similar to: persuade tabulate function to count NAs in a data frame

Hello everybody, I have a data frame in R which is similar to the follows. Actually my real 'df' dataframe is much bigger than this one here but I really do not want to confuse anybody so that is why I try to simplify things as much as possible. So here's the data frame. id <-c(1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3) a

Hello everyone, I'd like to ask you a question again, basically focusing on referring to different objects. Let's suppose we create the following databases this way: id <-c(1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3) a <-c(3,1,3,3,1,3,3,3,3,1,3,2,1,2,1,3,3,2,1,1,1,3,1,3,3,3,2,1,1,3) b <-c(3,2,1,1,1,1,1,1,1,1,1,2,1,3,2,1,1,1,2,1,3,1,2,2,1,3,3,2,3,2) c

Hello everyone, I'd like to ask you a question again, basically focusing on referring to different objects. Let's suppose we create the following databases this way: id <-c(1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3) a <-c(3,1,3,3,1,3,3,3,3,1,3,2,1,2,1,3,3,2,1,1,1,3,1,3,3,3,2,1,1,3) b <-c(3,2,1,1,1,1,1,1,1,1,1,2,1,3,2,1,1,1,2,1,3,1,2,2,1,3,3,2,3,2) c

Hello there, I have a problem concerning bootstrapping in R - especially focusing on the resampling part of it. I try to sum it up in a simplified way so that I would not confuse anybody. I have a small database consisting of 20 observations (basically numbers from 1 to 20, I mean: 1, 2, 3, 4, 5, ... 18, 19, 20). I would like to resample this database many times for the bootstrap process with

Hi again, I'd like to ask you a question again. I have a matrix like this: a <-matrix(c(1,2,3,4,5,6,7,8,9,10,11,12)) a [,1] [1,] 1 [2,] 2 [3,] 3 [4,] 4 [5,] 5 [6,] 6 [7,] 7 [8,] 8 [9,] 9 [10,] 10 [11,] 11 [12,] 12 Is there a proper way to change the dimensions of this matrix so that I'll get this as a result: [,1] [,2] [,3] [1,]

Hello everybody, I have a little problem in good old R. It is basically the following. I have this small database with 3 rows and the following columns: d1, d2, d3 and Highest d value - which selects the highest value from d1, d2, d3 in each row. d1 d2 d3 Highest d value 1 51.398426 39.111721 11.6086220 51.398426 2 4.057801

Hello there, I have a problem concerning bootstrapping in R - especially focusing on the resampling part of it. I try to sum it up in a simplified way so that I would not confuse anybody. I have a small database consisting of 20 observations (basically numbers from 1 to 20, I mean: 1, 2, 3, 4, 5, ... 18, 19, 20). I would like to resample this database many times for the bootstrap process with

Hello there, I don't know if I'm addressing my question to the right e-mail address, I hope I do. Actually I have a little problem concerning writing a code in R. I try to briefly sum up my problem. As you can see below, I created the functions "Equation1" and "Equation2" with some conditions. Equation1 <-function(x){ if

Hi there, I have a huge dataframe containing 70,000 observations. I have filtered this dataframe (let it's name be "transformed_dataframe") as I wanted to select only those observations which are greater than or equal to 60,001 regarding the very first identity column. So I have a transformed dataframe now including 10,000 obeservations (from 60,001 - to 70,000) and if you send

Dear R-community, I'd like to ask you a question concerning R again. I try to keep this simple because I am not willing to confuse you at all. I have a little data frame which I have created the following way: a <-c(1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4,5,5,5,5,5,6,6,6,6,6) b <-c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30) df

tabulate has .C("R_tabulate", as.integer(bin), as.integer(length(bin)), as.integer(nbins), ans = integer(nbins), PACKAGE="base")$ans The implementation of R_tabulate has if(x[i] != R_NaInt && x[i] > 0 && x[i] <= *nbin) and so copes with (silently drops) NA. Perhaps the .C could have NAOK=TRUE? This is useful in apply'ing tabulate to

Hi, I am using the quantile function currently and I have just bumped into a little problem. I have a very small data frame something like this: small_df <- c(7,3,4,7,1,10,12,1,12,4,4,8,6,11,9,10,4,13,3,9,6,5,2,10,7,14,2,7,10,10,7,8,2,11,3,10,11,3,11,14,12,7,6,11) small_df Now in the next step I would like to calculate the quantile value of the previous data frame at the probability of 95%

Hello, I'd like to ask you something again. I have a database and it has a column which looks like this one here: small_factor <- factor(c("d_variable1","d_variable2","d_variable3")) small_factor Now the thing is that I would like to convert each element of this factorized column. Basically I want to rewrite the words in it without the first two characters:

Peter, I thought this one was noted and fixed, but I could be wrong. R : Copyright 1999, The R Development Core Team Version 0.63.3 (March 6, 1999) .... [Previously saved workspace restored] > tabulate(1:10, 5) Process R:1 segmentation fault at Sat Apr 3 17:48:34 1999 -- (The following contact details become official on 1 May 1999, but the email

Hi all, I have a question about apply function. Is that possible to pass some non-default arguments in the function we want to apply ? For example: if "mat" is a matrix and I want to use the "tabulate" function on its row. The command apply(mat,1,tabulate) works but I have problem with this one apply(mat, 1, tabulate(nbins=4)). Any clue ? Thanks, Eric -- Eric

Hi, To clarify the default behavior that Boris is referencing below, note the definition of the 'bin' argument to the tabulate() function: bin: a numeric vector ***(of positive integers)***, or a factor. Long vectors are supported. I added the asterisks for emphasis. This is also noted in the examples used for the function in ?tabulate at the bottom of the help page. The second

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-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 All. Just in then case if anyone is using some old piece of hardware like the ibm x440, I could successfully run xen 4.2.3 on it. I have a working kernel .config and a set of xen boot parameters, along with some tuneups in the x440''s BIOS. The problem was quite complex (irq handling pci bus problems, ethtool magics, etc). Occasionally (once

|> x <- sample(0:2, 10, replace = TRUE) |> x [1] 1 0 2 1 0 2 2 0 2 1 |> tabulate(x) [1] 3 4 |> table(x) x 0 1 2 3 3 4 B. > On Nov 10, 2017, at 4:32 AM, Allaisone 1 <allaisone1 at hotmail.com> wrote: > > > > Thank you for your effort Bert.., > > > I knew what is the problem now, the values (1,2,3) were only an example. The values I have are

Hi, table1D() below can be up to 60x faster than base::table() for the 1D case. Here are the detailed speedups compared to base::table(). o With a logical vector of length 5M: 11x faster (or more if 'useNA="always"') o With factor/integer/numeric/character of length 1M and 9 levels (or 9 distinct values for non-factors):