RDocumentation: sample

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if(!require('base')) {
    install.packages('base')
    library('base')
}

x <- 1:12
# a random permutation
sample(x)
# bootstrap resampling -- only if length(x) > 1 !
sample(x, replace = TRUE)

# 100 Bernoulli trials
sample(c(0,1), 100, replace = TRUE)

## More careful bootstrapping --  Consider this when using sample()
## programmatically (i.e., in your function or simulation)!

# sample()'s surprise -- example
x <- 1:10
    sample(x[x >  8]) # length 2
    sample(x[x >  9]) # oops -- length 10!
    sample(x[x > 10]) # length 0

## safer version:
resample <- function(x, ...) x[sample.int(length(x), ...)]
resample(x[x >  8]) # length 2
resample(x[x >  9]) # length 1
resample(x[x > 10]) # length 0

## R 3.x.y only
sample.int(1e10, 12, replace = TRUE)
sample.int(1e10, 12) # not that there is much chance of duplicates

Data frameas

df

variable

-- Select the names and most recent salaries of all current employees
SELECT first_name,
        last_name,
        hire_date,
        salary
FROM employees
  INNER JOIN salaries USING(emp_no)
WHERE to_date = (SELECT MAX(to_date) FROM salaries)
ORDER BY emp_no
LIMIT 5