Data Analysis with R Programming: Vectors in R Program

Vectors are one-dimensional arrays of values in R programming. They are used to store and manipulate data, and are a fundamental data structure in R. Vectors can contain elements of different data types, such as numeric, character, or logical.

Data Analysis with R Programming: Vectors in R Program

To create a vector in R, you can use the c() function. For example, to create a numeric vector, you can use the following code:

v <- c(1, 2, 3, 4, 5)

To create a character vector, you can use the following code:

v <- c("a", "b", "c", "d", "e")

To create a logical vector, you can use the following code

v <- c(TRUE, FALSE, TRUE, FALSE, TRUE)

You can also create a vector with mixed data types, such as numeric and character:

v <- c(1, "a", 2, "b", 3, "c")

To access the elements of a vector, you can use indexing. In R, indexing starts at 1. For example, to access the third element of a vector v, you can use the following code:

v[3]

You can also access multiple elements of a vector using indexing. For example, to access the second and fourth elements of a vector v, you can use the following code:

v[c(2, 4)]

You can also use negative indexing to exclude certain elements from a vector. For example, to exclude the first and last elements of a vector v, you can use the following code:

v[-c(1, length(v))]

In addition to indexing, R also provides many functions for manipulating vectors. For example, you can use the length() function to get the length of a vector, the mean() function to calculate the mean value of a numeric vector, and the unique() function to get the unique elements of a vector.

Vectors are an important data structure in R programming, and are used in many data manipulation and statistical analysis tasks. They provide a simple and efficient way to store and manipulate data, and are a building block for more complex data structures such as matrices and data frames.