aggregate_key() produces aggregations of single leaf nodes

This is not necessarily a bug, just something to be aware of. An option to produce unbalanced hierarchies for redundant aggregations may be useful.

library(fabletools)
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
tsibble::tourism %>% 
  aggregate_key(Purpose * (State / Region), Trips = sum(Trips)) %>% 
  filter(Purpose == "Business", State == "ACT")
#> # A tsibble: 160 x 5 [1Q]
#> # Key:       Purpose, State, Region [2]
#>    Quarter Purpose  State Region       Trips
#>      <qtr> <chr>    <chr> <chr>        <dbl>
#>  1 1998 Q1 Business ACT   <aggregated> 150. 
#>  2 1998 Q2 Business ACT   <aggregated>  99.9
#>  3 1998 Q3 Business ACT   <aggregated> 130. 
#>  4 1998 Q4 Business ACT   <aggregated> 102. 
#>  5 1999 Q1 Business ACT   <aggregated>  95.5
#>  6 1999 Q2 Business ACT   <aggregated> 229. 
#>  7 1999 Q3 Business ACT   <aggregated> 109. 
#>  8 1999 Q4 Business ACT   <aggregated> 159. 
#>  9 2000 Q1 Business ACT   <aggregated> 105. 
#> 10 2000 Q2 Business ACT   <aggregated> 202. 
#> # … with 150 more rows

^{Created on 2020-06-19 by the reprex package (v0.3.0)}

Start by running the R example using tsibble::tourism and aggregate_key(Purpose * (State / Region), Trips = sum(Trips)) to reproduce the single-leaf aggregation. Read the aggregate_key() entry point and clarify the desired option and expected unbalanced hierarchy before defining what a complete change would look like.