similar to: change value in one cell

Hi all, I've searched everywhere to try to find out how to do this and have had no luck. I am trying to construct identifiers for couples in a dataset. Essentially, I want to identify couples using more than one column as identifiers. Take for instance: obs unit home z sex age 1 015029 18 1 1 053 2 015029 18 1 2 049 3 015029 01 1 1 038 4 015029 01 1

In the hypothetical example below, how do I add two segments() into the two panels, respectively? Say segments(x0=5, y0=10, x1=5, y1=20) on the left and segments(x0=15, y0=-10, x1=15, y1=-2) on the right? Many thanks in advance, Yuelin Li. ps. part of the code came from a solution given by Deepayan Sarkar. ------------------- library(lattice) set.seed(12345) x <- 0:20 y.male.obs <- - 1.2

Hello all, I hope something is not already posted regarding this exact problem I am trying to solve. I've read through the forums and previous postings and am still confused as to how to approach this. Basically, what I am trying to do is construct variables that utilizes an average of a variable from a grouping, or higher order, variable. For instance, in my dataset I have variables, with

Merry Xmas to all, I am writing a function and curiously this runs sometimes on one data set and fails on another and i cannot figure out why. Any help much appreciated. If i run the code below with data <- iris[ ,1:4] The code runs fine, but if i run on a large dataset i get the following error (showing data structures as matrix is large) > str(cluster.data) num [1:9985, 1:811] 0 0 0 0

'grepl' returns a logical vector; you have to use this to get your subset. You can use: df_tq <- subset(df, grepl("t1", Command)) df_t2 <- subset(df, grepl("t2", Command)) # if you want to also get a subset that has both, use df_both <- subset(df, grepl("t1", Command) & grepl("t2", Command)) Jim Holtman Data Munger Guru What is

Inline. -- Bert On Tue, Apr 26, 2016 at 2:25 PM, Andr? Luis Neves <andrluis at ualberta.ca> wrote: > Ok. I`m trying to run a Poisson glmm with an observation-level random > intercept. But I`m getting the following error for the 'Baci' variable: > > 'Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in > pwrssUpdate'. I guess this message

Ok. I`m trying to run a Poisson glmm with an observation-level random intercept. But I`m getting the following error for the 'Baci' variable: 'Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in pwrssUpdate'. I guess this message is because the baci variable is not a an integer, and cannot be transformed into an integer as R has a threshold of 2x10^9 even in

I ran into a puzzling minor behaviour I would like to understand. Reading in a csv file, I find an extraneous "." after a column header, "in" [short for "inches"] thus, "in.". Is this due to "in" being reserved? I initially blamed this on RStudio or to processing the data through LibreCalc. However, the same result occurs in a console R session.

Hi, I' am interested in differences between sample's result when samples consist of full elements and consist of only distinct elements. When sample consist of full elements it take about 120 sec., but when consist of only distinct elements it take about 4.5 or 5 times more sec. I expected that opposite of this result, because unique(sample) has less elements than full sample. Code as

now after this: df_both <- subset(df, grepl("t1", Command) & grepl("t2", Command)) I use factor to apply the subset to df but then the Command level becomes 0 df_both$Command=factor(df_both$Command) str(df_both) $ Protocol : Factor w/ 0 levels: Do you know what is the reason? Thanks for replying On Sunday, April 24, 2016 12:18 PM, jim

Hi, May be this helps: dat1<- as.data.frame(table1) ?dat2<- as.data.frame(table2) names(dat2)<-c("V3","V4") library(plyr) res<-join(dat1,dat2,type="full") ?res[is.na(res)]<- 0 ?res #? V1 V2 V3 V4 #1? 1? 1? 0? 0 #2? 1? 2? 0? 0 #3? 0? 0? 0? 1 #4? 0? 0? 0? 4 ?combinedtable<-as.matrix(res) ?colnames(combinedtable)<- NULL ?combinedtable #???? [,1] [,2]

i can see source code of function > cor function (x, y = NULL, use = "everything", method = c("pearson", "kendall", "spearman")) { na.method <- pmatch(use, c("all.obs", "complete.obs", "pairwise.complete.obs", "everything", "na.or.complete"))

Dear R-help list, Part of a program I wrote seem to take a significant amount of time, therefore I am looking for an alternative approach. In order to explain what is does: - the input is a sorted vector of integer numbers - some higher numbers may be derived (using a mathematical formula) from lower numbers, therefore they should be eliminated - at the end, the vector should contain only

Hi, I have a dataframe: (obs <- data.frame(a=c(1,2,2,3,3,3), b=c(1,2,3,4,4,5), c=1:2)) attach(obs) In reality its about 1 million rows. Some of the datasets have same contents in col a and! b like row 4 and 5. I want to do some calculations on col c within the duplicated rows and merge them afterwards: layer <- function(x) round((1-prod(1-x/100))*100,0) (covnew <- aggregate(c,

This is an example from chapter 11 of the 6th edition of Devore's engineering statistics text. It happens to be a balanced data set in two factors but the calculations will also work for unbalanced data. I create a factor called 'cell' from the text representation of the Variety level and the Density level using '/' as the separator character. The coefficients for the linear

Good Evening- I have a dataframe that has 10 columns that has a header and 7306 rows in each column, I want to combine these columns into one. I utilized the stack function but it only returned 3/4 of the data...my code is: where nfcuy_bw is the dataframe with 7305 obs. and 10 variables Once I apply this code I only receive a data frame with 58440 obs. of 2 variables, of which there should be

Hi r-users,   I would like to compare the cdf between historical and predicted. My x.obs and x.pre are the frequency data in classes of 0-300. I tried: plot(ecdf(x.obs),ecdf(x.pre),type="l",col="red")   and it gives me: Error in plot.stepfun(x, ..., ylab = ylab, verticals = verticals, pch = pch) :   argument 4 matches multiple formal arguments   Thank you so much for any

Hi I have the following df and I created two subsets but I don't know how to use these subsets as the colors of my plot. data.frame': 36919 obs. of 162 variables $TE :int 38,41,11,52,48,75,..... $TR :int 100,210,548,546,..... $Command :factor W/2229 levels

I have a large dataset organised in choice groups see below. Each choice represents a separate occasion with 1 product chosen out of the 6 offered.            +-------------------------------------------------------------------------------------------------+      | dn   obs   choice      acid   br                 date       cdate   situat~n   mth   year   set |     

Hi, I have sort of a newbie question. I've seriously put a lot of effort into how to handle simple replicates in a repeated ANOVA design, but haven't had much luck. I really liked reading "Notes on the use of R for psychology experiments and questionnaires", by Jonathan Baron and Yuelin Li ( http://www.psych.upenn.edu/~baron/rpsych/rpsych.html ) but still didn't run across