Difference between revisions of "R Notes"

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=== Loading a plain CSV file into a vector ===
 
=== Loading a plain CSV file into a vector ===
 
   myvector = read.csv(file="path_to_csv_file", header=FALSE)
 
   myvector = read.csv(file="path_to_csv_file", header=FALSE)
* You may then access each of the individual components using myvector[,1], myvector[,2], ... myvector[,n]
+
* You may then access each of the individual records using myvector[row, column]
 +
** Access entire columns using myvector[,1], myvector[,2], ... myvector[,n]
 +
** Access entire rows using myvector[1,], myvector[2,], ... myvector[n,]
  
=== Scatterplot two components of a vector ===
+
=== Scatterplot two columns of a vector ===
In this example, myvector has 4 components and we want to plot the 3rd and 4th
+
In this example, myvector has 4 columns and we want to plot the 3rd and 4th
 
   plot(myvector[,3], myvector[,4], main="This is the title of the plot")
 
   plot(myvector[,3], myvector[,4], main="This is the title of the plot")
  
 
=== Plot a simple histogram ===
 
=== Plot a simple histogram ===
 
   hist(myvector[,3])
 
   hist(myvector[,3])
* Also try ''density(myvector[,3])'' for a density-plot
+
* Also try ''plot(density(myvector[,3]))'' for a density-plot
  
 
=== Linear regression ===
 
=== Linear regression ===
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=== For loops ===
 
=== For loops ===
 
   for (i in 1:100) { ''do_something_useful'' }
 
   for (i in 1:100) { ''do_something_useful'' }
 +
 +
== A complete example ==
 +
* Launch R, and then paste this into the shell:
 +
  # Scott's quick R example
 +
  par (mfrow=c(2,2), oma = c(0, 0, 2, 0), mar = c(5.1, 4.1, 2.1, 2.1)); <br />
 +
  a = rnorm(1000)
 +
  b = rnorm(1000)
 +
  c = rlnorm(20000)
 +
  d = rnorm(20000, mean=5, sd=20) <br />
 +
  plot(a, b, main = "A vs B", xlab="x axis", ylab="y axis", pch=20, col="blue")
 +
  plot(c, d, main = "C vs D", xlab="x axis", ylab="y axis", pch=".", col=palette(rainbow(50)))
 +
  hist(a, main = "Histogram of A", col="darkgreen")
 +
  plot(density(b), main = "Density plot of B", col="red") <br />
 +
  mtext("This is an example that combines multiple plots on a single page", line=0.5, outer=TRUE)

Latest revision as of 17:38, 13 June 2008

A few very basic R examples

Loading a plain CSV file into a vector

  myvector = read.csv(file="path_to_csv_file", header=FALSE)
  • You may then access each of the individual records using myvector[row, column]
    • Access entire columns using myvector[,1], myvector[,2], ... myvector[,n]
    • Access entire rows using myvector[1,], myvector[2,], ... myvector[n,]

Scatterplot two columns of a vector

In this example, myvector has 4 columns and we want to plot the 3rd and 4th

  plot(myvector[,3], myvector[,4], main="This is the title of the plot")

Plot a simple histogram

  hist(myvector[,3])
  • Also try plot(density(myvector[,3])) for a density-plot

Linear regression

  mymodel = lm(myvector[,3] ~ myvector[,4])
  summary(mymodel)

Squeeze multiple plots onto a page ( 4x4 in this example )

  par(cfrow = c(4,4))
  # or par(cfcol = c(4,4)) depending on whether you want row or column ordering
  plot(myvector[,3], myvector[,4])
  plot(myvector[,3], myvector[,4])
  plot(myvector[,3], myvector[,4])
  plot(myvector[,3], myvector[,4])

For loops

  for (i in 1:100) { do_something_useful }

A complete example

  • Launch R, and then paste this into the shell:
  # Scott's quick R example
  par (mfrow=c(2,2), oma = c(0, 0, 2, 0), mar = c(5.1, 4.1, 2.1, 2.1)); 
a = rnorm(1000) b = rnorm(1000) c = rlnorm(20000) d = rnorm(20000, mean=5, sd=20)
plot(a, b, main = "A vs B", xlab="x axis", ylab="y axis", pch=20, col="blue") plot(c, d, main = "C vs D", xlab="x axis", ylab="y axis", pch=".", col=palette(rainbow(50))) hist(a, main = "Histogram of A", col="darkgreen") plot(density(b), main = "Density plot of B", col="red")
mtext("This is an example that combines multiple plots on a single page", line=0.5, outer=TRUE)