similar to: R-help Digest, Vol 124, Issue 12

Hi Keith,, ggpairs(dat1, upper = list(continuous = "density", combo = "box")) appears to be what you want. John Kane Kingston ON Canada > -----Original Message----- > From: kw1958 at gmail.com > Sent: Tue, 11 Jun 2013 09:25:48 -0400 > To: r-help at r-project.org > Subject: Re: [R] R-help Digest, Vol 124, Issue 12 > > Folks, > > Sorry for

I have the following data: v <- rnorm(13) w <- rnorm(13) x <- rnorm(13) y <- rnorm(13) z <- rnorm(13) Using GGPLOT facet, what I want to do is to create a 5*5 matrix, where each cells plot the correlation between each pair of the above data. E.g. v-v,v-w; v-x,...,z-z What's the way to do it? Attached is the image. GV.

Hi John (and other authors of ChoiceModelR package), I am experiencing a weird thing when using the function choicemodelr under R3.0.1. Before I updated to R3.0, I had used choicemodelr unde R2.15. It was always as fast or faster than exactly the same task in Sawtooth software. Now, I've tried to run it under R3.0.1. It seems to be doing the job. But something is slowing it down dramatically.

Thanks Marc. It never occurred to me that I would need a ""stringsAsFactors" expression in a data.frame.? I could have sworn I never did before when mocking up some data but clearly I was wrong or there has been a change in R v. 3.4.1 which seems unlikely. On Friday, July 7, 2017, 10:37:29 AM EDT, Marc Schwartz <marc_schwartz at me.com> wrote: > On Jul 7, 2017, at 6:03

Hello R community, I am computing weighted average statistic by using ddply function: My data set is: N1 T1 S1 I1 C1 FY-4 ROE11 EPS11 MKT11 N1 T1 S1 I1 C1 FY-3 ROE12 EPS12 MKT12 N1 T1 S1 I1 C1 FY-2 ROE13 EPS13 MKT13 N1 T1 S1 I1 C1 FY-1 ROE14 EPS14 MKT14 N1 T1 S1 I1 C1 FY0 ROE15 EPS15 MKT15 N1 T1 S1 I1 C1 FY1 ROE16 EPS16 MKT16 N1 T1 S1 I1 C1 FY2 ROE17

my data are matrix with 3 numeric columns. would like to have pairs plot with scatterplots in the upper with hist at the diag and with correlation at the lower. actually default pairs does almost what I want but looks semi awesome. Especially, i didn't find out how to remove the axes from the lower part where I do only want to display the numeric values correlations there and somehow axes

> On Jul 7, 2017, at 6:03 AM, John Kane via R-help <r-help at r-project.org> wrote: > > This is not serious problem but I just wonder if someone can explain what is happening. > The same command within a dataframe is giving me a factor and as a plain vector is giving me a character. It's probably something simple that I have read and forgotten but I thought I'd ask.

Hi, I was trying as well as looking for an answer without success (a bit strange since it should be an easy problem) and therefore I will appreciate you help: My simple script is: # Loadings data of 5 columns and 100 rows of data data1<-read.csv("C:/?/MyPCA.csv") pairs(data1[,1:4]) pca1 <- princomp(data1[,1:4], score=TRUE, cor=TRUE) biplot(pca1) The biplot present the data

> On Jul 7, 2017, at 7:03 PM, John Kane <jrkrideau at yahoo.ca> wrote: > > Thanks Marc. > It never occurred to me that I would need a ""stringsAsFactors" expression in a data.frame. I could have sworn I never did before when mocking up some data but clearly I was wrong or there has been a change in R v. 3.4.1 which seems unlikely. Welcome John. Going back to

Hello, I have a data set that looks like this: name G-ID test_id g-id g 1 00077464 C_068131 C_068131 OC_068131 - 2 00051728 C_044461 C_044461 OC_044461 - 3 00058738 C_050343 C_050343 OC_050343 - 4 00059239 C_050649 C_050649 OC_050649 - 5 00001761 C_000909 C_000909 OC_000909 - 6 00005119 C_002752 C_002752 OC_002752 - locs

Further to my email below, I have just realised that I forgot to include the specification of L and R. Hence, the code needs to include the following additional lines at the start;- L<-7.5e6 R<-2.5e6 Apologies for any confusion caused! Best regards, Tony > On 12 Jul 2017, at 10:03 AM, HUL-Anthony Egerton <aegerton at huntingtonunderwriting.com> wrote: > > I am trying

Hi all, I would love to plot my data with R. I have abundance and frequency of fungal taxonomic data that should be plotted in the same graph. In Microsoft Excel is that possible but the graphic result is, as always, very poor. Is there a function that may let me plot these data in R? I have a matrix made of two columns, on is the relative abundance and the other is the relative frequency for

I have x, y, z data. The x, y fields dont change but Z does. How do I add a very small number onto the end of each x, y data point. For example: Original (X) Original (Y) Original (Z) 15 20 30 15 20 40 New (X) New (Y)

Tony, I?m not sure what exactly you?re trying to do, but you're not really taking advantage of vectorization in your R code. I've tried to clean it up a little. The clamped lognormal is almost always 0 or L? That seems a little odd. You seem to be using the inverse cdf method of drawing samples. That's not necessary in R for standard probability distributions. You may want to do a

I've been trying to reshape this database but haven't succeed at it. I tried using loops but can't get it right. I just want to reshape my database from this matrix, to the one below, with only one column of data. Year Route Point Sp1 Sp2 Sp3 2004 123 123-1 0 1 0 2004 123 123-2 0 1 1 2004 123 123-10 1 1 0 Year Route Point 2004 123 123-1 Sp1 0 2004 123 123-2 Sp1 0 2004 123

This is not? serious problem but I just wonder if someone can explain what is happening. The same command within a dataframe is giving me a factor and as a plain vector is giving me a character.? It's probably something simple that I have read and forgotten but I thought I'd ask. Thanks #================================================ dat1 <- data.frame(aa = letters[1:10]) str(dat1)

Hi R user,I am struggling to figure out on how I can calculate the average from the two tables in R. Any one can help me? really your help would be grateful- I am spending so much time to figure it out. It should not be so hard, I think. I have very big data but I have created a hypothetical data for simplification. for example I have : table 1 table 1: species occurance data

Hi All, I have a data set wit three size classes (pico, nano and micro) and 12 different sites (Seamounts). I want to produce a table with the mean and standard deviation values for each site. Seamount Pico Nano Micro Total_Ch 1 Off_Mount 1 0.0691 0.24200 0.00100 0.31210 2 Off_Mount 1 0.0938 0.00521 0.02060 0.11961 3 Off_Mount 1 0.1130 0.20000 0.06620 0.37920 4 Off_Mount 1

You rang sir? library(tidyverse) xx = 1:10 yr1 = yr2 = yr3 = rnorm(10) dat1 <- data.frame(xx , yr1, yr2, y3) dat1 %>% select(!starts_with("yr")) or for something a bit more exotic as I have been trying to learn a bit about the "data.table package library(data.table) xx = 1:10 yr1 = yr2 = yr3 = rnorm(10) dat2 <- data.table(xx , yr1, yr2, yr3) dat2[, !names(dat2)

HI, I am not sure about what you expect as output. dat1<- read.table(text=" Offense Play Y??????? A N??????? B Y??????? A Y??????? C N??????? B N??????? C ",sep="",header=TRUE,stringsAsFactors=FALSE) ?with(dat1,tapply(Play,list(Offense),table)) #$N # #B C #2 1 # #$Y # #A C #2 1 #or with(dat1,tapply(factor(Play),list(Offense),table)) #$N # #A B C #0 2 1 # #$Y # #A B