What are the characteristics of data structures in the …
R programming language’s data structures have the following characteristics:
- Vector: The most fundamental data structure in R language, composed of elements of the same type such as numeric, character, or logical values. Vectors have a fixed length and their elements must be of consistent types.
- List: it can contain elements of different types, such as vectors, matrices, data frames, and other data structures. The length of a list is not fixed and elements can be added or removed as needed.
- Matrix: A two-dimensional data structure composed of elements of the same type, with rows and columns. Elements in the matrix must be of the same type and can be accessed using row and column numbers.
- Arrays, similar to matrices but with multiple dimensions, can have any number of dimensions and allow access to elements through indexing.
- A data frame is a data structure similar to a table, consisting of multiple columns, each of which can hold different types of data. The columns in a data frame can have varying lengths, similar to tables in a database.
- Factor: used to represent categorical variables, which can be ordered or unordered. Factors map discrete category values to integers and use labels to represent categories.
- Atomic Vector is a special type of vector where all elements must be of the same type. It can be numeric, character, logical, etc. Compared to regular vectors, atomic vectors have more properties and methods.
These data structures in the R programming language offer a variety of flexible and efficient ways to organize and manipulate data.
