Conditionally applying functions to grouped dataframes in R with magrittr, dplyr and purrr

Question

I would like to use the succinctness of magrittr, dplyr and possibly purrr to split a large dataframe (with many variables of different types) by one variable x and then apply different functions conditionally by x to each group and row within a group to a second variable y.

Take the dataframe df <- data.frame(a, b, x, c, d, y), where x are factors (foo, bar) and y are numbers. I can do what I have described inelegantly with an unpiped workflow thus:

df$y[df$x == "foo"] %<>% subtract(min(.))
df$y[df$x == "bar"] %<>% add(max(df$y[df$x == "foo"]))

I would like to rewrite this using dplyr and add it to a long pipe for df, but all my attempts to combine mutate, sapply and do have failed; as have attempts to incorporate purrr with anonymous functions, by_slice and dmap.

Many thanks in advance for the advice.

if you could supply a sample data set I could try to answer. — timelyportfolio, Apr 06 '16 at 15:45

score 2 · Answer 1 · answered May 22 '16 at 12:34

This is more dplyr than magrittr, but I think it's also more readable. I'm a bit uncomfortable with %<>% because it disrupts the linear structure of operations, and makes the code harder to read. So I just use %>% here.

An example dataframe that matches your description:

df <- data.frame(a = 'a', 
                 b = 'b', 
                 x = c("foo", "bar") , 
                 c = 'c', 
                 d = 'd', 
                 y = 1:6) 
df
  a b   x c d y
1 a b foo c d 1
2 a b bar c d 2
3 a b foo c d 3
4 a b bar c d 4
5 a b foo c d 5
6 a b bar c d 6

Your code:

library(dplyr)
library(magrittr)
df$y[df$x == "foo"] %<>% subtract(min(.))

df
  a b   x c d y
1 a b foo c d 0
2 a b bar c d 2
3 a b foo c d 2
4 a b bar c d 4
5 a b foo c d 4
6 a b bar c d 6

df$y[df$x == "bar"] %<>% add(max(df$y[df$x == "foo"]))

df
  a b   x c d  y
1 a b foo c d  0
2 a b bar c d  6
3 a b foo c d  2
4 a b bar c d  8
5 a b foo c d  4
6 a b bar c d 10

A dplyr solution:

df %>% 
  mutate(y = ifelse(x == "foo", y - min(y), y)) %>% 
  mutate(y = ifelse(x == "bar", y + max(y[x == 'foo']), y))

  a b   x c d  y
1 a b foo c d  0
2 a b bar c d  6
3 a b foo c d  2
4 a b bar c d  8
5 a b foo c d  4
6 a b bar c d 10

Conditionally applying functions to grouped dataframes in R with magrittr, dplyr and purrr

1 Answers1