similar to: Can you have a by variable in Lag function as in SAS

Hello, I have a variable in a data frame that contains NA values. I just want to subset so that I get the obs where that variable is missing. In SAS I would do: data missing; set test; if myvalue=' '; run; How can I perform this simple task in R? Thanks in advance for your help. -- View this message in context:

It might be a bit faster to do matrix indexing: R> tbm <- as.matrix(tb) # turn it into a character matrix R> tmat[cbind(match(tbm[,2], rownames(tmat)), match(tbm[,1], colnames(tmat)))] <- 1 > tmat Apple Orange Mango Grape Star A 1 1 1 0 0 O 1 1 0 0 0 M 0 0 1 0 0 G 0 0 0 0 0 S 1 1 1 0

hi: I have matrix with dimensions(200 X 20,000). I have another file, a tab-delim file where first column variables are row names and second column variables are column names. For instance: > tmat Apple Orange Mango Grape Star A 0 0 0 0 0 O 0 0 0 0 0 M 0 0 0 0 0 G 0 0 0 0 0 S 0 0 0 0 0

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Hi all, Suppose I have a vector Fruits <- c('Apple','Orange','Pear','Banana','Mango') I want to print the statement "The fruits in the basket are: Apple, Orange, Pear, Banana, Mango" If I do: print(paste('The fruits in the basket are:',Fruits)) The output is: [1] "The fruits in the basket are: Apple" "The fruits in

I am trying to replicate the SAS proc univariate in R. I got most of the stats I needed for a by grouping in a data frame using: all1 <- ddply(all,"ACT_NAME", summarise, mean=mean(COUNTS), sd=sd(COUNTS), q25=quantile(COUNTS,.25),median=quantile(COUNTS,.50), q75=quantile(COUNTS,.75), q90=quantile(COUNTS,.90), q95=quantile(COUNTS,.95), q99=quantile(COUNTS,.99) )

Hello, I am trying to re-code all my programs from SAS into R. In SAS I use the following code: proc sort data=upper; by tdate stock_symbol expire strike; run; data upper1; set upper; by tdate stock_symbol expire strike; if first.expire then output; rename strike=astrike; run; on the following data set: tdate stock_symbol expiration strike 9/11/2012 C 9/16/2012

Hello, I am a newbie to R coming from SAS background. I am trying to program the following: I have a monthly data frame with 2 variables: client pct_total A 15% B 10% C 10% D 9% E 8% F 6% G 4% I need to come up w/ a monthly list of clients that make 50% or just above it every month so I can pass them to the rest of the program.

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Hi, R-help: I am a new user of R and am very pleased with R's features. Here I have one question regarding data frame manipulation. I have a data frame look like this: Fruit Condition 1 Orange Good 2 Orange Bad 3 Orange Good 4 Orange Good 5 Orange Bad 6 Apple Good 7 Apple Bad 8 Apple Good 9 Apple Good 10 Apple Bad 11 Apple Good 12 Apple Bad 13

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Given this data frame (a simplified, essential reproducible example) A<-c(8,7,10,1,5) A_flag<-c(10,0,1,0,2) B<-c(5,6,2,1,0) B_flag<-c(12,9,0,5,0) mydf<-data.frame(A, A_flag, B, B_flag) # this is my initial df mydf I want to get to this final situation i<-which(mydf$A_flag==0) mydf$A[i]<-NA ii<-which(mydf$B_flag==0) mydf$B[ii]<-NA

Hi all, Can anyone explain why the following use of the subset() function produces a different outcome than the use of the "[" extractor? The subset() function as used in density(subset(mydf, ht >= 150.0 & wt <= 150.0, select = c(age))) appears to me from documentation to be equivalent to density(mydf[mydf$ht >= 150.0 & mydf$wt <= 150.0, "age"])

Hello, I have a column called max_date in my data frame and I only want to keep the bigger values for the same activity. How can I do that? data frame: activity max_dt A 2013-03-05 B 2013-03-28 A 2013-03-28 C 2013-03-28 B 2013-03-01 Thank you for your help -- View this message in context:

Hello! I have a data frame with dates. I need to create a new "month" that starts on the 20th of each month - because I'll need to aggregate my data later by that "shifted" month. I wrote the code below and it works. However, I was wondering if there is some ready-made function in some package - that makes it easier/more elegant? Thanks a lot! # Example data:

Dear all, given I have data in a data.frame which indicate the number of people in a specific year at a specific age: n <- 10 mydf <- data.frame(yr=sample(1:10, size=n, replace=FALSE), age=sample(1:12, size=n, replace=FALSE), no=sample(1:10, size=n, replace=FALSE)) Now I would like to make a matrix with (in this simple example) 10 columns (for the

Dear all, I wanted to make a two-way-table of two variables with a counting variable stored in another column of a dataframe. In version 1.9.1, the behavior is as expected as shown in the simplified example code. > sex <- rep(c("F", "M"), 5) > income <- c(rep("low", 5), rep("high", 5)) > count <- 1:10 > mydf <-

Hi All, I've been successfully using the with function for analyses and the transform function for multiple transformations. Then I thought, why not use "with" for both? I ran into problems & couldn't figure them out from help files or books. So I created a simplified version of what I'm doing: rm( list=ls() ) x1<-c(1,3,3) x2<-c(3,2,1) x3<-c(2,5,2)

I am trying to concatenate 2 datasets that don't have exactly the same column. In SAS I did: data summary; set agency prop; run; No problem in R I get error message summary <-rbind(agency,prop) Error in match.names(clabs, names(xi)) : names do not match previous names But when I use rbin.fill, that overwrites the second file w/ first one. Is there a way to replicate the sas process

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