CODEWITHSUNDEEP
rdplyr
Ujjawal Bhandari
Ujjawal Bhandari

Reputation: 1372

Conditional Evaluation in Dplyr

I have a character vector r <- c(). I want to mutate on dataframe based on length of r

This works

iris %>% if(length(r) > 0) mutate(Test = 1) else .

This does not work when I expand to add more dplyr verbs

iris %>% if(length(r) > 0) mutate(Test = 1) else . %>% mutate(Test2 = 1)

I am only looking for dplyr based solution.

Upvotes: 4

Views: 267

Answers (4)

josep maria porr&#224;
josep maria porr&#224;

Reputation: 1396

library(dplyr)

Using an intermediate function provides an alternative solution once it is substituted by an anonymous function

g_if <- function(df, r){
  if(length(r)) {
    ans <- df %>% mutate(test = 1)
  } else {
    ans <- df
  }
  invisible(ans)
}

r <- c()
iris %>% g_if(r) %>% str
#> 'data.frame':    150 obs. of  5 variables:
#>  $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
#>  $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
#>  $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
#>  $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
#>  $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...

r <- c(1)
iris %>% g_if(r) %>% str
#> 'data.frame':    150 obs. of  6 variables:
#>  $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
#>  $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
#>  $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
#>  $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
#>  $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
#>  $ test        : num  1 1 1 1 1 1 1 1 1 1 ...

Now, we can use the same idea with an anonymous function, that is, without defining explicitely function g_if()

r <- c()
iris %>% {
  function(df, cond){
    if(length(cond) > 0) {
      ans <- df %>% mutate(test = 1)
    } else {
      ans <- df
    }
    ans}}(r) %>%
head
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1          5.1         3.5          1.4         0.2  setosa
#> 2          4.9         3.0          1.4         0.2  setosa
#> 3          4.7         3.2          1.3         0.2  setosa
#> 4          4.6         3.1          1.5         0.2  setosa
#> 5          5.0         3.6          1.4         0.2  setosa
#> 6          5.4         3.9          1.7         0.4  setosa

r <- c(1)
iris %>% {
  function(df, cond){
    if(length(cond) > 0) {
      ans <- df %>% mutate(test = 1)
    } else {
      ans <- df
    }
    ans}}(r) %>%
head
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species test
#> 1          5.1         3.5          1.4         0.2  setosa    1
#> 2          4.9         3.0          1.4         0.2  setosa    1
#> 3          4.7         3.2          1.3         0.2  setosa    1
#> 4          4.6         3.1          1.5         0.2  setosa    1
#> 5          5.0         3.6          1.4         0.2  setosa    1
#> 6          5.4         3.9          1.7         0.4  setosa    1

Created on 2021-06-17 by the reprex package (v0.3.0)

Upvotes: 2

marqui
marqui

Reputation: 31

The below code will add the variable if the condition is met. If not, it will add a variable populated will all NA and eventually remove it (I understand you need the new variable only if the condition is met).

library(dplyr)

r <- c()

iris %>% 
  mutate(test2=if_else(length(r)>0, 2, NULL)) %>% 
  select(where(~ !(all(is.na(.))))) #remove columns with all NAs

Upvotes: 0

akrun
akrun

Reputation: 887851

As there are multiple statements, wrap it inside a {}

r <- c()
iris %>%
    {if(length(r) > 0) {
        mutate(., Test = 1)
      } else .}
    Sepal.Length Sepal.Width Petal.Length Petal.Width    Species
1            5.1         3.5          1.4         0.2     setosa
2            4.9         3.0          1.4         0.2     setosa
3            4.7         3.2          1.3         0.2     setosa
4            4.6         3.1          1.5         0.2     setosa
...

-testing with r length > 0

r <- 5
iris %>%
     {if(length(r) > 0) {
         mutate(., Test = 1)
       } else .}
    Sepal.Length Sepal.Width Petal.Length Petal.Width    Species Test
1            5.1         3.5          1.4         0.2     setosa    1
2            4.9         3.0          1.4         0.2     setosa    1
3            4.7         3.2          1.3         0.2     setosa    1
...

However, this can be easily modified without a loop i.e. convert the logical vector to numeric index by adding 1 (as indexing in R starts from 1). Use that to select a list with values 1 and NULL. If the length is 0, then NULL is selected and thus no column is created

iris %>%
    mutate(Test =  list(NULL, 1)[[1 + (length(r) > 0)]])

Upvotes: 3

TarJae
TarJae

Reputation: 79204

We could use ifelse

library(dplyr)
r <- c()
iris %>% 
  mutate(Test = ifelse(length(r) > 0, 1,1))

Output:

  Sepal.Length Sepal.Width Petal.Length Petal.Width Species Test
1          5.1         3.5          1.4         0.2  setosa    1
2          4.9         3.0          1.4         0.2  setosa    1
3          4.7         3.2          1.3         0.2  setosa    1
4          4.6         3.1          1.5         0.2  setosa    1
5          5.0         3.6          1.4         0.2  setosa    1
6          5.4         3.9          1.7         0.4  setosa    1

Upvotes: 0

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