R-Cookbook.com Delicious, statistical-computing recipes

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Our data in multivariate (wide) format:

my_data<- data.frame(
    id=c(1:50),
    depression1=rnorm(50),
    anxiety1=rnorm(50),
    depression2=rnorm(50),
    anxiety2=rnorm(50),
    depression3=rnorm(50),
    anxiety3=rnorm(50)
)
my_data

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This function will extract time labeled variables (or any variables with consistent naming) by name from a data frame in the order in which they appear in the data frame. This is especially useful in cases when one has a longitudinal or time-series data set where each row (subject) has many occasions of measurements for each measure. Code and examples after the jump.

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The function and documentation is listed after the jump.

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Creating a PDF version of your graphs is very easy:

pdfname<-paste("myfilename",".pdf",sep="")
pdf(pdfname, height=6.4,width=6.4)
# Plotting code
dev.off()

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From the r-help mailing list:

x <- rnorm(10)
y <- runif(10)
z <- 1:10

plot(x~z, ylim=range(x, y), type='l')
lines(y, col='red')

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If you're not happy with what R puts on the axes of your plot (tickmarks, labels etc), plot with "axes=F", then add custom axes with the "axis()" function.

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You have a plot, and you want to draw a grid behind it. If you add the grid to the plot, using either

grid()

or

abline()

, the lines will be added on top of your plot, not behind it. I found the solution on the R-help mailing list, here. Redraw the plot after adding the grid, but first set

par(new=T)

so that it will be drawn on top of the old plot on the same device.

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To replace all NA values in an object with zeroes:

x[is.na(x)] <- 0

If you want to do this only for some columns in a matrix or data frame, try this tip, which was posted by John Fox on the R-help mailing list:

cols <- c(1,3)
x[,cols][is.na(x[,cols])] <- 0

If you want to replace the NAs everywhere except in a single column, spare yourself some typing by:

cols <- -3

(then,

x[,cols][is.na(x[,cols])] <- 0

replaces everywhere except in the third column.)

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x is your data frame. x$total is the column you want to remove:

x$total <- NULL

More at the R Wiki