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I am trying to create a loop to calculate relative elemental levels for each fish in this dataset (relative elemental levels will be calculated by x/mean(x) in order to divide each data point by the mean of the entire column. I have all the fish in one dataframe but they can be filtered out by ID (see head of data frame) 1st fish is Ring10_1_2. Here is my current code and the current error I am getting.

raw_data <- read_csv("Hatch5Reg.csv")

fishIDs = unique(raw_data$ID)

Hatch5_Rel_El = list()
for(ID in fishIDs) {
  Hatch5_Rel_El[[ID]] = lapply(raw_data %>% filter(ID == ID_) %>% mutate_if(is.numeric),funs(mod = x / mean(x)))
  
}

#Error in match.fun(FUN) : 'funs(mod = x/mean(x))' is not a function, character or symbol

head of raw_data

Ritchie Sacramento
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confusedindividual
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1 Answers1

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Since no sample data is provided, please see How to make a great R reproducible example, the following would work on iris data:

iris %>% 
  mutate(across(where(is.numeric), ~.x /mean(.x)))

    Sepal.Length Sepal.Width Petal.Length Petal.Width    Species
1      0.8727895   1.1447885    0.3725386  0.16675931     setosa
2      0.8385625   0.9812473    0.3725386  0.16675931     setosa
3      0.8043354   1.0466638    0.3459287  0.16675931     setosa
4      0.7872219   1.0139555    0.3991485  0.16675931     setosa
5      0.8556760   1.1774967    0.3725386  0.16675931     setosa
6      0.9241301   1.2756215    0.4523683  0.33351862     setosa

BTW, mutate_if has been superseded by using across in the more recent dplyr versions.

Lennyy
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  • Hi @Lennyy thank you for sending this example. This is exactly what I want to do but I would want it to only run on data by species. So for this example you would get three separate lists for each species setosa,, virginica etc.. – confusedindividual Mar 24 '22 at 16:05
  • Your welcome. For that purpose you could just add a `group_by(Species)` before the `mutate`. – Lennyy Mar 25 '22 at 10:17