Using dplyr summarise() for specific columns within purrr map() with grouped data

user_12908375 0
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I have a problem I'm trying to solve, and I can't seem to find a succinct solution. There are a few similar questions on SO, but nothing that quite fits.

Take some sample data:

library(dplyr)

dat <- tibble(
  group1 = factor(sample(c("one", "two"), 10, replace = T)),
  group2 = factor(sample(c("alpha", "beta"), 10, replace = T)),
  var1 = rnorm(10, 20, 2),
  var2 = rnorm(10, 20, 2),
  var3 = rnorm(10, 20, 2),
  other1 = sample(c("a", "b", "c"), 10, replace = T),
  other2 = sample(c("a", "b", "c"), 10, replace = T),
)

I would like to summarise just the numeric variables (i.e. ignoring other1 and other2), but have the output grouped by group1 and group2.

I have tried something like this, but it returns an error as it attempts to apply my summarise() functions to the grouping variables too.

dat %>%
  group_by(group1, group2) %>%
  select(where(is.numeric)) %>%
  map(~ .x %>%
        filter(!is.na(.x)) %>%
        summarise(mean = mean(.x),
                  sd = sd(.x),
                  median = median(.x),
                  q1 = quantile(.x, p = .25),
                  q3 = quantile(.x, p = .75))
  )

My expected output would be something like

  group1  group2  mean    sd    median   q1     q3
  <fct> <fct>     <dbl>  <dbl>   <dbl>  <dbl>  <dbl>
1 one   alpha       ?      ?       ?      ?      ?
2 one   beta        ?      ?       ?      ?      ?
3 two   alpha       ?      ?       ?      ?      ?
4 two   beta        ?      ?       ?      ?      ?

Any solutions would be greatly appreciated.

Thanks, Sam

purrr dplyr r
2 Answers

Try:

dat %>% group_by(group1,group2) %>%
        summarize(across(is.numeric,c(sd = sd,
                                      mean = mean, 
                                      median =median,
                                      q1 = function(x) quantile(x,.25),
                                      q3 = function(x) quantile(x,.75))))

group1 group2 var1_sd var1_mean var1_median var1_q1 var1_q3 var2_sd var2_mean var2_median var2_q1 var2_q3 var3_sd
  <fct>  <fct>    <dbl>     <dbl>       <dbl>   <dbl>   <dbl>   <dbl>     <dbl>       <dbl>   <dbl>   <dbl>   <dbl>
1 one    alpha    4.06       20.6        19.3    18.3    22.2   1.12       17.9        17.3    17.2    18.2  1.09  
2 one    beta     0.726      18.7        18.7    18.4    18.9   0.348      18.8        18.8    18.7    18.9  0.604 
3 two    alpha    1.31       19.9        20.0    19.3    20.6   1.10       17.8        18.3    17.4    18.5  0.624 
4 two    beta     0.777      21.2        21.2    21.0    21.5   1.13       19.6        19.6    19.2    20.0  0.0161
user_135133280

You can also pass the columns to the functions in summarise:

dat %>%
  group_by(group1, group2) %>%
  summarise(mean = mean(var1:var3),
            sd = sd(var1:var3),
            median = median(var1:var3),
            q1 = quantile(var1:var3, p = .25),
            q3 = quantile(var1:var3, p = .75))
dat
# A tibble: 4 x 7
# Groups:   group1 [2]
#   group1 group2  mean     sd median    q1    q3
#   <fct>  <fct>  <dbl>  <dbl>  <dbl> <dbl> <dbl>
# 1 one    alpha   19.1  0.707   19.1  18.8  19.3
# 2 one    beta    17.5  1.29    17.5  16.8  18.3
# 3 two    alpha   17.1 NA       17.1  17.1  17.1
# 4 two    beta    19.9 NA       19.9  19.9  19.9
user_47186220
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