I would like to proportionally split the data I have. For example, I have 100 rows and I want to randomly sample 1 row every two rows. Using tidymodels rsample I assumed I would do the below.
dat <- as_tibble(seq(1:100))
split <- inital_split(dat, prop = 0.5, breaks = 50)
testing <- testing(split)
When checking the data the split hasnt done what I thought it would. It seems close but not exactly. I thought the breaks call generates bins which are sampled from. So, breaks = 50 would split the the 100 rows into 50 bins, therefore having two rows per bin. I have also tried strata = value to strafy accross the rows but I cannot get this to work either.
I am using this as an exaple but I am also curious how this would work when sampling 1 row every four etc.
Have I miss understood the breaks call function?
There is an argument that protects users from trying to create stratified splits that are too small that you are running up against; it's called pool:
library(rsample)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
dat <- tibble(value = seq(1:100), strat = as.factor(rep(1:50, each = 2)))
dat
#> # A tibble: 100 × 2
#> value strat
#> <int> <fct>
#> 1 1 1
#> 2 2 1
#> 3 3 2
#> 4 4 2
#> 5 5 3
#> 6 6 3
#> 7 7 4
#> 8 8 4
#> 9 9 5
#> 10 10 5
#> # … with 90 more rows
split <- initial_split(dat, prop = 0.5, strata = strat, pool = 0.0)
#> Warning: Stratifying groups that make up 0% of the data may be statistically risky.
#> • Consider increasing `pool` to at least 0.1
split
#> <Analysis/Assess/Total>
#> <50/50/100>
training(split) %>% arrange(strat)
#> # A tibble: 50 × 2
#> value strat
#> <int> <fct>
#> 1 1 1
#> 2 4 2
#> 3 5 3
#> 4 8 4
#> 5 10 5
#> 6 12 6
#> 7 13 7
#> 8 16 8
#> 9 17 9
#> 10 20 10
#> # … with 40 more rows
testing(split) %>% arrange(strat)
#> # A tibble: 50 × 2
#> value strat
#> <int> <fct>
#> 1 2 1
#> 2 3 2
#> 3 6 3
#> 4 7 4
#> 5 9 5
#> 6 11 6
#> 7 14 7
#> 8 15 8
#> 9 18 9
#> 10 19 10
#> # … with 40 more rows
Created on 2022-02-22 by the reprex package (v2.0.1)
We really don't recommend turning pool down to zero like this, but you can do it here to see how the strata and prop arguments work.