R dplyr: Write list output to dataframe

Question

Suppose I have the following function

SlowFunction = function(vector){
  return(list(
    mean =mean(vector),
    sd  = sd(vector)
    ))
  }

And I would like to use dplyr:summarise to write the results to a dataframe:

iris %>% 
  dplyr::group_by(Species) %>% 
  dplyr::summarise(
    mean = SlowFunction(Sepal.Length)$mean,
    sd   = SlowFunction(Sepal.Length)$sd
    )

Does anyone have a suggestion how I can do this by calling "SlowFunction" once instead of twice? (In my code "SlowFunction" is a slow function that I have to call many times.) Without splitting "SlowFunction" in two parts of course. So actually I would like to somehow fill multiple columns of a dataframe in one statement.

Will this help https://stackoverflow.com/a/52413631/786542? – Tung Apr 11 '19 at 01:56 — Tung, Apr 11 '19 at 01:56

Ronak Shah · Answer 1 · 2019-04-11T02:27:32.450

Without changing your current SlowFunction one way is to use do

library(dplyr)

iris %>% 
   group_by(Species) %>% 
   do(data.frame(SlowFunction(.$Sepal.Length)))

#  Species     mean    sd
#  <fct>      <dbl> <dbl>
#1 setosa      5.01 0.352
#2 versicolor  5.94 0.516
#3 virginica   6.59 0.636

Or with group_split + purrr::map_dfr

bind_cols(Species = unique(iris$Species), iris %>%
     group_split(Species) %>%
     map_dfr(~SlowFunction(.$Sepal.Length)))

score 3 · Accepted Answer · answered Apr 11 '19 at 02:07

3

An option is to use to store the output of SlowFunction in a list column of data.frames and then to use unnest

iris %>%
    group_by(Species) %>%
    summarise(res = list(as.data.frame(SlowFunction(Sepal.Length)))) %>%
    unnest()
## A tibble: 3 x 3
#  Species     mean    sd
#  <fct>      <dbl> <dbl>
#1 setosa      5.01 0.352
#2 versicolor  5.94 0.516
#3 virginica   6.59 0.636

answered Apr 11 '19 at 02:07

Maurits Evers

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Thanks, I've compared the answers and this one is in my case by far the fastest. It is 2x faster than using "do" and 2.5x faster than using group_map! – Frank Apr 12 '19 at 23:36

score 3 · Answer 3 · answered Apr 11 '19 at 02:18

We can use group_map if you are using dplyr 0.8.0 or later. The output from SlowFunction needs to be converted to a data frame.

library(dplyr)

iris %>% 
  group_by(Species) %>% 
  group_map(~SlowFunction(.x$Sepal.Length) %>% as.data.frame())
# # A tibble: 3 x 3
# # Groups:   Species [3]
#   Species     mean    sd
#   <fct>      <dbl> <dbl>
# 1 setosa      5.01 0.352
# 2 versicolor  5.94 0.516
# 3 virginica   6.59 0.636

score 3 · Answer 4 · answered Apr 11 '19 at 02:44

We can change the SlowFunction to return a tibble and

SlowFunction = function(vector){
  tibble(
     mean =mean(vector),
      sd  = sd(vector)
     )
   }

and then unnest the summarise output in a list

iris %>% 
    group_by(Species) %>% 
    summarise(out = list(SlowFunction(Sepal.Length))) %>%
    unnest
# A tibble: 3 x 3
#  Species     mean    sd
#  <fct>      <dbl> <dbl>
#1 setosa      5.01 0.352
#2 versicolor  5.94 0.516
#3 virginica   6.59 0.636

R dplyr: Write list output to dataframe

4 Answers4