The {samplezoo} package simplifies generating samples with various probability distributions, enabling users to quickly create data frames for demonstrations, troubleshooting, or teaching. By prioritizing simplicity and speed over customization of sample parameters, {samplezoo} reduces the need for repetitive code, making it particularly useful for beginners or anyone seeking to save time while working with statistical and probabilistic data.
You can install the development version of samplezoo from GitHub with:
# install.packages("pak")
pak::pak("nvietto/samplezoo")Creating or reprexing datasets on the Posit Community help forum can be challenging, especially for beginners. Similarly, building quick datasets for lectures, troubleshooting, or homework assignments often involves repetitive and time-consuming code that’s easy to forget. To simplify these tasks and save some time, {samplezoo} provides a streamlined approach to generating data sets.
For example, generating a dataset with various probability distributions typically looks like this:
numeric_data <- data.frame(
norm = rnorm(n = 100, mean = 50, sd = 15),
norm2 = rnorm(n = 100, mean = 60, sd = 10),
norm3 = rnorm(n = 100, mean = 40, sd = 20),
binom = rbinom(n = 100, size = 1, prob = 0.20),
neg = rnbinom(n = 100, size = 1, prob = 0.50),
pois = rpois(n = 100, lambda = 3),
exp = rexp(n = 100, rate = 0.10),
unif = runif(n = 100, min = 0, max = 1),
beta = rbeta(n = 100, shape1 = 2, shape2 = 5),
gamma = rgamma(n = 100, shape = 2, scale = 2),
chisq = rchisq(n = 100, df = 2),
t_dist = rt(n = 100, df = 10)
)
numeric_data <- round(numeric_data, 2)
head(numeric_data)
norm norm2 norm3 binom neg pois exp unif beta gamma chisq t_dist
1 46.38 73.25 34.66 0 4 4 8.49 0.89 0.32 1.30 2.94 -0.71
2 55.60 60.73 34.37 0 0 2 7.26 0.08 0.20 2.98 1.23 -0.88
3 42.81 68.03 18.15 0 1 0 0.02 0.70 0.17 2.18 3.89 -0.75
4 26.75 62.36 -3.14 0 0 3 11.92 0.05 0.20 8.72 2.16 -1.24
5 51.77 67.96 13.18 0 0 2 3.90 0.34 0.04 5.58 1.22 -0.74
6 65.95 64.32 38.59 0 0 2 6.85 0.04 0.29 8.12 4.32 0.88With {samplezoo}, you can use one line of code:
library(samplezoo)
small_data <- samplezoo("small")
small_data <- round(small_data, 2)
head(small_data)
norm norm2 norm3 binom neg pois exp unif beta gamma chisq t_dist
1 21.96 57.23 24.31 0 1 3 0.66 0.95 0.20 2.97 3.75 -0.05
2 51.54 60.12 55.61 0 1 3 24.26 0.01 0.25 2.25 8.63 -0.36
3 46.76 63.80 15.81 0 0 7 16.84 0.27 0.14 3.47 6.60 -0.49
4 44.86 58.63 37.32 1 1 4 8.58 0.70 0.22 1.26 0.92 -0.04
5 47.39 43.17 72.43 0 1 2 0.83 0.13 0.11 1.28 0.68 -1.04
6 57.07 71.30 19.79 0 1 4 1.14 0.47 0.18 1.35 3.35 1.44