How to get names inside enframe - r

Question

I want to get summary of multiple columns in a data frame group-wise. I'm using dplyr::group_by and dplyr::summarise_if to get the results, but I'm unable to get name the columns according to the names of the columns which are being summarised.
The following example illustrates this:
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(tibble)
library(tidyr)
iris %>%
group_by(Species) %>%
summarise_if(.predicate = is.numeric,
.funs = ~ list(enframe(x = summary(object = .)))) %>%
unnest() %>%
select(which(x = !duplicated(x = lapply(X = .,
FUN = summary))))
#> # A tibble: 18 x 6
#> Species name value value1 value2 value3
#> <fct> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 setosa Min. 4.3 2.3 1 0.1
#> 2 setosa 1st Qu. 4.8 3.2 1.4 0.2
#> 3 setosa Median 5 3.4 1.5 0.2
#> 4 setosa Mean 5.01 3.43 1.46 0.246
#> 5 setosa 3rd Qu. 5.2 3.68 1.58 0.3
#> 6 setosa Max. 5.8 4.4 1.9 0.6
#> 7 versicolor Min. 4.9 2 3 1
#> 8 versicolor 1st Qu. 5.6 2.52 4 1.2
#> 9 versicolor Median 5.9 2.8 4.35 1.3
#> 10 versicolor Mean 5.94 2.77 4.26 1.33
#> 11 versicolor 3rd Qu. 6.3 3 4.6 1.5
#> 12 versicolor Max. 7 3.4 5.1 1.8
#> 13 virginica Min. 4.9 2.2 4.5 1.4
#> 14 virginica 1st Qu. 6.22 2.8 5.1 1.8
#> 15 virginica Median 6.5 3 5.55 2
#> 16 virginica Mean 6.59 2.97 5.55 2.03
#> 17 virginica 3rd Qu. 6.9 3.18 5.88 2.3
#> 18 virginica Max. 7.9 3.8 6.9 2.5
Created on 2019-05-15 by the reprex package (v0.2.1)
As you can see, the columns are named value, value1, etc, whereas I'd like them to be Sepal.Length, Sepal.Width, etc. After I get this result, of course it is possible to name the columns manually, but I guess there's a better way to do it using the value argument of tibble::enframe.
As an alternative, I'm currently using the following method. It requires a fake data, which is also not preferable.
iris %>%
group_by(Species) %>%
summarise_if(.predicate = is.numeric,
.funs = ~ list(summary(object = .))) %>%
unnest() %>%
group_by(Species) %>%
mutate(Statistic = names(x = summary(object = rnorm(n = 1)))) %>%
ungroup() %>%
select(Species, Statistic, everything())
Any help will be appreciated.

Answer 1

Might be this way? I didn't sort it according to the name within each Species, but I think it isn't important.
library(tidyverse)
iris %>%
group_by(Species) %>%
summarise_if(is.numeric, . ~ list(enframe(summary(.)))) %>%
gather('key', 'value', -Species) %>%
unnest() %>%
spread(key, value)
## A tibble: 18 x 6
# Species name Petal.Length Petal.Width Sepal.Length Sepal.Width
# <fct> <chr> <dbl> <dbl> <dbl> <dbl>
# 1 setosa 1st Qu. 1.4 0.2 4.8 3.2
# 2 setosa 3rd Qu. 1.58 0.3 5.2 3.68
# 3 setosa Max. 1.9 0.6 5.8 4.4
# 4 setosa Mean 1.46 0.246 5.01 3.43
# 5 setosa Median 1.5 0.2 5 3.4
# 6 setosa Min. 1 0.1 4.3 2.3
# 7 versicolor 1st Qu. 4 1.2 5.6 2.52
# 8 versicolor 3rd Qu. 4.6 1.5 6.3 3
# 9 versicolor Max. 5.1 1.8 7 3.4
#10 versicolor Mean 4.26 1.33 5.94 2.77
#11 versicolor Median 4.35 1.3 5.9 2.8
#12 versicolor Min. 3 1 4.9 2
#13 virginica 1st Qu. 5.1 1.8 6.22 2.8
#14 virginica 3rd Qu. 5.88 2.3 6.9 3.18
#15 virginica Max. 6.9 2.5 7.9 3.8
#16 virginica Mean 5.55 2.03 6.59 2.97
#17 virginica Median 5.55 2 6.5 3
#18 virginica Min. 4.5 1.4 4.9 2.2