Create table with nested header from pre-summarized data - r

Question

How do I create a nested table from a data.frame, which have already been summarized? By nested I mean that the table has headers and subheaders.
My input data looks like this:
library(ggplot2)
library(reshape2)
df <- ggplot2::diamonds
count(df, cut,color) %>% mutate(
n = n,
pct = round(n / sum(n),2) ) %>% reshape2::melt() -> df2
head(df2 )
> head(df2 )
cut color variable value
1 Fair D n 163
2 Fair E n 224
3 Fair F n 312
4 Fair G n 314
5 Fair H n 303
6 Fair I n 175
I would like to have something this:
Color
D E F G H I J
cut n pct n pct n pct n pct n pct n pct n pct
Fair 163 0.10 224 0.14 312 0.19 314 0.20 303 0.19 175 0.11 119 0.07
Good 662 0.13 933 0.19 909 0.19 871 0.18 702 0.14 522 0.11 307 0.06
Very Good 1513 0.13 2400 0.20 2164 0.18 2299 0.19 1824 0.15 1204 0.10 678 0.06
Premium 1603 0.12 2337 0.17 2331 0.17 2924 0.21 2360 0.17 1428 0.10 808 0.06
Ideal 2834 0.13 3903 0.18 3826 0.18 4884 0.23 3115 0.14 2093 0.10 896 0.04
Below is an example of the closest I can get. The problem with this table below is that there is only one header. I would like 3 rows/headers: One which says the name of the variable: Color, one which lists the individual categories inside color, and one which lists type of summary (coming from df2$variable):
reshape2::dcast(df2, cut ~ color + variable , value.var = c("value") )
cut D_n D_pct E_n E_pct F_n F_pct G_n G_pct H_n H_pct I_n I_pct J_n J_pct
1 Fair 163 0.10 224 0.14 312 0.19 314 0.20 303 0.19 175 0.11 119 0.07
2 Good 662 0.13 933 0.19 909 0.19 871 0.18 702 0.14 522 0.11 307 0.06
3 Very Good 1513 0.13 2400 0.20 2164 0.18 2299 0.19 1824 0.15 1204 0.10 678 0.06
4 Premium 1603 0.12 2337 0.17 2331 0.17 2924 0.21 2360 0.17 1428 0.10 808 0.06
5 Ideal 2834 0.13 3903 0.18 3826 0.18 4884 0.23 3115 0.14 2093 0.10 896 0.04
I hope there is some function/package which can do this. I think it should be possible because the packages etable and tables, and the function ftable, can create the output I want, but not for pre-summarized data.
This link does what I need (I think), but I only have access to CRAN-packages on the server I use.
https://www.r-statistics.com/2012/01/printing-nested-tables-in-r-bridging-between-the-reshape-and-tables-packages/

Answer 1

Solution based on comments. Thanks!
# data
library(tidyr)
library(dplyr)
library(ggplot2)
library(reshape2)
df <- ggplot2::diamonds
count(df, cut,color) %>% mutate(
n = n,
pct = round(n / sum(n),2) ) %>% reshape2::melt() -> df2
head(df2 )
# Solution
spread( data = df2, key = variable, value = value ) -> df2_spread
tabular( Heading() * cut ~ color * (n + pct) * Heading() * (identity), data =df2_spread )