**cloudnumbers.com » R-project**, and kindly contributed to R-bloggers)

R (www.r-project.org) is a free and strongly functional language and environment for statistical computing. You can explore data sets, make graphical displays of data, run statistical simulations and many more. If you never used R you should give it a try!

**R beginners:**

There are many courses, slides and tutorials available for R beginners. We are not planning to add another one to this list. Here we provide you with an incomplete list of nice R beginners sessions. You can also follow our list of nice R features, start the preinstalled R at cloudnumbers.com, copy and paste the following commands into the cloudnumbers.com’s web console and enjoy the diversity of R.

- The official R introduction: http://cran.r-project.org/doc/manuals/R-intro.html
- An R reference card: http://cran.r-project.org/doc/contrib/refcard.pdf
- List of tutorials and books at Quick-R: http://www.statmethods.net/about/books.html
- A simple user guide for complete beginners: http://bioinformatics.knowledgeblog.org/2011/06/21/using-r-a-guide-for-complete-beginners/
- Munich R courses: http://www.statistik.lmu.de/R/

**Nice R features:
**Here we start a list of nice R features which present the diversity and power of R. Please feel free to add comments with your favorite R code snipset.

**R as a calculator:**

R provides you with all functionality of a powerful pocket calculator. All standard functions (powers, exponential, squareroot, logarithm, etc.) are built-in. Here are some examples:

(17-3) / (3-1) + 1 3*4 - 7 + 1.5 1.8^2 * exp(0.5) - sqrt(2.4)

You can also assign values to variables and use them for later computations:

x <- 1.8^2 y <- exp(0.5) z <- x*y - sqrt(2.4) z

**R for visualization**:

R is an environment for statistical computing and graphics! Draw star plots or segment diagrams of a multivariate data set “mtcars” (default data set in R).

palette(rainbow(12, s = 0.6, v = 0.75)) mtcars stars(mtcars[, 1:7], len = 0.8, key.loc = c(12, 1.5), main = "Motor Trend Cars", draw.segments = TRUE)

Another nice example is the “The Maunga Whau Volcano plot”. A contour plot using heat colors. The dataset volcano is one of the default datasets in R.

volcano x <- 10*(1:nrow(volcano)); x.at <- seq(100, 800, by=100) y <- 10*(1:ncol(volcano)); y.at <- seq(100, 600, by=100) # Using Terrain Colors image(x, y, volcano, col=terrain.colors(100),axes=FALSE) contour(x, y, volcano, levels=seq(90, 200, by=5), add=TRUE, col="brown") axis(1, at=x.at) axis(2, at=y.at) box() title(main="Maunga Whau Volcano", sub = "col=terrain.colors(100)", font.main=4)

More very nice R plots including example code and data are available in the R graph gallery.

**R help system:**

R provides you with a very flexible help system. You can search for help inside all loaded packages using the command help() or use the simple question mark command “?commandName”. Here are some examples:

help(lm) ?lm ?"for" ?"[[" args("lm") ?volcano help.search("regression") RSiteSearch("cloudnumbers.com")

We will come up with the second part of our favorite R features at the end of the week: R programming, libraries and statistical analyses, biological data analyses with Bioconductor and high-performance computing with R.

Please feel free to add comments with your favorite R code snipset.

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