Can dplyr package be used for conditional mutating?

Question

Can the mutate be used when the mutation is conditional (depending on the values of certain column values)? This example helps showing what I mean. ``` structure(list(a = c(1, 3, 4, 6, 3, 2, 5, 1), b = c(1, 3, 4, 2, 6, 7, 2, 6), c = c(6, 3, 6, 5, 3, 6, 5, 3), d = c(6, 2, 4, 5, 3, 7, 2, 6), e = c(1, 2, 4, 5, 6, 7, 6, 3), f = c(2, 3, 4, 2, 2, 7, 5, 2)), .Names = c("a", "b", "c", "d", "e", "f"), row.names = c(NA, 8L), class = "data.frame") a b c d e f 1 1 1 6 6 1 2 2 3 3 3 2 2 3 3 4 4 6 4 4 4 4 6 2 5 5 5 2 5 3 6 3 3 6 2 6 2 7 6 7 7 7 7 5 2 5 2 6 5 8 1 6 3 6 3 2 ``` I was hoping to find a solution to my problem using the dplyr package (and yes I know this not code that should work, but I guess it makes the purpose clear) for creating a new column g: ``` library(dplyr) df <- mutate(df, if (a == 2 | a == 5 | a == 7 | (a == 1 & b == 4)){g = 2}, if (a == 0 | a == 1 | a == 4 | a == 3 | c == 4) {g = 3}) ``` The result of the code I am looking for should have this result in this particular examp…

Accepted Answer

Use `ifelse`

```
df %>%
  mutate(g = ifelse(a == 2 | a == 5 | a == 7 | (a == 1 & b == 4), 2,
               ifelse(a == 0 | a == 1 | a == 4 | a == 3 |  c == 4, 3, NA)))
```

Added - if_else: Note that in dplyr 0.5 there is an `if_else` function defined so an alternative would be to replace `ifelse` with `if_else`; however, note that since `if_else` is stricter than `ifelse` (both legs of the condition must have the same type) so the `NA` in that case would have to be replaced with `NA_real_` .

```
df %>%
  mutate(g = if_else(a == 2 | a == 5 | a == 7 | (a == 1 & b == 4), 2,
               if_else(a == 0 | a == 1 | a == 4 | a == 3 |  c == 4, 3, NA_real_)))
```

Added - case_when Since this question was posted dplyr has added `case_when` so another alternative would be:

```
df %>% mutate(g = case_when(a == 2 | a == 5 | a == 7 | (a == 1 & b == 4) ~ 2,
                            a == 0 | a == 1 | a == 4 | a == 3 |  c == 4 ~ 3,
                            TRUE ~ NA_real_))
```

Added - arithmetic/na_if If the values are numeric and the conditions (except for the default value of NA at the end) are mutually exclusive, as is the case in the question, then we can use an arithmetic expression such that each term is multiplied by the desired result using `na_if` at the end to replace 0 with NA.

```
df %>%
  mutate(g = 2 * (a == 2 | a == 5 | a == 7 | (a == 1 & b == 4)) +
             3 * (a == 0 | a == 1 | a == 4 | a == 3 |  c == 4),
         g = na_if(g, 0))
```

Can dplyr package be used for conditional mutating?

Solution

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