Heterogeneous Data Structures
R supports two ways of representing heterogeneous data, namely lists and dataframe. Both structures are discussed in detail below:
1) Lists :
- Lists are single-dimensional heterogeneous data types.
- A list can represent more than one data type at a time.
- We can simply use the list() function to create a list.
- Lists are similar to vectors, however, vectors are homogeneous and lists are heterogeneous.
- Another interesting property of lists is that we can store lists inside other lists(like simple recursion). Due to this reason, Lists are also referred to as “Recursive Vectors“.
Example:
R
list_ex = list (Ch= "R language" , numbers = 5:1, fl= FALSE ) print (list_ex) |
Output:
$Ch
[1] “R language”
$numbers
[1] 5 4 3 2 1
$fl
[1] FALSE
Example: Recursive vectors
R
list_ex2<- list ( list (1, "R language" , FALSE ), list ( "Python" ,2, "Language" ), list ( "Hello" , FALSE , "World" )) str (list_ex2) |
Output:
List of 3
$ :List of 3
..$ : num 1
..$ : chr “R language”
..$ : logi FALSE
$ :List of 3
..$ : chr “Python”
..$ : num 2
..$ : chr “Language”
$ :List of 3
..$ : chr “Hello”
..$ : logi FALSE
..$ : chr “World”
2) Data Frames:
- In the R language, a data frame is a two-dimensional heterogeneous table-like structure
- They are simply lists of vectors that have equal lengths.
- Data frames make data analysis easier when they are used systematically,
- In the R language, we use the data.frames() function to create data frames.
- A data frame in R must follow the following rules :
- A data frame must have column names and each column must contain equal amount of items,
- Each row in a data frame must have a unique name,
- Each entry in a column must have same data type,
- Different columns can have same or different data types.
Example:
R
employee_id <- c (1:4) employee_name <- c ( "Abdul" , "Anshul" , "Vishal" , "Riya" ) employee_salary <- c ( "45000" , "90000" , "25000" , "75000" ) employee_designation <- c ( "Software Engineer" , "Senior Manager" , "Intern" , "Manager" ) employee.data <- data.frame (employee_id , employee_name, employee_salary, employee_designation) employee.data |
Output:
Heterogeneous Data in R
Data structures are a logical way or representing as per requirement. They further help depict this logical view physically in computer memory. In the R language, data structures can be classified into two groups, namely homogeneous and heterogeneous.
- Homogeneous Data Structures: This type can only store a single type of data inside them(integer, character, etc.),
- Heterogeneous Data Structures: This type can store more than one type of data at the same time.