r Assign groups based on the trend

Question

I have searched a lot for this simple question, but have not found a solution. It looks really simple. I have a dataframe with a column like this:

Value

0.13

0.35

0.62

0.97

0.24

0.59

0.92

0.16

0.29

0.62

0.98

All values have a range between 0 and 1. What I want is that when the value starts to drop, I assign a new group to it. Within each group, the value is increasing. So the ideal outcome will look like this:

Value Group

0.13   1

0.35   1

0.62   1

0.97   1

0.24   2

0.59   2

0.92   2

0.16   3

0.29   3

0.62   3

0.98   3

Does anyone have a suggestion for how to address this? Thanks!

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Answer 1

This isn't the most elegant solution, but it works:

value <- c(0.13, 0.35, 0.62, 0.97, 0.24, 0.59, 0.92, 0.16, 0.29, 0.62, 0.98)

foo <- data.frame(value, group = 1)
current_group <- 1
for(i in 2:nrow(foo)){
  if(foo$value[i] >= foo$value[i-1]){
    foo$group[i] <- current_group
  }else{
    current_group <- current_group + 1
    foo$group[i] <- current_group
  }
}

r Assign groups based on the trend

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