How to write loops “for” loops in R using dplyr syntax

Question

I have an extensive block of code that I\'ve written using dplyr syntax in R. However, I am trying to put that code in a loop, so that I can ultimately create multiple output fi

Answer 1

It is unfortunate that your code didn't raise any errors. If you run your code line by line you'll understand what I'm saying. For this example I will choose the first iteration of your loop, let's replace i for "setosa":

> iris  %>% filter(iris$Species == unique(iris$Species)["setosa"])
[1] Sepal.Length Sepal.Width  Petal.Length Petal.Width  Species     
<0 rows> (or 0-length row.names)

Your filter yields a data frame with no observations, so no point in going ahead, but for this example, let's run the rest of the code:

> iris  %>% filter(iris$Species == unique(iris$Species)["setosa"]) %>%  
+ summarize(mean(iris$Petal.Length))
  mean(iris$Petal.Length)
1                   3.758

What happened is that you're calling the iris dataset from within your code, a more obvious example would be:

> filter(iris, iris$Species == unique(iris$Species)["setosa"]) %>% 
+ summarize(mean(mtcars$cyl))
  mean(mtcars$cyl)
1           6.1875

That's why you don't get the answer you expected, your filter didn't work and you got a summary statistic from another dataset.

As TJ Mahr mentioned, your code without specifying the dataset runs fine:

> for (i in unique(iris$Species))
+ {
+     iris %>% filter(Species==i) %>%
+         summarize(mean(Petal.Length)) %>% print()
+     print(i) 
+ }
  mean(Petal.Length)
1              1.462
[1] "setosa"
  mean(Petal.Length)
1               4.26
[1] "versicolor"
  mean(Petal.Length)
1              5.552
[1] "virginica"

I hope this helps

Answer 2

As I mentioned in my comment, if you really need the results separated, it will probably be easier to just use group_by and then split() the results:

iris %>% 
  group_by(Species) %>% 
  summarise(mn = mean(Petal.Length)) %>% 
  split(.,.$Species)

$setosa
# A tibble: 1 × 2
  Species    mn
   <fctr> <dbl>
1  setosa 1.462

$versicolor
# A tibble: 1 × 2
     Species    mn
      <fctr> <dbl>
1 versicolor  4.26

$virginica
# A tibble: 1 × 2
    Species    mn
     <fctr> <dbl>
1 virginica 5.552