The set of function that allows to perform most common operations ion data sample.
unique_sample(sim_expr, ..., unique = TRUE, n_name = "n", n_iter = 10)
na_rand(sample_vec, na_ratio, not_null = FALSE)
levels_rand(sample_vec, levels_ratio, unique)Expression to be evaluated in order to get column sample.
Parameters and their values that are used in sim_expr.
If TRUE the function will try to simulate unique values.
Name of the parameter providing sample length (for example 'n' for rnorm and 'size' for sample).
Number of iteration to make to assure the returned values are unique.
Vector to which NA values should be injected.
Ratio (in terms of column length) of NA values to attach to the sample.
Information whether NA's are allowed.
Ratio of unique levels in terms of whole sample length.
unique_sample - takes simulation expression and assures the expression will be executed as many times as needed to return unique result sample.
na_rand - attaches NA values to the sample according to provided NA's ratio.
levels_rand - takes provided number of sample levels, and assures the returned sample have as many levels as requested.
unique_sample(rnorm(n, mean = my_mean), n = 10, my_mean = 2)
#> [1] -0.9751768 1.4232448 2.3145267 1.3069100 2.5500642 1.8788824
#> [7] 2.6350277 1.0081140 2.2643543 1.5788523
unique_sample(sample(values, size, replace = TRUE), size = 10, values = 1:10, n_name = "size")
#> Error in unique_sample(sample(values, size, replace = TRUE), size = 10, values = 1:10, n_name = "size"): It wasn't possible to generate the unique sample. Please make sure sampling configuration is correct.
if (FALSE) {
## In 10 iterations it was not possible to simulate 6 unique values from the vector 1:5
unique_sample(sample(values, size, replace = TRUE), size = 6, values = 1:5, n_name = "size")
}
na_rand(1:10, na_ratio = 0.5)
#> [1] 1 2 NA NA NA 6 7 NA NA 10