= R Data Types =

R exposes a few '''atomic data types''' and many more '''derived data types'''.

<<TableOfContents>>

----



== Classes ==

Objects in the R language belong to one or more non-exclusive classes. These are inspected using the `class()` function.

{{{
> now <- Sys.time()
> class(now)
[1] "POSIXct" "POSIXt" 
}}}


----



== Modes ==

Incidentally, the atomic data types can be categorized by their '''mode''', which essentially refers to the underlying storage mechanism.

The mode of an object can be inspected using the `mode()` function. Note that the `typeof()` function is nearly equivalent, with one exception noted below.



=== Numeric ===

'''Numeric''' is a mode of data types.

Data types can be explicitly cast into a numeric type using the `as.integer()`, `as.double()`, and `as.numeric()` functions. Similarly, use the `is.integer()`, `is.double()`, and `is.numeric()` functions to test for these specific data types.

{{{
> my.num <- 1.23
}}}

There are principally two subtypes of numerics, and these are what the `typeof()` function will return instead of the mode.
 * '''integer''' data types store an integer value
 * '''double''' data types store a numeric value with decimal places

For a number of reasons, it usually does not matter which subtype is used. Most implementations of algorithms and estimations implicitly use double precision, not arbitrary precision. Furthermore, implicitly casting between numeric data types is generally an acceptable side effect in implementations.



=== Complex ===

The '''complex''' data type stores a complex numeric value.

{{{
> my.com <- 9i + 3
}}}

Complex values are ''not'' numeric in R. Calling `is.numeric()` on a complex value will return `FALSE`.



=== Logical ===

The '''logical''' data type stores a Boolean value. These are represented as the keywords `TRUE` and `FALSE`.

{{{
> my.bool <- TRUE
}}}



=== Character ===

The '''character''' data type stores a string value.

{{{
> my.char <- "R"
}}}

----



== Compositions ==

A '''vector''' is an ordered container whose members are of a uniform data type.

{{{
> my.vector <- c(1, 2, 3)
}}}

An '''array''' is another ordered container whose members are of a uniform data type.

{{{
> my.array <- array(c(1, 2, 3, 4))
}}}

A '''list''' is an ordered container of any data types.

{{{
> my.list <- list("R", 1.23, TRUE)
}}}

A '''matrix''' is a multi-dimensional container whose members are of a uniform data type.

{{{
> my.matrix <- matrix(c(1, 2, 3, 4), nrow=2, ncol=2)
}}}

See also [[R/DataFrames|data frames]] and [[R/Tibble|tibbles]].

----



== Other Common Objects ==



=== Factor ===

A '''factor''' is a data type that represents categorical levels. For one, this is an optimization for storage; the vector of unique levels is stored, then all rows' values are replaced with integers that refer to an index in that vector.

{{{
> my.factor <- as.factor(my.factor)
}}}

to inspect the levels of a factor, try the `levels()` function.

When regressing on a factor, [[Statistics/Parameterization#Reference_Parameterization|dummy coding]] is automatically applied. To force a reference level, try:

{{{
> my.factor <- relevel(my.factor, ref="Label")
}}}



----
CategoryRicottone