CODEWITHSUNDEEP
rdataframerowsubtraction
A.Benson
A.Benson

Reputation: 479

Subtract one row from another row in an R data.frame

I have a fairly large data.frame that shows the results of a data analysis for two treatments (plus a control) for a range of tree species. I'd like to be able to create a new data.frame that shows the difference between the control and each treatment for each species.

Here's some dummy data to show what I'm trying to do

dat <- data.frame(species = rep (c("Oak", "Elm", "Ash"), each = 3), 
                  result = c(10, 7, 4, 13, 9, 2, 8, 5, 1), 
                  treatment = rep(c('Ctrl', 'Type_1', 'Type_2')))

  species result treatment
1     Oak     10      Ctrl
2     Oak      7    Type_1
3     Oak      4    Type_2
4     Elm     13      Ctrl
5     Elm      9    Type_1
6     Elm      2    Type_2
7     Ash      8      Ctrl
8     Ash      5    Type_1
9     Ash      1    Type_2

What I'd like to do is subtract the Type_1 and Type_2 treatment results for each species by the respective control and generate a new data.frame containing the results. It should look like this.

 species result treatment_diff
1     Oak      3         Type_1
2     Oak      6         Type_2
3     Elm      4         Type_1
4     Elm     11         Type_2
5     Ash      3         Type_1
6     Ash      7         Type_2

Happy to take a dplyr, tidyr, datatable or any other solution

Thanks very much

Upvotes: 0

Views: 775

Answers (1)

Quinten
Quinten

Reputation: 41285

An option could be using group_by and use the first value for each group to extract with and filter the rows with result 0 like this:

dat <- data.frame(species = rep (c("Oak", "Elm", "Ash"), each = 3), 
                  result = c(10, 7, 4, 13, 9, 2, 8, 5, 1), 
                  treatment = rep(c('Ctrl', 'Type_1', 'Type_2')))

library(dplyr)
dat %>%
  group_by(species) %>%
  mutate(result = first(result) - result) %>%
  filter(result != 0)
#> # A tibble: 6 × 3
#> # Groups:   species [3]
#>   species result treatment
#>   <chr>    <dbl> <chr>    
#> 1 Oak          3 Type_1   
#> 2 Oak          6 Type_2   
#> 3 Elm          4 Type_1   
#> 4 Elm         11 Type_2   
#> 5 Ash          3 Type_1   
#> 6 Ash          7 Type_2

Created on 2022-07-29 by the reprex package (v2.0.1)

Upvotes: 1

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