similar to: mystery "158"

Your data frame fam contains factors. Turn it into character strings using fam$Family = as.character(fam$Family) and try again. It may be helpful if you read up on R's factors, see ?factor. HTH, Peter On Tue, Nov 21, 2017 at 2:14 PM, Glen Forister <gforister at gmail.com> wrote: > This is a simple problem, but a mystery to me. > I'm trying to grab $Family

Well, ?factor does not say anything about this behaviour (assigning numeric code instead of level of factor). And actually if you do assignment for whole vector the result is different (vector in data frame is changed to factor). > temp2$fff[1]<-vec[1] > head(temp2,2) pokus minuty fff 1 T42 240 3 2 T42 300 <NA> > temp2$fff<-vec > head(temp2,2) pokus

HI all, Is it possible to use one column spread on multiple columns values. example spread( Key_col, value1:value7) spreading Key_col to variable value1, value2, ....... Value7 Please advise, Kind regards Mangalani Peter Makananisa (5786) South African Revenue Service (SARS) - HO +2782 456 4669 / +2712 422 7357 Please Note: This email and its contents are subject to our email legal notice

Hi something like dcast(temp2, minuty~pokus) ? > dput(temp2) structure(list(pokus = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 7L, 7L, 8L, 8L ), .Label = c("T42", "T43", "T44", "T45", "T46", "T47", "T48", "T49"), class = "factor"), minuty = structure(c(2L,

# lda.r > # > # Author: Amsha Nahid, Jairus Bowne, Gerard Murray > # Purpose: Perform Linear Discriminant Analysis (LDA) > # > # Input: Data matrix as specified in Data-matrix-format.pdf > # Output: LDA plot > # > # Notes: Missing values (if any) are replaced by the half of the lowest > # value in the entire data matrix. >

hello, i already include the error in blue color word. i hope it can help you to understand my question. if not burden you, please give me a guide how to correct the error or maybe you can correct the coding cause error. thank you. > # lda.r > # > # Author: Amsha Nahid, Jairus Bowne, Gerard Murray > # Purpose: Perform Linear Discriminant Analysis (LDA) > # > #

Hi there, I am a master student in Denmark, and apply R to analyze the drug data. I use the function 'lda' to obtain a linear discriminant object, and then wish to use 'plot.lda' to do the plot on this object like below. drug.lda <- lda(Inhibition ~ NET_CHARGE + PKA_1 + MW + MLOGP, data = drug.class, method = "moment") plot.lda(drug.lda,

Hi, I have done different discriminant function analysis of multivariat data. With the CV=True option I was not able to perform the predict() call. What do I have to do? Or is there no possibility at all? You also need the predicted values to produce a plot of the analysis, as far as I know. Here my code: pcor.lda2<-lda(pcor~habarea+hcom+isol+flowcov+herbh+inclin+windprot+shrubcov+baregr,

Hi !! I am trying to analyze some of my data using linear discriminant analysis. I worked out the following example code in Venables and Ripley It does not seem to be happy with it. ============================ library(MASS) library(stats) data(iris3) ir<-rbind(iris3[,,1],iris3[,,2],iris3[,,3]) ir.species<-factor(c(rep("s",50),rep("c",50),rep("v",50)))

Hi, I am using the lda function from the MASS library. I would to find the decision boundaries of each class and subsequently plot them. I wonder if anybody can offer any help on this topic? Below I applied the lda function on a small dataset of mine. Any help will be much appreciated. > library(MASS) >

Dear members of the flac-dev list, I'm writing to ask for feedback from the FLAC community regarding the possibility of standardizing the FLAC specification through the Internet Engineering Task Force. I'm working with MediaArea on the PREFORMA project which focuses on building conformance checkers for Matroska and FFV1. Since Matroska and FFV1 are not yet formally standardized, this

I've writen this function (imagenrgb) to display a (m,n,3) array as a RGB image with ngris^3 colors and,optionally, stretching. If option ver=F, it does not display but saves a pseudocolor version of the image as a list (so that subsequent displays are faster). I'd appreciate feedback and improvements and hope that it's useful for others. Example of use: > dim(imatest) [1] 100

Hi, Thanks Sarah. Unfortunately I did not get a step further. My question, perhaps a bit clearer, is how to display the case control status (or any other arbitrary point label) after clustering in a plot: With a bit of pseudo code, where dataset is a data.frame, parameters are those column names where we find numerical values (no NAs) and nclasses is the desired number of classes. fit <-

So, I'm trying to boot using PXE + NFS root filesystem, to boot a kernel that can reimage machines. This has been quite successful for me, until just recently where I ran into a motherboard that had a broadcom ethernet chipset - the broadcom driver is binary only. I can boot a kernel using PXE and load the broadcom driver using a custom initrd, but don't know how to then NFS mount the root

Not to many days ago, somebody posted a "refresh" script that I believe allowed you to refresh samba without dropping currently connected users. If this is correct, could someone repost please? I seem to have misplaced my copy and now need it fairly bad. Thanks, Wade Winright "Build a better mantrap, and the rats will beat a path to your door..." -Neil Fallon

> # >> # Generate the figures (on screen) >> # >> # Image generation - function definition >> pic_onscr<-function(matrix, title, cex_val=1) > + {x11() + par(mgp=c(5,2,0), # axis margins + # (title, > labels, line) + mar=c(7,4,4,2), # plot margins (b,l,t,r) + > las=1) # horizontal labels + plot(matrix, # data to plot + >

Hello. I have a vector and within that vector is one expression. When I display this vector it comes up as expression(NA_character_, NA_character_, "Null Effect", "Pooled effect", NA_character_, NA_character_, NA_character_, NA_character_, NA_character_, paste("Het Contours ", I^2, sep = ""), 0.4, 0.41, 0.42, 0.45, NA_character_) Where the

R Experts, I would like to create a series of variables without having to assign a separate line of code for each new variable. My dataframe (DF) contains two groups of linked variables (ESP1:ESP9) and (ECRL1:ECRL9). Within ESP1:ESP9 are abbreviated species codes (full dataframe contains 26 codes). ECRL1 represents the number of species x in variable ESP1 harvested, and so on through ESP9 and

Hi, Is there a kind of scope mechanism in the instruction lowering pattern language in order to control where instructions are inserted or how they are later reordered during the SelectionDiag linearization? I know the glue chain that stick instructions together. But such mechanism in not provided in instruction lowering pattern. I'm facing many situations where some patterns are lowered into

Hi, I'm using plot.lda (R1.4.0 on linux) and, if dimen > 2, I get the error: Error in text.default(x, y, txt, cex = cex, font = font) : X11 font at size 16 could not be loaded The traceback indicates that the problem comes from pairs(). I've tried several cex and font values, always with the same error. The same command works fine with pdf() If I'm missing fonts, how