What's the difference between integer class and numeric class in R

There are multiple classes that are grouped together as "numeric" classes, the 2 most common of which are double (for double precision floating point numbers) and integer. R will automatically convert between the numeric classes when needed, so for the most part it does not matter to the casual user whether the number 3 is currently stored as an integer or as a double. Most math is done using double precision, so that is often the default storage.

Sometimes you may want to specifically store a vector as integers if you know that they will never be converted to doubles (used as ID values or indexing) since integers require less storage space. But if they are going to be used in any math that will convert them to double, then it will probably be quickest to just store them as doubles to begin with.

Patrick Burns on Quora says:

First off, it is perfectly feasible to use R successfully for years and not need to know the answer to this question. R handles the differences between the (usual) numerics and integers for you in the background.

> is.numeric(1)

[1] TRUE

> is.integer(1)

[1] FALSE

> is.numeric(1L)

[1] TRUE

> is.integer(1L)

[1] TRUE

(Putting capital 'L' after an integer forces it to be stored as an integer.)

As you can see "integer" is a subset of "numeric".

> .Machine$integer.max

[1] 2147483647

> .Machine$double.xmax

[1] 1.797693e+308

Integers only go to a little more than 2 billion, while the other numerics can be much bigger. They can be bigger because they are stored as double precision floating point numbers. This means that the number is stored in two pieces: the exponent (like 308 above, except in base 2 rather than base 10), and the "significand" (like 1.797693 above).

Note that 'is.integer' is not a test of whether you have a whole number, but a test of how the data are stored.

One thing to watch out for is that the colon operator, :, will return integers if the start and end points are whole numbers. For example, 1:5 creates an integer vector of numbers from 1 to 5. You don't need to append the letter L.

> class(1:5)
[1] "integer"

Reference: https://www.quora.com/What-is-the-difference-between-numeric-and-integer-in-R

To quote the help page (try ?integer), bolded portion mine:

Integer vectors exist so that data can be passed to C or Fortran code which expects them, and so that (small) integer data can be represented exactly and compactly.

Note that current implementations of R use 32-bit integers for integer vectors, so the range of representable integers is restricted to about +/-2*10^9: doubles can hold much larger integers exactly.

Like the help page says, R's integers are signed 32-bit numbers so can hold between -2147483648 and +2147483647 and take up 4 bytes.

R's numeric is identical to an 64-bit double conforming to the IEEE 754 standard. R has no single precision data type. (source: help pages of numeric and double). A double can store all integers between -2^53 and 2^53 exactly without losing precision.

We can see the data type sizes, including the overhead of a vector (source):

> object.size(1:1000)
4040 bytes
> object.size(as.numeric(1:1000))
8040 bytes

To my understanding - we do not declare a variable with a data type so by default R has set any number without L to be a numeric. If you wrote:

> x <- c(4L, 5L, 6L, 6L)
> class(x)
>"integer" #it would be correct

Example of Integer:

> x<- 2L
> print(x)

Example of Numeric (kind of like double/float from other programming languages)

> x<-3.4
> print(x)