2008 3 1 6755 53122 2009 1 0 6755 53122 2009 2 1 6755

Hello, I would appreciate if someone could help me resolve the following: 1. df1[!is.na( X1 | X2 | X3 | X4 | X5),][,1:5] # This does not work 2. Is these message harmful? The following object(s) are masked from 'df1 (position 3)': X1, X2, X3, X4, X5 Thanks, Pradip Muhuri #Reproducible Example set.seed(5) df1<-data.frame(matrix(sample(c(1:10,NA),100,replace=TRUE),ncol=5))

Hello guys, Having a slight problem with acts_as_ferret, specifically using a condition. I have the following code @results = SupplierProduct.find_by_contents(params [:search], :conditions => [''area_id = ?'', @area]) and it seems the condition isn''t being applied. Does anyone have any pointers? Cheers, Alastair ------ Alastair Moore Standards compliant web

Hi: I am trying to query pubmed abstracts using the following syntax: url= "http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?" search = paste(url, "db=pubmed&term=", queryTerm1, "+AND+", queryTerm2,"+OR+",queryTerm3, "+OR+", queryTerm4, "[abstract]&retmax=100&usehistory=y", sep="") docId <-

Hello guys, I''m pretty new to using AAF and am having a slight problem with using a condition. I have the following code @results = SupplierProduct.find_by_contents(params[:search], :conditions => [''area_id = ?'', @area]) and it seems the condition isn''t being applied. Does anyone have any pointers? Cheers, Alastair -- Posted via

Hi, I have two lists (c and h - see below) containing matrices with similar cases but different values. I want to split these matrices into multiple matrices based on the values in h. So, I did the following: years<-c(1997:1999) for (t in 1:length(years)) { year=as.character(years[t]) h[[year]]<-sapply(colnames(h[[year]]), function(var)

On Sun, May 14, 2017 at 8:37 AM, Hal Finkel <hfinkel at anl.gov> wrote: > > On 03/01/2017 05:30 PM, Daniel Berlin via llvm-dev wrote: > > So, https://bugs.llvm.org/show_bug.cgi?id=32056 is an example showing our > current TBAA tree for union generation is definitely irretrievably broken. > I'll be honest here. I'm pretty sure your proposal doesn't go far

Hi, I know ways to do this but they all seem awkward and I somehow believe that there is a convenient shortcut. If I have a data.frame with many columns, how can I request all rows for which at least one column satisfy an expression? For instance, all rows where at least one column is negative. Many thanks, Werner

Hello there, Offending source code is ????? if(? ( BattVoltage> 129 ) || ( BattVoltage < 144 ) ) Maybe swap || for && would be better. This problem I found by using cppcheck. It said [rhino.c:190]: (warning) Logical disjunction always evaluates to true: BattVoltage> 129 || BattVoltage < 144. Regards David Binderman

Hi all, Suppose I have 2 data.frame , a and b, how can I add them together to get c? Thanks > a A a 1 b 2 c 3 > b A a 6 c 1 > c A a 7 b 2 c 4 -- Best, Zhenjiang [[alternative HTML version deleted]]

Hi all, I have a question concerning using several conditions in an ifelse function used as the function in apply. I want to create a new value with the function ifelse ? object which can be coerced to logical mode ?test[n,] >1 & test[n-1,]==0? With n I mean the row. I don?t know how I could do this without a loop. I want to avoid the usage of loops and was thinking about apply. This

Dear R users, I??ve got a simple question but somehow I can??t find the solution: I have a data frame with columns 1-5 containing one set of integer values, and columns 6-10 containing another set of integer values. Columns 6-10 contain NA??s at some places. I now want to calculate (1) the number of values in each row of columns 6-10 that were NA??s (2) the sum of all values on columns 1-5

I need to apply a yearly inflation factor to some wages and supply some simple sums by work category. I have gone at it with a brute force "for" loop approach which seems okay as it is a small dataset. It looks a bit inelegant and given all the warnings in the Intro to R, etc, about using loops I wondered if anyone could suggest something a bit simpler or more efficent? Example:

Hello, I am trying to achieve something which I *think* is possible using rowsum, but a little help should be useful: Consider the following dataframe DF0: A B C 89 1 140 89 06 20 89 29 137 89 52 13 89 57 10 89 97 23 89 1 37 89 1 12 89 1 3 52 1 11 52 1 31 52 1 16 52 1 6 52 1 10 52 1 13 52 1 10 52 1 25 52 1 2 52 59 38 52 97 75 57 1 14 57 1 13 57 1 14 57 114 12 57 1 23 57 06 26 I need create a

Hi Guys I have two data frames which I would like to merge on two conditions. I am doing the following (abstract form) new.data.frame <- merge(df1,df2, by=c("Col1","Col2")) It is giving me a null result. Basically I need to apply two conditions. I also tried sqldf but it is running forever. Will indexing help ? temp <- sqldf("select

*Hi all,* * * *The following is my general idea for the project. For a complete query parser I still need to consider more details. Please give me feedback because the description of this project is lack of detailed information, and I can submit my proposal without giant deviation.* * * design principle of query parsing: 1) better understanding user input. All search engine do is understanding

Greetings, My goal is to create a Markov transition matrix (probability of moving from one state to another) with the 'highest traffic' portion of the matrix occupying the top-left section. Consider the following sample: inputData <- c( c(5, 3, 1, 6, 7), c(9, 7, 3, 10, 11), c(1, 2, 3, 4, 5), c(2, 4, 6, 8, 10), c(9, 5, 2, 1, 1) ) MAT <- matrix(inputData,

I'm very new to R and am trying to create my first loop. I have: x <-c(0:200) A <- dpois(x,exp(4.5355343)) B <- dpois(x,exp(4.5355343 + 0.0118638)) C <- dpois(x,exp(4.5355343 -0.0234615)) D <- dpois(x,exp(4.5355343 + 0.0316557)) E <- dpois(x,exp(4.5355343 + 0.0004716)) F <- dpois(x,exp(4.5355343 + 0.056437)) G <- dpois(x,exp(4.5355343 + 0.1225822)) and would like to

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,

Hi, I am looking for some generalization of colSums and rowSums for general vector valued functions, and for arrays of more than 2 dimensions. So as a concrete example, suppose I have a 3 dimensional array, given by x = array(1:100,c(3,4,5)). and I want to sum the 3rd index of x to obain a 3 by 4 matrix. Using rowSums would return a vector of length 3 because it treats the last two indices as