similar to: Binning question (binning rows of a data.frame according to a variable)

I am hoping for some assistance with a problem that has puzzled me. Immediately below is the error messages I obtained when I tried to perform two functions. (A) tapply(outcome,na.rm=T,grp,mean) Error in tapply(outcome, na.rm = T, grp, mean) : arguments must have same length +++++++++++++++++++++++++++++++++++++++++++++++ (B) library(nlme) > anova(lme(outcome ~ grp * time,

I'm using this code to plot a smoothed line. These two columns of data really represent 4 groups and I'd like to plot a separate line for each group but have them all in the same plot. The R-Docs for lowess do not seem to indicate some type of "GROUPS=var_name" option. What would be the syntax for this? plot(AWGT ~ lipid ) lines(lowess(lipid , AWGT, f=.8)) -- Dean

Dear r-help mailing list, this seems stupid, but I actually don't find the solution: if I have a vector of numbers x of length n, ranging, say, from -3 to 4, if I do barplot (x) all the values below 0 go downwards, and all the positive values go upward. How can I make them all begin from the minimum pointing upwards? Thanks! Gabriele Zoppoli, MD Ph.D. Fellow, Experimental and Clinical

First, thanks to everyone who helped me get to grips with R in (x)emacs (I get confused easily). Special thanks to Stephen Eglen for continued support. My question is about non-linear binning, or density functions over distributions governed by a power law ... y ~ mu*x**lambda # In one of its forms # (can't find Pareto in the online help) Looking at the following

Hi, How can plot a frequency distribution curve for the following data.    V1      V2 1   1 160.54% 2   1 201.59% 3   1  18.45% 4   1 179.03% 5   1 274.37% 6   1   0.00% 7   1  24.52% 8   1  39.17% 9   3  43.72% 10  1  53.06% 11  1  64.97% 12  1  79.84% 13  1  98.08% 14  1 115.32% 15  1 127.96% 16  1 155.38% 17  1 157.25% 18  1 193.17% 19  1  51.53% 20 15  99.32% 21  1 106.86% 22  1 219.44%

Dear R-users, I am looking for an elegant way to change some levels of a factor column in data frame according to a condition. Lets look at the following data frame: > data.frame(crit1=gl(2,5), crit2=factor(letters[1:10]), x=rnorm(10)) crit1 crit2 x 1 1 a -1.06957692 2 1 b 0.24368402 3 1 c -0.24958322 4 1 d -1.37577955 5 1 e

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

...well, I don't think this is exactly the expected result (see my post) to be noted that the columns affected should be "A" and "B" thanks for the help max ----- Messaggio originale ----- Da: "Rui Barradas" <ruipbarradas at sapo.pt> A: "Massimo Bressan" <massimo.bressan at arpa.veneto.it>, "r-help" <r-help at

OPS, Sorry i did not read the post carfully. Mine will not work if you have zeros on columns A and B.. But you could modify it to work for specific columns i believe. EK On Wed, Nov 22, 2017 at 8:37 AM, Ek Esawi <esawiek at gmail.com> wrote: > Hi *Massimo,* > > *Try this.* > > *a <- mydf==0mydf[a] <- NAHTHEK* > > On Wed, Nov 22, 2017 at 5:34 AM, Massimo Bressan

Hello, Try the following. icol <- which(grepl("flag", names(mydf))) mydf[icol] <- lapply(mydf[icol], function(x){ is.na(x) <- x == 0 x }) mydf # A A_flag B B_flag #1 8 10 5 12 #2 7 NA 6 9 #3 10 1 2 NA #4 1 NA 1 5 #5 5 2 0 NA Hope this helps, Rui Barradas On 11/22/2017 10:34 AM, Massimo Bressan

yes, it works, even if I do not really get how and why it's working the combination of logical results (could you provide some insights for that?) moreover, and most of all, I was hoping for a compact solution because I need to deal with MANY columns (more than 40) in data frame with the same basic structure as the simplified example I posted thanks m ----- Messaggio originale ----- Da:

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

Do you mean like this: mydf <- within(mydf, { is.na(A)<- !A_flag is.na(B)<- !B_flag } ) > mydf A A_flag B B_flag 1 8 10 5 12 2 NA 0 6 9 3 10 1 NA 0 4 NA 0 1 5 5 5 2 NA 0 Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into

Dear anyone who knows more about R than me (so everyone). I have been bashing my head on the keyboard all day trying to do something with my table. I have some data, like so: yyyy-mm Rainfall(mm) 1 1977-02 17.4 2 1977-03 34.0 3 1977-04 26.2 4 1977-05 42.6 5 1977-06 58.6 6 1977-07 23.2 7 1977-08 26.8 8 1977-09 48.4 9

Hi *Massimo,* *Try this.* *a <- mydf==0mydf[a] <- NAHTHEK* On Wed, Nov 22, 2017 at 5:34 AM, Massimo Bressan < massimo.bressan at arpa.veneto.it> wrote: > > > 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) >

Hi, I have a data matrix in which there are 1000 rows by 30 columns. The first column of each row is a numeric indicating the number of trips taken to a particular location with location attributes in the following column entries for that row. I want to repeat each row based on the number of trips taken (as indicated by the number in the first column)...i.e., if 1,1 indicates 4 trips, I want

Any simple way to take a (2D) table and 'rotate' it so all the rows become columns and the columns rows? I'll wager there is a simple way ;) - but I can't find it :(

Hello, we have 80 text files with matrices. Each matrix represents a map (rows for latitude and columns for longitude), the 80 maps represent steps in time. In addition, we have a vector x of length 80. We would like to compute a regression between matrices (response through time) and x and create maps representing coefficients, r2 etc. Problem: the 80 matrices are of the size 4000 x 3500 and we

Dear all, I have a data.frame with some NAs that can happens anywere, and I would like to keep only rows without NAs. Thanks in advance for your help, and Merry Xmas. myvect<-runif(100) myvect[sample(1:100)[1:5]]<-NA myDF<-data.frame(matrix(myvect,ncol=5)) myDF miltinho [[alternative HTML version deleted]]

I have the following datasets: id d1 d2 d3 d4 d5 d6 d7 d8 1 100 0.3 0.4 -0.2 -0.3 0.5 0.6 -0.9 -0.8 2 101 0.3 0.4 0.5 0.6 -0.2 -0.4 -0.5 -0.6 what I am trying to accomplish: loop through the rows && do the following: if the values from the columns of the current row >0 then sum_positive=total if the values from the columns of the current row <0 then