> x <- 0:6
> class(x)
[1] "integer"
> as.numeric(x)
[1] 0 1 2 3 4 5 6
> as.logical(x)
[1] FALSE TRUE TRUE TRUE TRUE TRUE TRUE > as.character(x)
[1] "0" "1" "2" "3" "4" "5" "6"
> ## Create a vector with NAs in it
> x <- c(1, 2, NA, 10, 3)
> ## Return a logical vector indicating which elements are NA > is.na(x)
[1] FALSE FALSE TRUE FALSE FALSE
> ## Return a logical vector indicating which elements are NaN > is.nan(x)
[1] FALSE FALSE FALSE FALSE FALSE
> ## Now create a vector with both NA and NaN values > x <- c(1, 2, NaN, NA, 4)
> is.na(x)
[1] FALSE FALSE TRUE TRUE FALSE
> is.nan(x)
[1] FALSE FALSE TRUE FALSE FALSE
The Rise of
R
and
Open
Science
By: Luke Johnston
> ## Create a data frame
> y <- data.frame(a = 1, b = "a")
> ## Print 'dput' output to console
> dput(y)
structure(list(a = 1, b = structure(1L, .Label = "a", class = "factor")), .Names\
= c("a",
"b"), row.names = c(NA, -1L), class = "data.frame")
> a <- data.frame(x = rnorm(100), y = runif(100)) > b <- c(3, 4.4, 1 / 3)
>
> ## Save 'a' and 'b' to a file
> save(a, b, file = "mydata.rda")
> str(file)
function (description = "", open = "", blocking = TRUE, encoding = getOption("en\
coding"),
raw = FALSE)
Issue 3 | Nutrition of Everything | 23