As a teacher, I not only teach but also assess the achievements of students. One example of a typical student assignments is a presentation. You know, powerpoint slides and stuff.

For that purpose, I often need to map students to one of several time slots. Here’s the R code I use for that purpose.

`library(tidyverse)`

`## ── Attaching packages ────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──`

```
## ✔ ggplot2 3.0.0 ✔ purrr 0.2.5
## ✔ tibble 1.4.2 ✔ dplyr 0.7.6
## ✔ tidyr 0.8.1 ✔ stringr 1.3.1
## ✔ readr 1.1.1 ✔ forcats 0.3.0
```

`## Warning: package 'dplyr' was built under R version 3.5.1`

```
## ── Conflicts ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
```

How many students are subscribed to the assignment?

`stud_count <- 20`

Let’s say there 20 students in the course.

Let’s assume, for each time slot, 10 students can be allocated (not more time for more student for one slot).

```
slots_count <- (stud_count / 10) %>% ceiling # round to next integer
slots_count
```

`## [1] 2`

That gives 2 time slots.

Now let’s map the students to the slots on a random base:

```
slot <- 1:max(slots_count)
set.seed(2018)
allocation <- replicate(n = 10,
sample(x = slot)) %>% as.vector
```

What we’ve done here is:

- Take the first triplet of students and randomly assign them to the three slots (so that each of the three students has a unique slot, ie sampling without replacement)
- Repeat that for the rest of the triplets

Let’s check whether the `allocation`

has worked:

`table(allocation)`

```
## allocation
## 1 2
## 10 10
```

Worked out. Presentations ahead.

Let’s save the vector as a csv-file for the easy of interfacing with other applications such as Excel.

```
library(rio)
export(data_frame(slots = allocation),
file = "slots.csv")
```