na

I am making a lattice levelplot from x and y factors that range from [0,1]: x y level 1 m3134 m3134 1.0000000 2 m3134 m416B 0.4189057 3 m416B m3134 0.2696508 4 m3134 mA20 0.3322170 5 mA20 m3134 0.2454191 6 m3134 mB 0.3176792 ... Here is the R script that I use to make the figure from this data: #!/foo/bar/bin/Rscript --vanilla args <- commandArgs(TRUE) mtxFn <- args[1] pdfFn <- args[2] mtx <- read.table(mtxFn, col.names=c("x", "y", "level")) mtx$level[(mtx$level == 1)] <- NA library(lattice) trellis.device(dev=pdf, file=pdfFn) colors <- colorRampPalette(c('red', 'white'))(256) fig <- levelplot

I want to represent the structure of a data frame (or matrix, or data.table whatever) on a single plot with color-coding. I guess that could be very useful for many people handling various types of data, to visualize it in a single glance. Perhaps someone have already developed a package to do it, but I couldn't find one (just this ). So here is a rough mockup of my "vision", kind of a heatmap, showing in color codes: the NA locations, the class of variables (factors (how many levels?), numeric (with color gradient, zeros, outliers...), strings) dimensions etc..... So far I have just written a

Does anyone know how gbm in R handles missing values? I can't seem to find any explanation using google. To explain what gbm does with missing predictors, let's first visualize a single tree of a gbm object. Suppose you have a gbm object mygbm . Using pretty.gbm.tree(mygbm, i.tree=1) you can visualize the first tree on mygbm, e.g.: SplitVar SplitCodePred LeftNode RightNode MissingNode ErrorReduction Weight Prediction 0 46 1.629728e+01 1 5 9 26.462908 1585 -4.396393e-06 1 45 1.850000e+01 2 3 4 11.363868 939 -4.370936e-04 2 -1 2.602236e-04 -1 -1 -1 0.000000 271 2.602236e-04 3 -1 -7.199873e-04 -1

I am trying to predict fitted values over data containing NA s, and based on a model generated by plm . Here's some sample code: require(plm) test.data <- data.frame(id=c(1,1,2,2,3), time=c(1,2,1,2,1), y=c(1,3,5,10,8), x=c(1, NA, 3,4,5)) model <- plm(y ~ x, data=test.data, index=c("id", "time"), model="pooling", na.action=na.exclude) yhat <- predict(model, test.data, na.action=na.pass) test.data$yhat <- yhat When I run the last line I get an error stating that the replacement has 4 rows while data has 5 rows. I have no idea how to get predict return a vector of length 5... If instead of

Background Before running a stepwise model selection, I need to remove missing values for any of my model terms. With quite a few terms in my model, there are therefore quite a few vectors that I need to look in for NA values (and drop any rows that have NA values in any of those vectors). However, there are also vectors that contain NA values that I do not want to use as terms / criteria for dropping rows. Question How do I drop rows from a dataframe which contain NA values for any of a list of vectors? I'm currently using the clunky method of a long series of !is.na's > my.df[!is.na(my.df

I have a .csv dataset with many missing values, and I'd like R to recognize them all the same way (the "correct" way) when I read the table in. I've been using: import = read.csv("/Users/dataset.csv", header =T, na.strings=c("")) This script fills all the empty cells with something, but it's not consistant. When I look at the data with head(import) , some missing cells are filled with <NA> and some missing cells are filled with NA . I fear that R treats these two ways of identifying missing values differently when start analyzing the dataset, so I'd like to have the import uniformly read in

I am new to R. I want to fill in an empty matrix with the results of my for loop using cbind . My question is, how can I eliminate the NAs in the first column of my matrix. I include my code below: output<-matrix(,15,) ##generate an empty matrix with 15 rows, the first column already filled with NAs, is there any way to leave the first column empty? for(`enter code here`){ normF<-`enter code here` output<-cbind(output,normF) } The output is the matrix I expected. The only issue is that its first column is filled with NAs. How can I delete those NAs? The default for matrix is to have 1 column.