To use R most efficiently and effectively, you must understand the data types and data structures of R, because the Machine Learning algorithms such as Support Vector Machine (SVM), decision tree, and even linear regression and logistic regression have optimization components. The use of the correct data types is the key part of the performance of optimization. Also, to perform matrix operations, the user must use matrix data types. Moreover, the user needs to know the use of correct variables into the statistical model, and understanding R data types is the important aspect in this area. Here are the data types that will help you store and manage your data correctly and efficiently:

• Character
• Numeric
• Logical
• Integer
• Complex

The data structure of R is the way to organize the dataset for data storage and analytics purposes. Each of the different data structures can...

In this recipe, you will learn what a vector is in R, and how to create it, access its properties, and perform certain operations.

To follow this recipe, you need the R software installed on your computer. Before going to the next step, you have to understand the definition of a vector in R. In R, a vector is simply a collection of values with the same type; it could be all character, numeric, or logical. For example, it could contain names of places/countries, it could contain the number of hours a person spends on the internet over the last seven days, or it could also contain whether a group of people has a certain disease or not (true/false).

A matrix is a two-dimensional arrangement of vectors of the same type. Like vectors in R, the matrix is restricted to one data type. In this recipe, you will learn how to create a matrix, how to access its elements, and understand a few notes on matrix operations.

To get started with this recipe, you must have R installed on your computer. You also need to understand the structure of a matrix and various operations. There is no library required for this recipe, but if you are interested in advanced matrix algebra, then you might consider the See also section of this recipe. A matrix is considered as a two-dimensional grid where each cell is represented by a row and...

A data frame in R is also a two-dimensional arrangement like a matrix, but it can contain a combination of data types in different columns. One column could be numeric, another column could be character. A data frame can be considered as a natural generalization of a matrix in R. In this recipe, you will learn how to create a data frame and how to access various columns and/or elements of it.

Since you have already learned to create a matrix, it will be relatively simple to understand the data frame. It is good to have an understanding of variables and datasets. Though the structure of a data frame is similar to a matrix, it has more information within it.

An array is a way to organize data of the same type in more than two dimensions. An array could be of any dimension, and the data type must be the same in each of the array elements. A matrix is a special case of an array with only two dimensions. In this recipe, you will learn how to create an array and how to access its elements.

Suppose you are in a situation where you must store a series of matrices into a single R object and then perform analysis based on that; however, in this case, this is the perfect and efficient way to create an array. For example, you are in a situation to store four matrices of 2 x 2 order.

A list is the natural generalization of a data frame in R. A data frame is a rectangular arrangement of rows and columns where each of the columns must be of the same length. A list can contain a variety of heterogeneous objects with various lengths and data types. An array contains only one data type, whereas a list could contain heterogeneous data types of various lengths. In that sense, a list is also a natural generalization of an array. A list is a versatile R object, and it is important to know how it stores elements and how you can access it. In this recipe, you will learn how to create a list and access its elements.

Recall that you...

A matrix is a two-dimensional arrangement of data with rows and columns where each row/column is of the same data type, either all numeric, all character, or all logical. Moreover, the number of elements in each column should be the same, and the number of elements in each row should also be the same.

A data frame is also a two-dimensional arrangement of data with rows and columns, but each column could be of very different types; for example, a data frame may contain both character and numeric columns. However, the number of elements in each column should be the same. Since both data structures share some common properties, they could be converted from one structure to another. In this recipe, you will learn to convert a matrix to a data frame and a data frame to a matrix.