search for: value_var

...56 | Choice A 456 | Choice B ... I thought that I should do the following 1. Make the data set "wide", counting the observations so the data looks like this: ID | Count of Preference A | Count of Preference B 123 | 1 | 1 ... Using table1 <- dcast(data,ID ~ Page,fun.aggregate=length,value_var='Page' ) 2. Create a correlation matrix of preferences cor(table2[,-1]) How would I restrict my correlation to show preferences that met a minimum sample threshold? Can you confirm if the two following commands do the same thing? What would I do from here (or am I taking the wrong approac...

Hi all, Is there any chance that readRDS and saveRDS might one day become read.rds and write.rds? That would make them more consistent with the other reading and writing functions. Hadley -- Assistant Professor / Dobelman Family Junior Chair Department of Statistics / Rice University http://had.co.nz/

...Site group. The objective is to rearrange to: Site 1 Site 210 513 714 9 ........ I have tried a variety of approaches, none of which worked. The following code does not work but suggests the task might be possible, perhaps in 2 steps. Df2 <- dcast (Data1, Length ~ Site, value_var = "Length") Its output is: Length Site 1 Site 210 10 NA13 13 NA14 14 NA.......5 NA 57 NA 79 NA 9 One easy solution is to reshape in Excel and import a new dataframe for use but I would lik...

...mydata <- data.frame( x=sample(LETTERS[23:26],100, replace=TRUE), y=rnorm(100, mean=2), id=sample(letters[1:4], 100, replace=TRUE)) acast(mydata , id ~ x) # not so fine ================================================================= produces this : Using id as value column: use value_var to override. Aggregation function missing: defaulting to length W X Y Z a 7 5 5 7 b 6 9 6 12 c 1 4 5 6 d 6 14 5 2 Why does reshape2 think it needs an aggregation function here> Thanks

This is my reproducible example: example<-structure(list(SENSOR = structure(1:6, .Label = c("A", "B", "C", "D", "E", "F"), class = "factor"), VALUE = c(270, 292.5, 0, 45, 247.5, 315), DATE = structure(1:6, .Label = c(" 01/01/2010 1", " 01/01/2010 2", " 01/01/2010 3", " 01/01/2010

...------ Subject: Re: [R] sum data from data.frame in a matrix Date: Wed, 23 Feb 2011 00:10:52 -0800 From: Dennis Murphy <djmuser at gmail.com> To: Nicolas Gutierrez <nicolasg at uw.edu> Hi: ...and a second way, using the reshape2 package: library(reshape2) dcast(df, yloc ~ xloc, value_var = 'yield', fun = sum) yloc 10 11 12 1 10 0 81 0 2 11 0 0 30 3 12 95 0 0 Dennis On Tue, Feb 22, 2011 at 11:30 PM, Nicolas Gutierrez <nicolasg at uw.edu <mailto:nicolasg at uw.edu>> wrote: Hi all (again), I have a data frame "pop":...

Hi, I've tried to look through all the previous related Threads/posts but can't find a solution to what's probably a simple question. ? I have a data frame comprised of three columns e.g.: ? ID1?ID2?Value a?b?1 b?d?1 c?a?2 c?e?1 d?a?1 e?d?2 ? I'd like to convert the data to a matrix i.e.: ? ?a b c d e a n/a 1 2 1 n/a b 1 n/a n/a 1 n/a? c 2 n/a n/a n/a 1 d 1 1 n/a n/a 2 e n/a n/a 1

Seems like this should be easy but I'm struggling a bit. How do I rearrange a data frame to go from the first one to the second shown below ? State Date lbs TX 200701 400 TX 200702 650 TX 200703 950 TX 200704 1000 FL 200701 200 FL 200702 300 FL 200703 500 FL 200704 333 NJ 200701 409 NJ 200702 308 NJ 200703 300 NJ 200704 800 Date TX FL NJ 200701 400 200 409 200702 650

Whenever I use "..." in the formula of the cast function, from the reshape package, I get the following error: Error in `[.data.frame`(data, , variables, drop = FALSE) : undefined columns selected For example: data(french_fries) #available in the reshape package > head(french_fries) time treatment subject rep potato buttery grassy rancid painty 61 1 1 3 1

...peedup.elapsed1 <- tstats$meanElapsed_unvectorized / tstats$meanElapsed_1CoreVectorized tstats$speedup.elapsed3 <- tstats$meanElapsed_1CoreVectorized / tstats$meanElapsed_SMPVectorized speedupVectorizing <- dcast(tstats[c('g','n','speedup.elapsed1')], g~n, value_var='speedup.elapsed1') speedupSMP <- dcast(tstats[c('g','n','speedup.elapsed3')], g~n, value_var='speedup.elapsed3') return(list(vectoring=speedupVectorizing, smp=speedupSMP)) } timeSMP(10,1) # make it thrash as much as possible timeSMP...

> str(data) 'data.frame': 250 obs. of 3 variables: $ student: chr "A" "B" "C" "D" ... $ data : num 20.2 20.4 22.5 22.1 23.3 ... $ param : Factor w/ 4 levels "AGE","SCHOOL",..: 1 1 1 1 1 1 1 1 1 1 Hi , i would like to split the dataframe so that each level of param is a column At the end it should look like

I have some data 'myData' in wide form (attached at the end), and would like to convert it to long form. I wish to have five variables in the result: 1) Subj: factor 2) Group: between-subjects factor (2 levels: s / w) 3) Reference: within-subject factor (2 levels: Me / She) 4) F: within-subject factor (2 levels: F1 / F2) 5) J: within-subject factor (2 levels: J1 / J2) As this is the

Hello, I have a dataset with student performance on a math test. There are multiple cases for each student (identified by id) and the concept as a variable. > rtest id test subject grade concept correct tested per_corr year 1 1 83 Mathema 8 8.2.D 1 1 100 2011 2 1 83 Mathema 8 8.3.A 1 2

Hi all, Say I have a data frame something like the one below with different sample vials, measured before(B) and after(A) some process, with a value recorded at each measurement point vial measure value 1 B 26 1 A 12 2 B 45 2 A 30 3 B 32 3 A 27 4 B

Hello, I'd like to transpose data to create an analysis-friendly dataframe. See below for an example, I was unable to use t(x) and I couldn't find a function with options like PROC TRANSPOSE in SAS. The ideal solution handles variable quantities of SITE - but beggars can't be choosers. :-) Thank you in advance, Mike ## INPUT DATA USER_ID<-c(1,1,1,2,2,2,3,3,4) SITE

Dear all, I am having trouble creating summary tables using aggregate function. given the following table: Var1 Var2 Var3 dummy S1 T1 I 1 S1 T1 I 1 S1 T1 D 1 S1 T1 D 1 S1 T2 I 1 S1 T2 I 1 S1 T2 D 1 S1 T2 D 1 S2

Hi Hadley et all, I am struggling with reshape2 and melt works and melt_check (filtered151) seems fine My cast command was acast (filtered151, Time ~ Species ~ Number) > melt_check (filtered151) Using time, Species as id variables $id [1] "time" "Species" $measure [1] "Number" When I execute cast the data matrix is in the correct order but the data

HI, Dear R community, I am trying to created new variables and put into a data frame through a loop. My original data set: head(first) probe_name chr_id position array1 1 C-7SARK 1 849467 10 2 C-4WYLN 1 854278 10 3 C-3BFNY 1 854471 10 4 C-7ONNE 1 874460 10 5 C-6HYCN 1 874571 10 6 C-7SCGC 1 874609 10 I have

A late friday afternoon coding question. I'm having a hard time thinking of the correct search terms for what I want to do. If I have a df like this: a <- data.frame(name=c(rep('a',10),rep('b',15)),year=c(1971:1980,1971:1985),amount=1:25) name year amount 1 a 1971 1 2 a 1972 2 3 a 1973 3 4 a 1974 4 5 a 1975 5 6 a 1976

This is my first excursion into using reshape2 and I want to ensure that the melt() function call is syntactically correct. The unmodifed data frame is organized this way: head(tds.anal) site sampdate param quant 1 UDS-O 2006-12-06 TDS 10800 4 STC-FS 1996-06-14 Cond 280 7 UDS-O 2007-10-04 Mg 1620 9 UDS-O 2007-10-04 SO4 7580 19 JCM-10B 2007-06-21 Ca 79 20