Edited for clarity (#23034)
Minor changes to wording to stay consistent with professional standards.
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DataCowboy
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Christopher McCormack
Christopher McCormack
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abeb1af705
@ -1,103 +1,103 @@
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---
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title: Data Types in R
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---
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## Scalars
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Scalar refers to an atomic quantity that can hold only one value at a time. Scalars are the most basic data types. Some common types of scalars :
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1. Number
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```r
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> x <- 5
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> y <- 5.5
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> class(x)
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[1] "numeric"
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> class(y)
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[1] "numeric"
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> class(x+y)
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[1] "numeric"
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```
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2. Logical value
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```r
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> m <- x > y # Used to check, Is x larger than y?
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> n <- x < y # Used to check, Is x smaller than y?
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> m
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[1] FALSE
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> n
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[1] TRUE
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> class(m)
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[1] "logical"
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> class(NA) # NA is another logical value: 'Not Available'/Missing Values
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[1] "logical"
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```
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3. Character(string)
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```r
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> a <- "1"; b <- "2.5"
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> a;b
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[1] "1"
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[1] "2.5"
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> a+b
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Error in a + b : non-numeric argument to binary operator
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> class(a)
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[1] "character"
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> class(as.numeric(a))
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[1] "numeric"
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> class(as.character(x))
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[1] "character"
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```
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## Vector
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It is a sequence of data elements of the same basic type. For example:
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> o <- c(1,2,5.3,6,-2,4) # Numeric vector
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> p <- c("one","two","three","four","five","six") # Character vector
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> q <- c(TRUE,TRUE,FALSE,TRUE,FALSE,TRUE) # Logical vector
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> o;p;q
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[1] 1.0 2.0 5.3 6.0 -2.0 4.0
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[1] "one" "two" "three" "four" "five" "six"
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[1] TRUE TRUE FALSE TRUE FALSE
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## Matrix
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It is a two-dimensional rectangular data set. The components in a matrix also must be of the same basic type like vector. For example:
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> m = matrix( c('a','a','b','c','b','a'), nrow = 2, ncol = 3, byrow = TRUE)
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> m
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>[,1] [,2] [,3]
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[1,] "a" "a" "b"
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[2,] "c" "b" "a"
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## Data Frame
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It is more general than a matrix, in that different columns can have different basic data types. For example:
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> d <- c(1,2,3,4)
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> e <- c("red", "white", "red", NA)
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> f <- c(TRUE,TRUE,TRUE,FALSE)
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> mydata <- data.frame(d,e,f)
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> names(mydata) <- c("ID","Color","Passed")
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> mydata
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ID Color Passed
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1 1 red TRUE
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2 2 white TRUE
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3 3 red TRUE
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4 4 <NA> FALSE
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## Lists
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It is an R-object which can contain many different types of elements inside it like vectors, functions and even another list inside it. For example:
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> list1 <- list(c(2,5,3),21.3,sin)
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> list1
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[[1]]
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[1] 2 5 3
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[[2]]
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[1] 21.3
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[[3]]
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function (x) .Primitive("sin")
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## Reference:
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* [Official Docs](https://cran.r-project.org/manuals.html)
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* [Data Types in R by r-bloggers](https://www.r-bloggers.com/classes-and-objects-in-r/)
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---
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title: Data Types in R
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---
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## Scalars
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Scalar refers to an atomic quantity that can hold only one value at a time. Scalars are the most basic data types. Some common types of scalars :
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1. Number
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```r
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> x <- 5
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> y <- 5.5
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> class(x)
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[1] "numeric"
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> class(y)
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[1] "numeric"
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> class(x+y)
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[1] "numeric"
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```
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2. Logical value
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```r
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> m <- x > y # Used to check, Is x larger than y?
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> n <- x < y # Used to check, Is x smaller than y?
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> m
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[1] FALSE
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> n
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[1] TRUE
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> class(m)
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[1] "logical"
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> class(NA) # NA is another logical value: 'Not Available'/Missing Values
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[1] "logical"
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```
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3. Character(string)
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```r
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> a <- "1"; b <- "2.5"
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> a;b
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[1] "1"
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[1] "2.5"
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> a+b
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Error in a + b : non-numeric argument to binary operator
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> class(a)
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[1] "character"
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> class(as.numeric(a))
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[1] "numeric"
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> class(as.character(x))
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[1] "character"
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```
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## Vector
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Vectors are sequences of data elements of the same basic type. For example:
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> o <- c(1,2,5.3,6,-2,4) # Numeric vector
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> p <- c("one","two","three","four","five","six") # Character vector
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> q <- c(TRUE,TRUE,FALSE,TRUE,FALSE,TRUE) # Logical vector
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> o;p;q
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[1] 1.0 2.0 5.3 6.0 -2.0 4.0
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[1] "one" "two" "three" "four" "five" "six"
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[1] TRUE TRUE FALSE TRUE FALSE
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## Matrix
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A matrix is a two-dimensional rectangular data set. The components in a matrix must be of the same basic type. For example:
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> m = matrix( c('a','a','b','c','b','a'), nrow = 2, ncol = 3, byrow = TRUE)
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> m
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>[,1] [,2] [,3]
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[1,] "a" "a" "b"
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[2,] "c" "b" "a"
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## Data Frame
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A data frame is more general than a matrix, in that different columns can have different basic data types. For example:
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> d <- c(1,2,3,4)
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> e <- c("red", "white", "red", NA)
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> f <- c(TRUE,TRUE,TRUE,FALSE)
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> mydata <- data.frame(d,e,f)
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> names(mydata) <- c("ID","Color","Passed")
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> mydata
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ID Color Passed
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1 1 red TRUE
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2 2 white TRUE
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3 3 red TRUE
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4 4 <NA> FALSE
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## Lists
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Lists are R-objects which can contain many different types of elements inside them like vectors, functions and even another list. For example:
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> list1 <- list(c(2,5,3),21.3,sin)
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> list1
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[[1]]
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[1] 2 5 3
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[[2]]
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[1] 21.3
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[[3]]
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function (x) .Primitive("sin")
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## Reference:
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* [Official Docs](https://cran.r-project.org/manuals.html)
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* [Data Types in R by r-bloggers](https://www.r-bloggers.com/classes-and-objects-in-r/)
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