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Suppose I have a dataset with (90,000 x 17) i.e. (n x p) where n is the number of observations and p is the number of variables and I would like to take a random sample of 20% of rows from my whole dataset how can this be done in R?

After taking a random sample I will be performing cluster analysis accordingly.

I had tried using other questions to answer my question but they were inconclusive because it was not giving me what I needed.

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    sample() with repeated sampling could help Commented Mar 5, 2019 at 14:33
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    df[sample(nrow(df), nrow(df)*0.2),] Commented Mar 5, 2019 at 14:34
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    Remember to fix seed set.seed(1492) (or any number) in order to obtain reproducibility of your sample! Commented Mar 5, 2019 at 14:35

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You can do it with sample_frac from dplyr, here is an example with the database iris

 library(dplyr) #data(iris) sample20 <- iris %>% sample_frac(0.2)
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