similar to: How to fix my nested conditional IF ELSE code?

Dear R-helpers, I am helping a SAS user run some analyses in R that she cannot do in SAS and she is complaining about R's peculiar (to her!) way of recoding variables. In particular, she is wondering if there is an R package that allows this kind of SAS recoding: IF TYPE='TRUCK' and count=12 THEN VEHICLES=TRUCK+((CAR+BIKE)/2.2); Thanks for any help or suggestions you might be able

Just a minor point in the suggested solution: df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG)) since WC and TG are not conditional, would this be a slight improvement? df$LAP <- with(df, TG*(WC - ifelse(G=='male', 65, 58))) -----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of Jorgen Harmse via R-help Sent: Friday,

Hi R-helpers! I have the following dataframe: firm<-c(rep(1:3,4)) year<-c(rep(2001:2003,4)) X1<-rep(c(10,NA),6) X2<-rep(c(5,NA,2),4) data<-data.frame(firm, year,X1,X2) data So I want to obtain the same dataframe with a variable X3 that is: X1, if X2=NA X2, if X1=NA X1+X2 if X1 and X2 are not NA So my final data is X3<-c(15,NA,12,5,10,2,15,NA,12,5,10,2)

I have a vector of 2,1,0 I want to change to 0,1,2 respectively (the data is allele dosages) I have tried multiple nested if/else statements and looked at the ?if help and cannot work out what is wrong, other people have posted code which is identical and they state works. Any help would be greatly appreciated. > A[1:20] [1] 1 1 0 0 1 0 1 0 1 0 0 0 1 1 0 1 1 1 0 0 > B <-

I have a dataframe called "data" with 5 records (in rows) each of which has been scored on each of many variables (in columns). Five of the variables are named var1, var2, var3, var4, var5 using headers. The other variables are named using other conventions. I can create a new variable called var6 with the value 15 for each record with this code: > var6=var1+var2+var3+var4+var5

Dear R experts. I might be missing something obvious. I have been trying to fix this problem for some weeks. Please help. #data ped <- c(rep(1, 4), rep(2, 3), rep(3, 3)) y <- rnorm(10, 8, 2) # variable set 1 M1a <- sample (c(1, 2,3), 10, replace= T) M1b <- sample (c(1, 2,3), 10, replace= T) M1aP1 <- sample (c(1, 2,3), 10, replace= T) M1bP2 <- sample (c(1, 2,3), 10, replace= T)

Given the following dataframe: A=1:10 B=(a-5)^2 DATAFRAME=data.frame(A,B) How can I sort DATAFRAME increasing (or decreasing, for that matter) by B without making reference to A, or any other column? I've read ?order and ?sort but cannot seem to figure this out. Thank you. Mark

I'm trying to sort a DATAFRAME by a column "ID" that contains alphanumeric data. Specifically,"ID" contains integers all preceeded by the character "g" as in: g1, g6, g3, g19, g100, g2, g39 I am using the following code: DATAFRAME=DATAFRAME[order(DATAFRAME1$ID),] and was hoping it would sort the dataframe by ID in the following manner g1, g2, g3, g6, g19,

Hi all, I am trying to filter the element of a df that start with "TF", like this: alfa = c(123221,"TF13124",41243,"TF1234",32414,"TF13124","TF14333",2134123,"TF1234") beta =

I have data like so: time datum 30 12 60 24 90 37 120 41 150 8 In addition to standard deviation, I want to measure the average of the differences in data for each time interval, i.e. average of 24-12, 37-24, 41-37, 8-41. Is there a statistical term for this task? Which package should I use please? rhelp at conference.jabber.org

An undergraduate here, so do not hesitate to let me know if you feel that I''m heading in a wrong direction. I have a data frame containing panel data across 10 years (hence 120 months). I want to be able to run regression separately for each month (or year). The below shows how I ran the regression for each month, but I need to know how I would combine the regression results

I might have factored the gender. I'm not sure it would in any way be quicker. But might be to some extent easier to develop variations of. And is sort of what factors should be doing... # make dummy data gender <- c("Male", "Female", "Male", "Female") WC <- c(70,60,75,65) TG <- c(0.9, 1.1, 1.2, 1.0) myDf <- data.frame( gender, WC, TG ) #

I am looking for the most efficient way to replace all occurrences of NaN in a data frame with NA. I can do this with a double loop, but it seems that there should be a higher level and more efficient way. With is.na, I could use ifelse, but if.nan seems not to have similar capabilities. TIA, Jon Peck Jon K. Peck jkpeck@aya.yale.edu [[alternative HTML version deleted]]

Dear Group: I am working with a data frame containing 316 rows of individuals with 79 variables. Each of these 79 variables have values that range between -4 to +4, and I want to subset this data frame so that in the resulting new dataframe, values of _all_ of these variables should range between -3 and +3. Let's say I have the following dataframe (it's a toy example with 4 individuals

There are many techniques Callum and yours is an interesting twist I had not considered. Yes, you can specify what integer a factor uses to represent things but not what I meant. Of course your trick does not work for some other forms of data like real numbers in double format. There is a cost to converting a column to a factor that is recouped best if it speeds things up multiple times. The

All - Not sure if this is a real programming question, but here goes: I have data that looks like Lake Length Weight 1 158 45 1 179 70 1 200 125 1 202 150 1 206 145 1 209 165 1 210 140 1 215 175 1 216 152 1 220 150 1 221 165 ... where lake goes from 1 - 84 and the number of rows for each lake is variable (but > ~20). I'm trying to do two things: 1) build a simple linear model of the

Hi everyone, I have two columns: ? ?A? ? ? ? ? ? ? ?B ? ?1? ? ? ? ? ? ? ?1? ?1? ? ? ? ? ? ? ?0 ? ?0? ? ? ? ? ? ? ?1 ? ?0? ? ? ? ? ? ? ?0 I have 4 categories which are: 1) if A = 1 and B =1 then A1 = 1, else A2 = 0, A3 = 0, A4 = 0 2) if A = 1 and B =0 then A1 = 0, else A2 =1, A3 = 0, A4 = 0 3) if A = 0 and B = 1 then A1 = 0, else A2 = 0, A3 = 1, A4 = 0 4) if A = 0 and B =0 then A1 = 0, else A2 =

Hi, How can I get the values of mean and median (not only points but values too) on the boxplot. I am using boxplot function from graphics package. Following is my data set > df [1] 5 1 1 0 0 10 38 47 2 5 0 28 5 8 81 21 12 9 1 12 2 4 22 3 > mean.val <- sapply(df,mean) > boxplot(df,las = 1,col = "light blue") > points(seq(df), mean.val,

Hi Guys, Do you any one know how to convert a long format table to an adjacency matrix used in sna? The long table looks like p1 p2 counts a b 100 a c 200 a d 100 b c 80 b d 90 b e 100 c d 100 c e 40 d e 60 and I want to convert it to an adjacency matrix which can be used in sna? Any methods will be appreciated! btw, besides sna package, is there any better package can be used in social

I would like to remove columns of a df which have too many NAs. I think that summary() should give me the information, I just don't know how to access it. Advice? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall McCormick Road