R Vectors

 

R Vectors

In R, the most basic type of data is called a vector. A vector is simply a collection of elements, and even a single number is treated as a vector with one element. Matrices and arrays are also just special kinds of vectors with extra structure, like rows and columns. Vectors can store different kinds of data, but all the elements in a single vector must be of the same type, also called mode. The main types are integer for whole numbers, numeric for decimal numbers, character for text, logical for TRUE or FALSE, and complex for complex numbers. To combine a list of items into a vector, we use the c() function, separating the items with commas. One important point is that R indexing starts at 1, not 0, so the first element of any vector is accessed with [1]. We can check the type of a vector using the mode() function, and the length using the length() function.
Vectors are very important in R because almost everything we work with, including matrices, arrays, and even lists, is built on vectors. They allow us to store data in an organized way, perform calculations on many numbers at once, and apply functions efficiently. Using vectors, we can easily filter data and check conditions without writing long loops. Functions like ifelse( ) help us make decisions for each element in a vector at the same time. Vectors are very flexible. We can combine vectors, check their types, handle missing values using NA or NULL, and extract specific elements or subsets. Matrices are just vectors with extra attributes defining rows and columns. Lists are collections that can store different types of vectors, and data frames are lists of vectors where each column can have a different type. Understanding vectors helps us work with all these structures easily. Because vectors are everywhere in R, they are the foundation of all data analysis. They are the building blocks for tasks ranging from simple calculations to plotting graphs, running statistical models, or working with more advanced R objects.

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