How do I mutate column based on value returned from custom function?

Question

I'm trying to write a function that can return the artist's genre on Spotify based on their Spotify ID. This is with the spotifyr package. Consider the following dataframe artists:

# A tibble: 6 x 2
  id                     name           
  <chr>                  <chr>          
1 6ltzsmQQbmdoHHbLZ4ZN25 Lord Huron     
2 35U9lQaRWSQISxQAB94Meo America        
3 22WZ7M8sxp5THdruNY3gXt The Doors      
4 2MSlGNpwXDScUdspOK6TS7 Home Free      
5 4GITZM5LCR2KcdlgEOrNLD The Foundations
6 2jgPkn6LuUazBoBk6vvjh5 The Zombies

My function, get_genre is defined as follows:

get_genre <- function(x) {
    artist <- get_artist(x)
    artist <- enframe(artist)
    genre <- artist[3,2]
    genre <- as.data.frame(genre)
    return(genre)
}

For example, for the id 6ltzsmQQbmdoHHbLZ4ZN25 , it returns:

c("indie folk", "indie pop", "stomp and holler")

I would like to use it on each row of the artists dataframe, for each artist id. I tried doing this:

artists <- artists %>% mutate(genre = get_genre(id))

But this gives the following error:

Error: Problem with `mutate()` input `genre`. x length(url) == 1 is not TRUE i Input `genre` is `get_genre(id)`.

How can I mutate a new column genre whose values are returned by my function for each artist id?

DPUT:

structure(list(id = c("6ltzsmQQbmdoHHbLZ4ZN25", "35U9lQaRWSQISxQAB94Meo", 
"22WZ7M8sxp5THdruNY3gXt", "2MSlGNpwXDScUdspOK6TS7", "4GITZM5LCR2KcdlgEOrNLD", 
"2jgPkn6LuUazBoBk6vvjh5"), name = c("Lord Huron", "America", 
"The Doors", "Home Free", "The Foundations", "The Zombies")), row.names = c(NA, 
-6L), class = c("tbl_df", "tbl", "data.frame"))

Ronak Shah · Accepted Answer · 2021-04-04 09:34:38Z

1

The function is not vectorized, use rowwise. Also since one id can return more than 1 genre you can use toString to combine everything in one comma separated string.

library(dplyr)

artists <- artists %>% rowwise() %>% mutate(genre = toString(get_genre(id)))

answered Apr 4, 2021 at 9:34

Ronak Shah

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2 Comments

Aman Over a year ago

Thank you! I need to read up rowwise and vectorized functions, I think I'm still unclear on the distinction.

Alvaro Morales Over a year ago

Vectorized functions are faster than rowwise, because the first one apply a function in every element of a vector or column "at the same time". rowwise apply the function at one row at a time. Btw, @Ronak Shah, please, can you provide a vectorized version of this?

akrun · Accepted Answer · 2021-04-04 17:05:24Z

0

We can use map

library(purrr)
library(dplyr)
artists <- artists %>%
              mutate(genre = map_chr(id, ~ toString(get_genre(.x))))

answered Apr 4, 2021 at 17:05

akrun

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