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Atomic vectors
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Jesus Christ, here we go.

First, a note about notation. When you see a reference to a vector, the writers are probably referring to atomic vectors. There is another important data type called a list or generic vector, with (naturally) different semantics. Lists are also vectors, but lists are not atomic vectors.

Anyway: The atomic vector is the simplest R data type. Atomic vectors are linear vectors of a single primitive type, like an STL Vector in C++. There is no useful literal syntax for this fundamental data type. To create one of these stupid beasts, assign like:

a <- c(1,2,3,4)

Haha, what is c()? It is a function, "c" means "concatenate," and it assembles the vectors you pass into it end-to-end. "But I passed in numerical primitives," you might think. Wrong! All naked numbers are double-width floating-point atomic vectors of length one. You're welcome. Consequences of this include:

  • a, above, is a double-typed atomic vector.
  • is.integer(2) yields FALSE, because 2 is interpreted as a floating-point value. This has implications for testing equality! You can type an integer literal by suffixing L, as in 2400L.
  • is.integer(as.integer(c(1,2))) yields TRUE, because you gave it an atomic vector of integer type.

Note that as.integer()—not integer()—is used to cast vectors to an integer type. Similar functions include as.character() and as.numeric(); you can do things like as.character(1.23) or as.numeric(c("1", "2")).

Index vectors like a[1] ... a[4]. All indexing in R is base-one. Note that no error is thrown if you try to access a[0]; it always returns an atomic vector of the same type but of length zero, written like numeric(0). Unaccountably, nobody's in jail for that decision! Indexing past the end of the vector yields the special value NA, which is used to represent missingness in R. Assigning past the end of the vector (i.e. a[10] <- 5) works and extends the vector, filling with NA. To get an zero-filled vector of a particular length and type to start with, write something like a <- integer(42).

Zero-length vectors like numeric(0) have undefined truthiness, and testing the truth value raises an error:

> if(numeric(0)) { print("Truth!"); } else {print("Folly.");}
Error in if (numeric(0)) { : argument is of length zero

Kinds of atomic vectors

  • logical (may contain TRUE, FALSE, NA)
  • integer
  • double (real is a deprecated alias)
  • complex (as in complex numbers; write as 0+0i)
  • character (pronounced "string"—see next section)
  • raw (for bitstreams; printed in hex by default. Logical operators magically operate bitwise on these; they operate elementwise on all other vector types.)

Integer and double atomic vectors are both numeric atomic vectors, i.e. is.numeric(x) is TRUE. Complex atomic vectors, duh???, are not numeric.

If you ask for a numeric vector using numeric(42) or as.numeric(x), you will get a double vector. A perfect R-ism is that if you ask for a single vector, you'll still get a double-precision float vector, though it will have a flag set so that it will be passed into C APIs as single-width floats instead of doubles. There is no single-precision storage type in R.

Check the type of your vector with typeof(x), which returns a string.

A potential source of mischief is that if you try to place a value of a particular type into an atomic vector of a different type, R will—silently, natch—recast either the value you are trying to add or the entire vector (!) to the more permissive type. Witness:

> a <- c(1L, 2L, 3L); typeof(a)
[1] "integer"
> a[1] = 2; typeof(a)
[1] "double"
> a[1] = '2'; typeof(a)
[1] "character"

Logic values

TRUE, FALSE, and NA are special logic values. NULL is also defined and is a special vector of length zero. Do not use T and F for TRUE and FALSE. You will see people doing it but they're not your friend; T and F are just variables with default values. Set T <- F and source their code and laugh as it burns.

This also means that you shouldn't ever assign useful quantities to variables named T and F. Sorry. Other variable names that you cannot use are c, q, t (!), C, D, and I. :(

NA means "not available" and is a filler quantity for missing values. The result of all comparisons with NA is NA. Use is.na(x) to test whether a value is NA, not x == NA. NA has undefined truth value, and testing it raises an error:

> if(NA) print ("Hello");
Error in if (NA) print("Hello") : missing value where TRUE/FALSE needed

NULL, by the way, also has undefined truth value, raising an error if you test it:

> if(NULL) print("Nope");
Error in if (NULL) print("Nope") : argument is of length zero

If you need to test the truth value of some x that may sometimes be NA or have zero length, you can test the charming and ever-so-concise expression identical(TRUE, as.logical(x)), which will always evaluate to true or false.

Dealing with strings

When you see "character atomic vector" you should think "string atomic vector." length('foo bar') yields 1... because you have created a character atomic vector of length one, containing the character value 'foo bar'. (Yes. I know.) length(c('to be', 'or not', 'to be')) is 3.

String primitives, which is to say the elements of a character atomic vector, are immutable.

Some other things that are true:

  • length('foo') is 1 (see above).
  • nchar('foo') is 3.
  • Strings are indexed with substr(x, start, stop). Base one, remember: substr('foo', 1, 1) is 'f'. substr('foo', 2, 3) is 'oo'.
  • You can wrap strings in either single or double quotes. Escape with backslashes as in C, e.g. 'Tim\'s bad attitude.'
  • paste() is useful for a variety of string-concatenation operations. There is also a sprintf() function.

The stringr or Biostrings packages may ease the pain of string handling in R. In particular, stringr has a very pleasant interface for matching regexps.

Vector operations

You can do vector math in R, which always operates elementwise, like the dot operators in MATLAB. R will not do linear algebra unless you explicitly ask it to (with the infix operator %*%; see ?"%*%"). Vector math is fast and dangerous. Almost nothing you can do with vector math will raise an error. If your operands are different sizes, R will silently recycle your short vector until it's long enough to perform the operation.1 R will, at least, raise a warning if your short vector does not fit into your long vector an integer number of times; fear it.

Arrays

Atomic vectors are extended to multiple dimensions as arrays. A matrix is a two-dimensional array. One-dimensional arrays are possible; the primary difference between a one-dimensional array and a vector is that dim(some.array) will have length 1 and dim(some.vector) will be NULL. N-dimensional arrays are indexed like my.array[dim1, dim2, dim3]. Use an empty value to represent "all values"—i.e., to select row 3 of a matrix, use my.matrix[3,].

Footnotes

  1. which is fucking ghastly ↩