CODEWITHSUNDEEP
rloopsdplyr
W148SMH
W148SMH

Reputation: 172

custom functions inside nested for loops

I'd like generate a list of data.frames inside nested loops similar to this question. In the second loop, j should be 4, then 5 but it only runs as 5. Is the error with my function or in the way I'm using nested loops? 

df=data.frame(Value=c(11,4,6,10,7,2)) 

exceedance_fun= function(x,y){ 
z=case_when(
  x > y ~ "No",
  x <= y ~ paste(y,"mg/L"),
  TRUE ~ "unsure"
)
return(z)
}  

datalist = list()

for (i in 1:2) {
for (j in 4:5) {
dat=df %>%
mutate(Vio= exceedance_fun(Value,j))
dat$i <- i
datalist[[i]] <- dat 
}
}

Incorrect Output

[[1]]
Value    Vio i
1    11     No 1
2     4 5 mg/L 1  #This should be 4 mg/L
3     5 5 mg/L 1  #This should be 4 mg/L
4    10     No 1
5     7     No 1
6     2 5 mg/L 1  #This should be 4 mg/L

[[2]]
Value    Vio i
1    11     No 2
2     4 5 mg/L 2
3     5 5 mg/L 2
4    10     No 2
5     7     No 2
6     2 5 mg/L 2

Upvotes: 0

Views: 143

Answers (1)

Gregor Thomas
Gregor Thomas

Reputation: 145775

Here's how I would recommend restructuring in the general case where you are changing multiple parameters meaningfully:

params = expand.grid(i = 1:2, j = 4:5)
datalist = list()

for (k in 1:nrow(params)) {
  datalist[[k]] = df %>%
    mutate(Vio= exceedance_fun(Value,param$j[k]),
           i = params$i[k])
}

I'd also recommend using more descriptive variable names than i and j, but I can't tell what those are.

However, in this case, i doesn't really do anything, so a single for loop is probably fine:

j_vals = 4:5
datalist = list()

for (i in seq_along(j_vals)) {
  datalist[[i]] = df %>%
    mutate(Vio= exceedance_fun(Value, j_vals[i]),
           i = i)
}

Though it seems like it might be more useful to record j than i...

Upvotes: 1

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