# Simple Random Sampling Of Rows

Want to learn more? I recommend working through: R for Data Science, R Cookbook, and R Graphics Cookbook.

```# create a dataframe with simulated values
x <- runif(1000)
y <- runif(1000)
z <- runif(1000)
a <- runif(1000)
df <- data.frame(x, y, z, a)
```
```# create a vector of weighs
w <- runif(1000)
```
```# sample 10 rows of the dataframe at pseudorandom, without replacement
sample <- df[sample(1:nrow(df), 10, replace = F),]
```
```sample
```
```             x         y          z           a
500 0.44885287 0.7228785 0.11504159 0.054208551
980 0.08392782 0.4568137 0.04393736 0.639204705
445 0.48527409 0.9822628 0.37823768 0.410292231
734 0.54769226 0.8992187 0.58030521 0.178938602
177 0.43245083 0.9172805 0.02955689 0.743852472
266 0.94394635 0.7638428 0.43960561 0.942814638
256 0.77091541 0.2714964 0.49622060 0.009319224
944 0.92682962 0.4278643 0.87805822 0.283003822
492 0.84598479 0.7312344 0.02114653 0.366224907
409 0.71072941 0.8280846 0.03118358 0.196112987
```
```# sample 10 rows of the dataframe at pseudorandom, without replacement, with the selection of reach row weighted by w (note w doesn't need to add up to 1)
sample.weighted <- df[sample(1:nrow(df), 10, replace = F, prob = w),]
```
```sample.weighted
```
```             x         y         z         a
588 0.42359291 0.7747600 0.3443440 0.7502456
417 0.23503932 0.2448383 0.8961582 0.2380380
997 0.05755856 0.1587866 0.8144725 0.3183274
789 0.46962589 0.5453313 0.3952169 0.5651571
646 0.74493118 0.5151418 0.8717189 0.8330892
231 0.60350137 0.2860977 0.8010951 0.7727321
957 0.11192911 0.8962056 0.1051003 0.7203017
947 0.38530976 0.7359524 0.1379156 0.7036205
101 0.32523590 0.8928368 0.2648167 0.8808521
208 0.84037450 0.8692373 0.5897262 0.2414655
```