similar to: Summing with NA

Hi, How can I create an NA? for example, i have this program but it has errors > x=scan() 1: 1 2 3 4 5 6: Read 5 items > "na"*x Error in "na" * x : non-numeric argument to binary operator what should I multiply x so that I will get an NA? And I really need to multiply that with my x vector. I need this output: (na,na,na,na,na) Thank you for your time and help!=) --

Hi everyone! May I request again for your help? I need to make some codes using if else statements... Can I do an "if-else statement" inside an "if-else statement"? Is this the correct form of writing it? Thank you.=) Example: for (v in 1:6) { for (i in 2:200) { if (v==1) (if max(x*v-y*v)>1 break()) if (v==2) (if max(x*v-y*v)>1.8 break()) if (v==3) (if

Hi, may I ask for your help... What is the R code if I want to count the number of times that "2" appeared in the following R output > k [1] 1 1 1 1 1 1 3 1 2 1 1 1 1 1 1 1 1 3 2 1 1 4 1 1 1 1 1 5 1 1 Thank you for your help. :-) -- View this message in context: http://n4.nabble.com/How-to-count-the-number-of-occurence-tp1661733p1661733.html Sent from the R help mailing list

Dear All If I have the following dataset V1 V2 x y y x z b a c b j d l c o How do I use R command to get the total number of different letter in column "V1" column "V1" has 7 different letters. Thank you -- View this message in context: http://r.789695.n4.nabble.com/Summing-up-Non-numeric-column-tp3077710p3077710.html Sent from the R help mailing list archive

Dear R-helpers, New to R, I'm in the middle of a project that I'm using to force me learn R. I'm running into some behavior that I don't understand, and I need some advice. In the last week I've gotten some great advice from the list on visualizing my data, and I was hoping people could help me get over another barrier I've encountered to my progress. Before I

Hi all, When I try to sum a few columns in a data frame (which has NA?s randomly distributed as elements), I am not able to get the summing operation to ignore the NA?s. Let me explain with the following code : ################################? a<-structure(list(a1 = c(NA, 2, 3, NA, 5, 6, NA, 8, 9, NA), a2 = c(NA, + 4, 5, 5, NA, 7, 8, 8, NA, 10), a3 = c(2, NA, 6, 8, NA, 12, 14, + NA, 18, 20)),

I'm observing that base::sum(x, na.rm=FALSE) for typeof(x) == "double" is much more time consuming when there are missing values versus when there are not. I'm observing this on both Window and Linux, but it's quite surprising to me. Currently, my main suspect is settings in on how R was built. The second suspect is my brain. I hope that someone can clarify the below

#I would like to interpolate a straight line between 06/08/06 04:16:00 - 06/08/06 20:31:00 with values and then sum them. This is an estimate of ecosystem #respiration and I will be using this in a larger context(48 days of these diurnal curves), but for right now I am just trying to figure out how to do it for this one #day example. I have some other code for Ecosystem (stream) Metabolism that

This is a great example how you cannot figure it out after spending two hours troubleshooting, but a few minutes after you post to R-devel, it's just jumps to you (is there a word for this other than "impatient"?); Let me answer my own question. The discrepancy between my sum2() code and the internal code for base::sum() is that the latter uses LDOUBLE = long double (on some system

Hi All, I have a large dataset I need to re-structure. It looks something like this: YearAreaQBinFD20001150200011101200011152320001120122000112512000215120002110 6200021151120002120132000212532000125020001210120001215232000122012200012251 20002251200022103200022151220002220132000222532001…2011 And I need to create different vectors (Bin, FD) summing by year and/or by area; For example, I need

Hi All, Year Area Q Bin FD I have a large dataset I need to re-structure. It looks something like this: 2000 1 1 5 0 2000 1 1 10 1 2000 1 1 15 23 2000 1 1 20 12 2000 1 1 25 1 2000 2 1 5 1 2000 2 1 10 3 2000 2 1 15 15 2000 2 1 20 11 2000 2 1 25 3 2000 1 2 5 0 2000 1 2 10 1 2000 1 2 15 23 2000 1 2 20 12 2000 1 2 25 1 2000 2 2 5 1 2000 2 2 10 3 2000 2 2 15 15 2000 2 2 20 11

Hello, I am trying to figure out how to do a sum of items within a row. For example, I have a data frame something like this: A1 B1 ... A2 B2 ... 1 1 4 1 4 2 2 5 2 5 3 3 6 3 6 What I want, is for each row, to get A1 + A2, B1 + B2, etc. which would, perhaps, give me a vector something like this c(2, 8, ... 4, 10 ... 6, 12). Does anyone know of a simple

This is the same set of data that I have been working with for those in the know. it is a matrix of ~174 columns and ~70,000 rows. I have it as a zoo object, but I could read it in as just a matrix as long as the date time stamp won't be corrupted. here is an example of what a column would look like: 1/1/06 12:00, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5,6 ,7, NA #read in with the

#this is my little function that I would like to use the column names of the x and y arguments in the function. I would like it to read # site1-site2 how would I do this diff.temp <- function(x, y ,use="pairwise.complete.obs") { na.method <- pmatch(use, c("all.obs", "complete.obs", "pairwise.complete.obs")) par(mfrow=c(2,1))

Hi I'm trying to sum functions of lists with different lengths. Here is a simplified example of the problem: r=list(1:3,1:5,1:2) r [[1]] [1] 1 2 3 [[2]] [1] 1 2 3 4 5 [[3]] [1] 1 2 x=function(i,j) sum(j*r[[i]]) # x is a function of two parameters: i & j y=function(j) # y is the sum of x over i + {

I have a data frame that is 122 columns and 70000ish rows it is a zoo object, but could be easily converted or read in as something else. It is multiparameter multistation water quality data - there are a lot of NA s. I would like to find "chuncks" of data that are free of NA s to do some analysis. All of the data is numeric. Is there a way besides graphing to find these NA less

Suppose I have the following: x1<-as.vector(rnorm(10)) x2<-as.vector(rnorm(10)) x3<-as.vector(rnorm(10)) x4<-as.vector(rnorm(10)) x5<-as.vector(rnorm(10)) x6<-as.vector(rnorm(10)) x7<-as.vector(rnorm(10)) x8<-as.vector(rnorm(10)) x9<-as.vector(rnorm(10)) x10<-as.vector(rnorm(10)) I would like the mean of x1 to x6 for each vector position. I would do something else

Dear R users, the colSums function from the base package returns zero if there are no values in a range to be summed over (after removing missing values with na.rm = TRUE). Is there some way to make it return NA in that case just like colMeans does? Or any other function or some good way to achieve that? Any ideas are be welcome. Regards, Martin Ivanov

Dear R users, I am new to R and have some query. I am having a dataset with binary output 0's and ones. But along with it it has NA's too. I want to sum all the rows and get the sum total for each column. But whenever there is a NA in an row the sum of the row is returned as NA so I am not able to sum up the values. *row.sums.m <- apply(dummy.curr.res.m,1,sum)* It would be helpful

Dear R community, I'm trying to develop a fast way of summing specific rows of a large data frame. Here is an example of the kind of data frames I'm dealing with: > refls H K L M/ISYM BATCH I SIGI 43247 1 0 5 21 79 61.44117 2.20553 1040 1 0 5 257 6 15.16316 0.54431 2324 1 0 5 257 5 46.76152 1.67858 31515 1 0 5 259 60 57.97305