CODEWITHSUNDEEP
rfunctiondplyrtidyverse
M_M
M_M

Reputation: 909

Using a custom function with tidyverse

I created a dummy function to get the lag of one variable and I want to use it with other tidyverse functions. It works after I call mutate but not after calling group_by. It throws the following error: Error in mutate_impl(.data, dots) : Not compatible with STRSXP: [type=NULL].

Here is a repex:

#create a function to lag a selected variable
lag_func <- function(df, x) {
  mutate(df, lag = lag(df[,x])) 
}

#works
iris %>% 
  mutate(lead = lead(Petal.Length)) %>%
  lag_func('Petal.Length')

#doesn't work
iris %>%
  group_by(Species) %>%
  mutate(lead = lead(Petal.Length)) %>%
  lag_func('Petal.Length')

Any idea what the error means and/or how to fix it?

Upvotes: 2

Views: 1689

Answers (1)

Abdallah Atef
Abdallah Atef

Reputation: 671

The best way to pass a column name as an argument to a tidyverse function is convert it to quosure using enquo(). See this code:

lag_func <- function(df, x) {
  x <- enquo(x)
  mutate(df, lag = lag(!!x)) # !! is to evaluate rather than quoting (x)
}

Now let's try our function:

iris %>%
  group_by(Species) %>%
  mutate(lead = lead(Petal.Length)) %>%
  lag_func(Petal.Length)

# A tibble: 150 x 7
# Groups:   Species [3]
   Sepal.Length Sepal.Width Petal.Length Petal.Width Species  lead   lag
          <dbl>       <dbl>        <dbl>       <dbl> <fct>   <dbl> <dbl>
 1          5.1         3.5          1.4         0.2 setosa    1.4  NA  
 2          4.9         3            1.4         0.2 setosa    1.3   1.4
 3          4.7         3.2          1.3         0.2 setosa    1.5   1.4
 4          4.6         3.1          1.5         0.2 setosa    1.4   1.3
 5          5           3.6          1.4         0.2 setosa    1.7   1.5
 6          5.4         3.9          1.7         0.4 setosa    1.4   1.4
 7          4.6         3.4          1.4         0.3 setosa    1.5   1.7
 8          5           3.4          1.5         0.2 setosa    1.4   1.4
 9          4.4         2.9          1.4         0.2 setosa    1.5   1.5
10          4.9         3.1          1.5         0.1 setosa    1.5   1.4
# ... with 140 more rows

For more info on how to use tidyverse functions within your custom functions see here

Upvotes: 5

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