similar to: Symbolic references - passing variable names into functions

is there a smart way of determining the number of pairwise present data in a data matrix with missings (maybe as a by-product of some statistical function?) so far, i used several loops like: for (column1 in 1:99) { for (column2 in 2:100) { for (row in 1:500) { if (!is.na(matrix[row,column1]) & !is.na(matrix[row,column2])) { pairs[col1,col2] <- pairs[col1,col2]+1

here's my question: suppose I have a matrix: mt<-matrix(1:12,ncol=6) now I have a vector vt<-c(1,2,2,2,1,2) which means I want to get: the 1st row for column1; the 2nd row for column2; the 2nd row for column3; the 2nd row for column4; ... that what I want is this vector: 1,4,6,8,9,12 Does anyone know how to do this fast? I know I can use for-loop to travel all columns,but

Hello, I need to take a dot product of each row of a dataframe and a vector. The number of columns will be dynamic. The way I've been doing it so far is contorted. Is there a better way? dotproduct <- function(dataf, v2) { apply(t(t(as.matrix(a)) * v2),1,sum) #contorted! } df = data.frame(a=c(1,2,3),b=c(4,5,6)) vec = c(4,5) dotproduct(df, vec) thanks,

Hi, Im trying to complete a list of jobs using SQL Querries and some "if else" commands but im stucked in some steps. Could any of you give me some help? -in COLUMN1 change the format 20JAN2000:00:00:00 to 20JAN2000 and exclude every row that date is different from 20. -extract the first character in COLUMN2 and creat COLUMN3 with that value ex: COL2,COL3 135,1 461,4 247,2 -in every

# Hello # I have a question regarding pairwise calculations of a matrix using a "for-loop." # Below I have a matrix "X" with 8 columns. These are genotypic data so Column1 & Column2 is # a unit, Column3 & Column4 is a unit, Column5 & Column6 is a unit, and Coulmn7 & 8 is a unit. # I have a loop designed to calculate the number of times an individual in

Readers, I have entered a file into r: ,column1,column2 row1,0.1,0.2 row2,0.3,0.4 using the command: dataframe<-read.table("/path/to/file.csv",header=T,row.names=1) When I try the command: dataframe[,2] I receive the response: NULL I was expecting: row1 0.2 row2 0.4 What is my error with the syntax please? Yours, r251 mandriva2009

I am writing a custom function that uses an R-function from the reshape package: cast. However, my question could be applicable to any R function. Normally one writes the arguments directly into a function, e.g.: result=cast(table1, column1 + column2 + column3 ~ column4, mean) (1) I need to be able to write this statement as follows: result=cast(table1, string_with_columns ~

Hello to all is there a function wich splits a data.frame (column1,column2,column3,....) into data1 <-(column1,column3....) #column2 = 1 data2 <-(column1,column3....) #column2 = 2 data3 <-(column1,column3....) #column2 = 3 ... Regards Knut

Apologies first, because I need to ramp up on Ruby and coding Ruby in Rails, however it''s my 3rd day with this beast :) so I''m asking : When I added protected methods to the model before it was like: protected method.................... end Would this be a valid way to write a protected method as well ?: attr_protected :column1, :column2 Perhaps this particular call

Hi ? I have a file. list.txt (two columns) ? column1??? column2 name??????? address ? ? I need to put in the letter file letter.txt eg: ? Dear: Chloe Address: CA ? Can I use this ? for i `cat list.txt` | sed 's/Chloe/$i.1; /CA/$i.2/g' $i.letter.txt ? Thank you for your help ? ? ? ? ? __________________________________________________________________ Looking for the perfect gift?

Hello everybody, I have experience coding with R, but am brand new to R Shiny. I am trying to produce an application that will allow users to upload their own dataset, select columns they want an ANOVA analysis run on, and generate graphs that will allow users to view their results. However, I am getting the following error: *"Argument is of length zero."* Being new to Shiny, I am

Hi, I have written boxplot commands of this form before, but I don''t quite understand why the function call is reporting a syntax error in this instance. All parameters passed to the function are strings. Thanks in advance. Payam > simplevar <- function(wframe,column1,column2) { + tframe <- get(wframe) + x1 <- which(names(wframe)==column1) + x2 <-

Hi Gregg. Just wanted to follow up on the solution you proposed. I had to make some adjustments to get exactly what I wanted, but it works, and takes about 15 minutes on our server configuration: temp <- ??????open_dataset( ????????????sources = input_files, ????????????format = 'csv', ????????????unify_schema = TRUE, ????????????col_types = schema( ????????????"ID_Key"

Hello Thomas, Consider that the primary bottleneck may be tied to memory usage and the complexity of pivoting extremely large datasets into wide formats with tens of thousands of unique values per column. Extremely large expansions of columns inherently stress both memory and CPU, and splitting into 110k separate data frames before pivoting and combining them again is likely causing resource

Hi, set.seed(45) test1<-data.frame(columnA=rnorm(7,45),columnB=rnorm(7,10)) #used an example probably similar to your actual data apply(test1,2,function(x) sprintf("%.1f",median(x))) #columnA columnB # "44.5"? "10.2" par(mfrow=c(1,2)) lapply(test1,function(x) {b<-

I am about to write general functions to read the output of simulations models. These model generate output files with different sections which I want to analyze plot etc. Since this will be used many people at the department I wanted to make sure that will do this in the best way. For instance I want to read a snippets of data from a text that look like this.

How is the server configured to handle memory distribution for individual users. I see it has over 700GB of total system memory, but how much can be assigned it each individual user? AAgain - just curious, and wondering how much memory was assigned to your instance when you were running R. regards, Gregg On Wednesday, December 11th, 2024 at 9:49 AM, Deramus, Thomas Patrick <tderamus at

Hi Thomas, Glad to hear the suggestion helped, and that switching to a `data.table` approach reduced the processing time and memory overhead?15 minutes for one of the smaller datasets is certainly better! Sounds like the adjustments you devised, especially keeping the multicore approach for `make_clean_names()` and ensuring that `ID_Key` values remain intact, were the missing components you

About to try this implementation. As a follow-up, this is the exact error: Lost warning messages Error: no more error handlers available (recursive errors?); invoking 'abort' restart Execution halted Error: cons memory exhausted (limit reached?) Error: cons memory exhausted (limit reached?) Error: cons memory exhausted (limit reached?) Error: cons memory exhausted (limit reached?)

Hi there I have two dataframes Dataframe_1 column_1 colum_2 121 12345 145 1675 167 2765 Dataframe_2 column_1 column2 121 abc 345 lmn 167 efg I want a resulting dataframe 121 12345 abc 167 2765 efg how do i go abt it Ramya -- View this message in context: http://n4.nabble.com/Dataframe-help-tp947934p947934.html Sent from the R