Muhammad Imdad Ullah, Author at R Language Frequently Asked Questions

Vectors in R Language

July 23, 2024December 3, 2017 by Muhammad Imdad Ullah

Introduction to Vectors in R Language

Vectors in the R Language are the simplest data structures. A vector in R is also an object containing elements of the same data type. To create a vector (say ‘x’) of the same type (that is data type is double) of elements consisting of five elements one can use the c() function. For example,

Creating Vectors in R using the c() Function

x <- c(10, 7, 3, 2, 1)

The c() function can be used to combine a different number of vectors into a single vector. A single number is regarded as a vector of length one. For example, a vector (say ‘y’) is created by combining the existing vector(s) with a single number.

Appending a Number to an Existing Vector(s)

One can append a number to an existing vector or even append a vector with another vector. For example, vectors in R Language can be appended like:

y <- c(x, .55)
z <- c(x, y)

Extracting Vector Element(s)

The simplest example to select a particular element of a vector can be performed by using a subscription mechanism. That is, use the name of the vector with a square ([ ]) bracket with a number in it indicating the position of a vector element. For example,

# shows first element of vector x
> x[1:2]   # shows first two elements of vector 'x'
> x[3:5]   # shows elements of vector 'x' from index 3 to 5

Note that a positive number is used as a subscript index in a square bracket. A positive subscript indicates the index (position) of a number to extract from the vector. A negative number as the index can also be used, which is used to select all the elements except the number(s) that are used in the square bracket ([ ]).

An example of a negative index is;

x[-1]       # shows all elements of vector 'x' except first element
x[-(1:2)]   # shows elements of vector 'x' except first two elements

Also note that if the number exceeds the number of elements in a vector, then it will result in NA (not available). For example,

x[7] 
x[1:10]

Updating Vector Elements

One or more elements of a vector can be changed by the subsetting mechanism. For example, to change the 4th element of a vector, one can proceed as follows;

x[4] <- 15     # 4th position of vector 'x' is updated to 15
x[1:3] <- 4    # first three numbers are updated to 4
x[1:3] <- c(1,2,3) # first three numbers are updated to 1, 2, and 3

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Reading and Writing Data in R: A Quick Guide

August 13, 2024September 30, 2017 by Muhammad Imdad Ullah

For dealing with data, one may need “reading and writing data in R”. Therefore, it is important to discuss reading and writing data in R. It is also important to learn about reading and writing data files in the R environment.

Reading and Writing Data in R Language

Reading Data in R

read.table(), and read.csv(), for reading tabular data
readLines() for reading lines of a text file
source() for reading in R code files (inverse of dump)
dget() for reading in R code files (inverse of dput)
load() for reading in saved workspaces.

Writing Data to File in R

Following are a few functions for writing (exporting) data to files in R Language.

write.table() in R, and write.csv() export data to a wider range of file formats including CSV and tab-delimited.
writeLines() write text lines to a text-mode connection.
dump() takes a vector of names of R objects and produces text representations of the objects on a file (or connection). A dump file can usually be sourced into another R session.
dput() writes an ASCII text representation of an R object to a file (or connection) or uses one to recreate the object.
save() writes an external representation of R objects to the specified file.

Reading Data Files with read.table()

The read.table() function in R is one of the most commonly used functions for reading data into R. It has a few important arguments.

file, the name of a file, or a connection
header, logical indicating if the file has a header line
sep, a string indicating how the columns are separated
colClasses, a character vector indicating the class of each column in the data set
nrows, the number of rows in the dataset
comment.char, a character string indicating the comment character
skip, the number of lines to skip from the beginning
stringsAsFactors, should character variables be coded as factors?

read.table() and read.csv() Examples

data <- read.table("foo.txt")
data <- read.table("D:\\datafiles\\mydata.txt")
data <- read.csv("D:\\datafiles\\mydata.csv")

R will automatically skip lines that begin with a symbol # and figure out how many rows there are (and how much memory needs to be allocated). R also figures out what type of variable is in each table column.

Writing Data Files with write.table() in R

A few important arguments are usually used in function write.table() in R.

x, the object to be written, typically a data frame
file, the name of the file that the data are to be written to
sep, the field separator string
col.names, a logical value indicating whether the column names of x are to be written along with x, or a character vector of column names to be written
row.names, a logical value indicating whether the row names of x are to be written along with x, or a character vector of row names to be written
na, the string to use for missing values in the data

write.table() and write.csv() Examples

The following are few examples about saving data in CSV or TXT files.

x <- data.frame(a = 5, b = 10, c = pi)

write.table(x, file = "data.csv", sep = ",")
write.table(x, "c:\\mydata.txt", sep = "\t")
write.csv(x, file = "data.csv")

Importing and exporting data in R

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List in R Language: A Comprehensive Guide

September 11, 2024June 16, 2017 by Muhammad Imdad Ullah

In R language, a list is an object that consists of an ordered collection of objects known as its components. A list in R Language is structured data that can have any number of modes (types) or other structured data. That is, one can put any kind of object (like vector, data frame, character object, matrix, and/ or array) into one list object. An example of a list is

x <- list(c(1,2,3,5), c("a", "b", "c", "d"), c(T, T, F, T, F), matrix(1:9, nr = 3) )

that contains 4 components, three of them are vectors (numeric, string, and logical) and one of them is a matrix.

Converting Objects to List in R Language

An object can also be converted to a list by using the as.list( ) function. For vector, the disadvantage is that each element of the vector becomes a component of that list. For example,

as.list (1: 10)

Extract components from a list

The operator [[ ]] (double square bracket) is used to extract the components of a list. To extract the second component of the list, one can write at R prompt,

list[[2]]

Using the [ ] operator returns a list rather than the structured data (the component of the list). The component of the list need not be of the same mode. The components are always numbered. If x1 is the name of a list with four components, then individual components may be referred to as x1[[1]], x1[[2]], x1[[3]], and x1[[4]].

If components of a list are defined then these components can be extracted by using the names of components. For example, a list with named components is

x1 <- list(a = c(1,2,3,5), b = c("a", "b", "c", "d"), c = c(T, T, F, T, F), 
d = matrix(1:9, nr = 3) )

To extract the component a, one can write

x1$a
x1["a"]
x1[["a"]]

To extract more than one component, one can write

x[c(1,2)]     #extract component one and two
x[-1]         #extract all component except 1st
x[[c(2,2)]]   #extract 2nd element of component two
x[[c(2:4)]]   #extract all elements of component 2 to 4

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