Data Structure - 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

Learn about R Workspace, Objects, and .RData File

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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

Practicing R for Statistical Computing: rfaqs.com

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read.table Function in R (2016): A Comprehensive Guide

September 11, 2024June 6, 2016 by Muhammad Imdad Ullah

The post is about how to import data using read.table() function in R. You will also learn what is a file path and how to get and set the working directory in R language. The read.table() function in R is a powerful tool for importing tabular data, typically from text files, into the R environment. The read.table function converts the tabular data from a flat-file format into a more usable data structure called the data frame.

Question: How can I check my Working Directory so that I would be able to import my data in R? Answer: To find the working directory, the command getwd() can be used, that is

getwd()

import data using read.table function in R

Question: How can I change the working directory to my path?
Answer: Use function setwd(), that is

setwd("d:/mydata")
setwd("C:/Users/XYZ/Documents")

Import Data using read.table Function in R

Question: I have a data set stored in text format (ASCII) that contains rectangular data. How can I read this data in tabular form? I have already set my working directory.
Answer: As data is already in a directory set as the working directory, use the following command to import the data using read.table() command.

mydata <- read.table("data.dat")
mydata <- read.table("data.txt")

The mydata is a named object that will have data from the file “data.dat” or “data.txt” in data frame format. Each variable in the data file will be named by default V1, V2,…

Question: How this stored data can be accessed?
Answer: To access the stored data, write the data frame object name (“mydata”) with the $ sign and name of the variable. That is,

mydata$V1
mydata$V2
mydata["V1"]
mydata[ , 1]

Question: My data file has variable names in the first row of the data file. In the previous question, the variable names were V1, V2, V3, … How can I get the actual names of the variables stored in the first row of the data.dat file?
Answer: Instead of reading a data file with default values of arguments, use

read.table("data.dat", header = TRUE)

Question: I want to read a data file that is not stored in the working directory.
Answer: To access the data file that is not stored in the working directory, provide a complete path of the file, such as.

read.table("d:/data.dat" , header = TRUE)
read.table("d:/Rdata/data.txt" , header = TRUE)

Note that read.table() is used to read the data from external files that have normally a special form:

The first line of the file should have a name for each variable in the data frame. However, if the first row does not contain the name of a variable then the header argument should not be set to FALSE.
Each additional line of the file has its first item a row label and the values for each variable.

In R it is strongly suggested that variables need to be held in the data frame. For this purpose read.table() function in R can be used. For further details about read.table() function use,

help(read.table)

Important Arguments of read.table Function:

file: (required argument) it is used to specify the path to the file one wants to read.
header: A logical value (TRUE or FALSE) indicating whether the first line of the file contains column names. The default value is set to FALSE.
sep: The separator that segregates values between columns. The default is set to white space. One can specify other delimiters like commas (“,”) or tabs (“\t”).
as.is: A vector of logical values or column indices specifying which columns to read as characters and prevent conversion to numeric or factors.
colClasses: A vector specifying the data type for each column. Useful for ensuring specific data formats during import. This can be useful to ensure the data is read in the correct format (e.g., numeric, character).