similar to: Tables and merge

Hello, I have a table (1) of the form q1 q3 q4 q8 q9 A 5 2 0 1 3 B 2 0 2 4 4 I have another table (2): q1 q2 q3 q4 q5 q6 q7 q8 q9 C 10 7 4 2 6 9 3 1 2 I would like to divide the numbers in table (1) by the number of the appropriate column in table (2): q1 q3 q4 q8 q9 A 5/10 2/4 0/2 1/1 3/2 B 2/10 0/4 2/2 4/1 4/2

From: Jyri Sarha <jsarha at ti.com> I optimized Speex resampler for NEON capable ARM CPUs. The first patch should speed up resampling on any platform that can spare the increased memory usage. It would be nice to have these merged to the master branch. Please let me know if there is anything I can do to help the the merge. The patches have been rebased on top of master branch in

I currently have a data frame whose rows correspond to each student and whose columns are different variables for the student, as shown below: Lastname Firstname CATALOG_NBR Email StudentID EMPLID Start 1 alastname afirstname 1213 *@uark.edu 10295236 # 12/2/2008 2 anotherlastname anotherfirstname 1213 **@uark.edu ## 10295236 9/3/2008 Xattempts Q1

This is my first post to R-help and I look forward receiving some advice for a novice like me... I?ve got a simple repeated (4 periods so far) 10-question survey data that is very easy to work on Excel. However, I?d like to move the compilation to R but I?m having some trouble operating on count list data in a neat way. The data C > str(C) 'data.frame': 551 obs. of 13

Hello! First of all, 100x thanks to Monty and colleagues: you have done an excellent job! I just didn't believe my ears when I first tested Oggenc 1.0 at q0 to q1 - it sounds AMAZINGLY GOOD !!! But as HDD drives are getting larger and cheaper, most of us move toward higher quality settings ......... I use q8, because: - I was able to ABX some test samples up to q4.99 - at q8 Ogg is still

If I'm understanding what's going on in this test correctly, what's happening is: * ARMTargetLowering::LowerCall prefers indirect calls when a function is called at least 3 times in minsize * In thumb 1 (without -fno-omit-frame-pointer) we have effectively only 3 callee-saved registers (r4-r6) * The function has three arguments, so those three plus the register we need to hold the

I have end of semester teaching evaluation data of the following form: > head(evaluations) Course Prefix Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 1 2330301 2 4 3 3 3 4 4 1 2 5 4 1 1 1 1 2 2330301 2 3 3 3 3 3 5 1 2 5 8 1 1 1 1 3 2330301 2 4 4 3 3 4 4 2 2 5 9 1 1 1 1 4 2330301 2 2 1 1 3 4 5 1 2 5 8

Hello R users! I have several data frames where some of the variables have many missing observations. For example, Q1 in one of my data frames has over 66% of its observations missing. I have tried imputation with mice but it does not work for all the data frames and I get the following message or a similar message to this: iter imp variable 1 1 Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11

Hi, I have 35 data files for reading. I would like get a program for performing reading of 35 files at once. All are of the type: Dados1.raw, Dados2.raw and so on. If the files have the same number of columns, I can read with the following commands: rm(list=ls()) filenames = list.files(path="~/Silvano/Arq", pattern="Dados+.*raw") names = substr(filenames, 1, 7) for(i in

Hi, I have a question about how to obtain the union of several data frame rows. I'm trying to create a common key for several tests composed of different items. Here is a small scale version of the problem. These are keys for 4 different tests, not all mutually exclusive: id q1 q2 q3 q4 q5 q6 1 A C 2 B D 3 A D B 4 C D B D I would like

R Experts, I have a dataframe made up of character vectors--these are results from survey questions. I need to convert them to factors. I tried the following which did not work: scs2<-sapply(scs2,as.factor) also this didn't work: scs2<-sapply(scs2,function(x) as.factor(x)) After doing either of above I end up with >str(scs2) chr [1:10, 1:10] "very important" "very

This mail depends upon the fact that I don't have a couple of good earphones ;-) I read in the site that q=6 is a very high quality, but does it contain perceivable differencies from the original? (for 95% of people, of course). I also found q=6 to produce files slightly bigger (1/10 bigger) than those produced with lame VBR q=2 (about 192 bps on average). I always thought LAME VBR q=2

Dear users, i'm using the sem package in R, because i need to improve a confermative factor analisys. I have so many questions in my survey, and i suppose, for example, that Question 1 (Q1) Q2 and Q3 explain the same thing (factor F1), Q4,Q5 and Q6 explain F2 and Q7 and Q8 explain F3... For check that what i supposed is true, i run this code to see if the values of loadings are big or not.

anyone able to explain logic behind "rake spec" startup? i.e. the below steps & why things occur when they do Macintosh-2:myequity greg$ rake spec --trace (in /Users/greg/source/myequity) ** Invoke spec (first_time) ** Invoke db:test:prepare (first_time) ** Invoke db:abort_if_pending_migrations (first_time) ** Invoke environment (first_time) ** Execute environment ** Execute

Hi. I have 2 tables, with same dimensions (8000 x 5). Something like: tab1: V1 V2 V3 V4 V5 14.23 1.71 2.43 15.6 127 13.20 1.78 2.14 11.2 100 13.16 2.36 2.67 18.6 101 14.37 1.95 2.50 16.8 113 13.24 2.59 2.87 21.0 118 tab2: V1 V2 V3 V4 V5 1.23 1.1 2.3 1.6 17 1.20 1.8 2.4 1.2 10 1.16 2.6 2.7 1.6 11 1.37 1.5 2.0 1.8 13 1.24 2.9 2.7 2.0 18 I need generate a table of averages, the

Hi I made a CD-backup with cdparanoia | oggenc and I tried to use different values of -q listening to the effect by cdparanoia | oggenc -o - | mplayer -. The best quality was 8 -- why? Oggenc version was the precompiled 1.0 from Mandrake 9. --- >8 ---- List archives: http://www.xiph.org/archives/ Ogg project homepage: http://www.xiph.org/ogg/ To unsubscribe from this list, send a message to

Hi, I'm using Sweave to prepare a descriptive report. Are at least 20 tables built with xtable command of kind: <<echo=F, results=hide>>= q5 = factor(Q5, label=c("N?o", "Sim")) (q5.tab = cbind(table(q5))) @ <<echo=F, results=tex>>= xtable(q5.tab, align="l|c", caption.placement = "top", table.placement='H') @ I'm

Dear all, I like the way the Rcmdr package computes reliability. E.g reliability(cov(d[,c("q1", "q2", "q3", "q4", "q5", "q6")], use="complete.obs")) will not only give me the alpha score, but also for each variable, alpha.score if deleted. However - when writing scripts it's very tiresome to load the whole Rcmdr GUI just

Hi, I have this data set: obitoss = c( 5.8,17.4,5.9,17.6,5.8,17.5,4.7,15.8, 3.8,13.4,3.8,13.5,3.7,13.4,3.4,13.6, 4.4,17.3,4.3,17.4,4.2,17.5,4.3,17.0, 4.4,13.6,5.1,14.6,5.7,13.5,3.6,13.3, 6.5,19.6,6.4,19.4,6.3,19.5,6.0,19.7) (dados = data.frame( regiao = factor(rep(c('Norte', 'Nordeste', 'Sudeste', 'Sul', 'Centro-Oeste'), each=8)), ano =

From: Jyri Sarha <jsarha at ti.com> Also adds inline asm implementations of WORD2INT(x) macro for fixed and floating point. --- libspeex/resample_neon.h | 101 ++++++++++++++++++++++++++++++++++++++++++++++ 1 files changed, 101 insertions(+), 0 deletions(-) diff --git a/libspeex/resample_neon.h b/libspeex/resample_neon.h index ba93e41..e7e981e 100644 --- a/libspeex/resample_neon.h +++