similar to: ifelse to speed up loop?

Hello all, This is one of those "Is there a better way to do this questions". Say I have a dataframe (df) with a grouping variable (z). This is my base data. Now I know that there is a higher order level of grouping that exist for my group variable. So what I want to do is create a new column that express that higher order level of grouping based on values in the sub-group (z in this

Hi everyone, I have a data frame one of whose columns is a character vector and the rest are numeric, and in debugging a script, I noticed that an ifelse call seems to be coercing the character column to a numeric column, and producing unintended values as a result. Roughly, here's what I tried to do: df: a data frame with, say, the first column as a character column and the second and

Dear R-help community, If I have a data.frame df as follows: > df x1 x2 x3 x4 x5 x6 1 5 5 1 1 2 1 2 5 5 5 5 1 5 3 1 5 5 5 5 5 4 5 5 1 4 5 5 5 5 1 5 2 4 1 6 5 1 5 4 5 1 7 5 1 5 4 4 5 8 5 1 1 1 1 5 9 1 5 1 1 2 5 10 5 1 5 4 5 5 11 1 5 5 2 1 1 12 5 5 5 4 4 1 13 1 5 1 4 4 1 14 1 1 5 4 5 5 15 1 5 5 4

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I'm trying to figure out how to repeat a series of commands in R and have the outputs added to a dataframe after each iteration. My code starts this way... a<-read.csv("File1.csv") b<-read.csv("File2.csv")

I am having a hard time understanding what is happening with ifelse. Let me illustrate: h <- numeric(5) p <- 1:5 j <- floor(j) x <- 1:1000 ifelse(h == 0, x[j+2], 1:5) [1] 2 3 4 5 6 My question is, "shouldn't this be retruning 25 numbers?" It seems that the ifelse should check 5 values of h for zero. For each of the 5 values I am thinking it should return an array of 5

I am trying to model a dependent variable as a threshold function of my independent variable. What I mean is that I want to fit different intercepts to y following 2 breakpoints, but with fixed slopes. I am trying to do this with using ifelse statements in the nls function. Perhaps, this is not an appropriate approach. I have created a very simple example to illustrate what I am trying to do.

Hi all, I have time series data in a matrix format 20 rows x 205 columns and have been trying to replace outliers with NA. My first column contains the outliers threshold (3 Standard deviations) for each row - here's a bit of the first row sd3 V1 V2 V3 V4 V5 V6 V7 V8 V9 1 13.03267 1797157 75 84 58 -1.958649 0.048775 2.056198 8.063622

Hello, I want to know if there is any way to avoid source() stopping when there is an error. Here is the content of my Main.R script: source("~/R/source/Constructor1.R") # Object1 should be constructed ifelse(exists("Object1"), # It's an S4 object print("Object1 exists"), # I can't avoid using 'validity'

On Fri, Aug 12, 2016 at 11:31 AM, Hadley Wickham <h.wickham at gmail.com> wrote: >> >> One possibility would also be to consider a "numbers-only" or >> >> rather "same type"-only {e.g., would also work for characters} >> >> version. >> >> > I don't know what you mean by these. >> >> In the

I have a question regarding significance testing for the difference in the ratio of means. The data consists of a control and a test group, each with and without treatment. I am interested in testing if the treatment has a significantly different effect (say, in terms of fold-activation) on the test group compared to the control. The form of the data with arbitrary n and not assuming equal

Hello I have a data set that looks like this; > b2 dato chr status PRRSvac PRRSsanVac PRRSsanDk PRRSdk 33 2007-12-03 090432 R?d SPF 34 2007-02-09 090432 R?d SPF+sanDK 35 2002-12-17 090432 R?d SPF+DK 36 2002-11-27 090432 R?d SPF+sanDK 37 2002-07-23

I would like to remove a loop to speed up my code. I want to remove a loop which references the last row. In general I want to a remove a loop which looks something like this: for 2 to number of rows in a matrix do{ if indextrow-1 is < currentIndexRow then do something. } My R code: for (i in 2:length(tUnitsort$Hour)){ ifelse(tUnitsort[i,4]>=tUnitsort[i-1,4],(tempMC

Dear all, As our previous email did not get any response, we try again with a reformulated question! We are trying to do something which needs an efficient loop over a huge array, possibly functions such as apply and related (tapply, lapply...?), but can't really understand syntax and examples in practice...i.e. cant' make it work. to be more specific: we are trying to apply a mask

Dear all, I am attempting to perform a calculation which counts the number of positive (or negative) values based on the sample mean (on a per-row basis). If the mean is>0 then only positive values should be counted, and if the mean is <0 then only negative values should be counted. In cases where the mean is equal to zero, the value -99999 should be returned. The following is an example

Hello again, Let say I have following vector: Vec <- c("0.0365780769", "(1.09738648244378)", "(0.812507787221523)", "0.5778069963", "(0.452456601362355)", "-1.8900812605", "-1.8716093762", "0.0055217041", "-0.4769192333", "-2.4133018880") Now I want to convert this vector to numeric vector. I

All, Martin: Thanks for this and all the other things you are doing to both drive R forward and engage more with the community about things like this. Apologies for missing this discussion the first time it came around and if anything here has already been brought up, but I wonder what exactly you mean when you want recycling behavior. Specifically, based on an unrelated discussion with Henrik

Hello All, Can anyone tell help me understand why the function below doesn't work and how I can fix it? Below are some sample data, some code that works on individual rows of the data, and my attempt to translate that code into a function. My hope is to get the function working and then to apply it to the larger data frame using ddply() from the plyr package or possibly some other approach.

Hi, Here i have been a matrix like this, *NAME AGE PALCE TRUE/FALSE* ABC 20 INDIA XYZ 30 FRANCE PQR 40 USA MNO 30 KENIYA DEF 25 AUSTRALIA Here,* TRUE/FALSE* Column containing empty values. So my requirement what is , need to change all the *TRUE/FALSE *column value into "*TRUE*" where *AGE =

When I run this code from an R-script: ddd = 360 + round ( atan2(-u,-v) / d2r ) print(class(ddd)) print(ddd) ifelse ( ddd>360, ddd-360, ddd ) print(ddd) I get this output: [1] "numeric" [1] 461 213 238 249 251 [1] 461 213 238 249 251 Why does ifelse not change the 461 to 101? I recreated the vector ddd and ran the same ifelse code