Gone Guerrill_ R on Our Data

August 16, 2010
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(This article was first published on The Pith of Performance, and kindly contributed to R-bloggers)

Here's a summary of some things we learnt about applying R to computer performance and capacity planning data in the GDAT Class last week.
  • Neural nets pkg nnet applied to CPU performance data in the Ripley and Venables book (see Section 8.10).
  • How to do stacked plots that Jim calls "spark plots."
  • Jim told us that ggplot has a nice GUI but considerably slower than using the base plot routines.
  • Use of POSIXct to convert timestamps.
  • Handling multi-line headers.
  • Handling multi-word fields in headers.
  • To make getwd() like the UNIX shell command: pwd<-function(){cat(getwd())}.
  • Think of lapply as a vectorized for-loop.
  • Calculating confidence intervals, which David explained earlier in the week, is available as the CI function in gmodels pkg on CRAN.
  • Fourier Transform Your Data. This was done using Mathematica but the same thing can be accomplished with the fftw pkg on CRAN.
  • VAMOOS your data.
If you want to learn things like this, then consider putting this GDAT class on your calendar for next year.

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