Is there a function like switch which works inside of dplyr::mutate?
dplyr, r
Solution
Eons too late for the OP, but in case this shows up in a search ...
dplyr v0.5 has `recode()`, a vectorized version of `switch()`, so
data_frame(
x = sample(1:4, 10, replace=TRUE),
y1 = rnorm(n=10, mean=7, sd=2),
y2 = rnorm(n=10, mean=5, sd=2),
y3 = rnorm(n=10, mean=7, sd=1),
y4 = rnorm(n=10, mean=5, sd=1)
) %>%
mutate(y = recode(x,y1,y2,y3,y4))
produces, as anticipated:
# A tibble: 10 x 6
x y1 y2 y3 y4 y
<int> <dbl> <dbl> <dbl> <dbl> <dbl>
1 2 6.950106 6.986780 7.826778 6.317968 6.986780
2 1 5.776381 7.706869 7.982543 5.048649 5.776381
3 2 7.315477 2.213855 6.079149 6.070598 2.213855
4 3 7.461220 5.100436 7.085912 4.440829 7.085912
5 3 5.780493 4.562824 8.311047 5.612913 8.311047
6 3 5.373197 7.657016 7.049352 4.470906 7.049352
7 2 6.604175 9.905151 8.359549 6.430572 9.905151
8 3 11.363914 4.721148 7.670825 5.317243 7.670825
9 3 10.123626 7.140874 6.718351 5.508875 6.718351
10 4 5.407502 4.650987 5.845482 4.797659 4.797659
(Also works with named args, including character and factor x's.)
Problem
I can't use switch inside of `mutate` because it returns the whole vector instead of just the row. As a hack, I'm using: ``` pick <- function(x, v1, v2, v3, v4) { ifelse(x == 1, v1, ifelse(x == 2, v2, ifelse(x == 3, v3, ifelse(x == 4, v4, NA)))) } ``` This works inside of `mutate`, and is fine for now because I'm typically choosing among 4 things, but that may change. Can you recommend an alternative? For example: ``` library(dplyr) df.faithful <- tbl_df(faithful) df.faithful$x <- sample(1:4, 272, rep=TRUE) df.faithful$y1 <- rnorm(n=272, mean=7, sd=2) df.faithful$y2 <- rnorm(n=272, mean=5, sd=2) df.faithful$y3 <- rnorm(n=272, mean=7, sd=1) df.faithful$y4 <- rnorm(n=272, mean=5, sd=1) ``` Using `pick`: ``` mutate(df.faithful, y = pick(x, y1, y2, y3, y4)) Source: local data frame [272 x 8] eruptions waiting x y1 y2 y3 y4 y 1 3.600 79 1 8.439092 5.7753006 8.319372 5.078558 8.439092 2 1.800 54 2 13.515956 6.1971512 6.343157 4.962349 6.197151 3 3.333 74 4 7.693941 6.8973365 5.406684 5.425404 5.425404 4 2.283 62 4 12.595852 6.9953995 7.864423 3.730967 3.730967 5 4.533 85 3 11.952922 5.1512987 9.177687 5.511899 9.177687 6 2.883 55 3 7.881350 1.0289711 6.304004 3.554056 6.304004 7 4.700 88 4 8.636709 6.3046198 6.788619 5.748269 5.748269 8 3.600 85 1 8.027371 6.3535056 7.152698 7.034976 8.027371 9 1.950 51 1 5.863370 0.1707758 5.750440 5.058107 5.863370 10 4.350 85 1 7.761653 6.2176610 8.348378 1.861112 7.761653 .. ... ... . ... ... ... ... ... ``` We see that I copy the value from y1 into y if x == 1, and so on. This is what I'm looking to do, but want to be able to do it, whether I have a list of 4 or 400 columns. Trying to use `switch`: ``` mutate(df.faithful, y = switch(x, y1, y2, y3, 4)) Error in switch(c(1L, 2L, 4L, 4L, 3L, 3L, 4L, 1L, 1L, 1L, 4L, 3L, 1L, : EXPR must be a length 1 vector ``` Trying to use `list`: ``` mutate(df.faithful, y = list(y1, y2, y3, y4)[[x]]) Error in list(c(8.43909205142925, 13.5159559591257, 7.69394050059568, : recursive indexing failed at level 2 ``` Trying to use `c`: ``` mutate(df.faithful, y = c(y1, y2, y3, y4)[x]) Source: local data frame [272 x 8] eruptions waiting x y1 y2 y3 y4 y 1 3.600 79 1 8.439092 5.7753006 8.319372 5.078558 8.439092 2 1.800 54 2 13.515956 6.1971512 6.343157 4.962349 13.515956 3 3.333 74 4 7.693941 6.8973365 5.406684 5.425404 12.595852 4 2.283 62 4 12.595852 6.9953995 7.864423 3.730967 12.595852 5 4.533 85 3 11.952922 5.1512987 9.177687 5.511899 7.693941 6 2.883 55 3 7.881350 1.0289711 6.304004 3.554056 7.693941 7 4.700 88 4 8.636709 6.3046198 6.788619 5.748269 12.595852 8 3.600 85 1 8.027371 6.3535056 7.152698 7.034976 8.439092 9 1.950 51 1 5.863370 0.1707758 5.750440 5.058107 8.439092 10 4.350 85 1 7.761653 6.2176610 8.348378 1.861112 8.439092 .. ... ... . ... ... ... ... ... ``` No errors are produced, but the behavior is not as intended.