Joseph Herlant
version 1.0.0, 2013-11-03 : Initial version

1. Variables

1.1. Basics

Variables are assigned using the <- operator.

x <- 2
y <- "Bla bla bla"

Booleans are: TRUE and FALSE which can be shorten as T and F respectively.

NA is the equivalent of a null or nil in other languages. It indicates that no data is available. Note that a sum containing at least a NA value will render NA. To get rid of these values when calculating a sum, use the na.rm = TRUE option available in a lot of R functions.

1.2. Vectors

Create vectors using the Combine`function on a coma-separated list of elements of the SAME TYPE. This function has a shortcut: `c. Example:

x <- c(1, 2, 3)
y <- c('a', 'b', 'c')

To create a vector which is a sequence, use either the start:end notation or the seq function. The advantage of using seq is that you can specify a 3rd parameter which is the step increment to catever value you want.

You can see that the simple vector is just like what’s called an array in many programming languages.

The above example output exactly the same:

s1 <- 2:11
s2 <- seq(2,11)

To access something in a vector, use its index just like an array in other programming languages. In the above example, we are extracting c, replacing b by o and adding a new strings as 4th value. Be careful, vector’s index start with 1!

x <- c('a', 'b', 'c')
x[2] <- 'o'
x[4] <- 'is good!'

You also can extract a vector from the vector using a sequence as parameter. The following will extract a vector of b c and d, and then extend the vector with f g and h.

x <- c('a', 'b', 'c', 'd', 'e')
x[6:8] <- 'f':'h'

A vector can have a named index just like an hashtable in other programming languages. For this, assign the vector as usual and the assign its names using the names function.

hash_equivalent <- c("Val1", "Val2", "Val3")
names(hash_equivalent) <- c("first val", "2nd val", "3rd val")
hash_equivalent{"first val")

1.3. Matrix

To create a zero-filled matrix, use the matrix function on the 0 number like this (3 is the number of lines, 4 the number of columns):

x <- matrix(0, 3, 4)

To create a matrix from a vector, use the same as above:

x <- 1:12
matrix(x, 3, 4)

which will render:

     [,1] [,2] [,3] [,4]
[1,]    1    4    7   10
[2,]    2    5    8   11
[3,]    3    6    9   12

To assign dimensions to a vector, transforming it to a matrix. The example bellow will render exactly the same as the previous example but the vector himself is converted in-place to a matrix (in the previous example, it is not the case).

x <- 1:12
dim(x) <- c(3,4)

Matrix works the same as a multidimensionnal array that you can find in other programming languages. The example below shows how to get the 3rd row, 4th column element of a matrix:


To get an antire row, omit the 2nd index. To get an entire column, omit the 1st index. To get multiple lines/rows, put a sequence in the corresponding index place.

my_matrix|3, ]
my_matrix|, 4]
my_matrix|3:5, ]
my_matrix|, 2:4]

Assignment of a single element works the same way:

my_matrix|3,4] <- 11

1.4. Data frames

Data frames are just like a matrix with title colums or just like an excel stylesheet.

Let’s say you have 3 vectors: country, population, age. You can do a data frame like this:

countries <- c("France", "Germany", "Italy")
population <- c(65806000, 80523700, 59772978)
age <- c(40, 45, 43)
my_frame <- data.frame(countries, population, age)

A print(my_frame) would, in this case, give:

    countries population  age
1      France   65806000   40
2     Germany   80523700   45
3       Italy   59772978   43

You can get a column on a data frame by giving its index between double brackets or giving its name between double brackets or even passing it after a dollar. All the lines above give the same result in our example:


To merge data frames, you can use the merge function.

2. Operations

Classic math operations can be done on numbers like:

  • + for addition

  • - for substraction

  • / for division

  • * for multiplication

Doing such operation on a vector will do the operation on all the elements of the vector.

Comparing 2 strings / numbers or whatever you want using ==. You can also compare vectors using the == operator which will return a vector of the result of the comparision for each elements.
All of this is also true for >, <, >=, <=.

The mean function will display the average value of a vector.

The median function will display the median value. (Value of the vector that is at the middle of the sorted list or the average of both middle values for even numbered vectors).

The standard deviation of a vector is given by the sd function. To summarize:

+ sd = sqrt(average(for each vector’s value ( sqrt(mean of vector - value))))

R can try to find correlation between vectors using the cor.test(vector1, vector2) function.

It can also try and calculate the linear model using the lm(vector1 ~ vector2) function.

3. Working with files

To list local files, use:


Run a ".R" file from the interpreter using:


To load a csv file, use the read.csv function. This will return a Data Frame structure.


A tab-separated file can be loaded using the read.table function, specifying the separator and wether or not the file contains a header. If header is set to false, a new header will be created. It will return a data frame structure.

read.table("a_tsv_file.txt", sep="\t", header=TRUE)

4. Getting help

To get some help on a function, use the following command:


If you only want examples of it, use:


5. Drawing charts

Create a bar chart with a vector using the barplot function. You can set the name on the vector to have values on y-axis as shown in the above example.

my_vect <- c(3, 9, 2)
names(my_vect) <- c("France", "US", "UK")

Which would give a graph similar to this (this one is actually generated by google graph for this website needs):

Create a plot chart using the plot function. You must provide 2 vectors for this: one for the x-axis values and one for the y-axis values.

x <- seq(20, 100, 0.9)
y <- sqrt(x)
plot(x, y)

Add a line on a graph using abline(h = value_of_the_line)̀.

Draw a contour map of a matrix by usong the contour function.

m <- matrix(1, 10, 10)
m[2, 3] <- 0

Draw a 3D perspective with the persp function, setting the height with the expand parameter.

m <- matrix(1, 10, 10)
m[2, 3] <- 0
persp(m, expand=0.3)

The image dunction will display a 2D "heat" graph representation of the matrix.

m <- matrix(1, 10, 10)
m[2, 3] <- 0
You can use the "volcano" matrix that contains a sample data set to play with those functions.

6. Resources

R project official site:

Codeschool introduction to the R programming language (it’s free, you really should do that if you’re interested in R):

ggplot2 is a graphics package to install new packages from the Comprehensive R Archive Network (CRAN). You can get some help with the help(package = "ggplot2") command… Give it a try!