timbr provides data frames for forest (or tree) data structures. You can create forest data structures from data frames and process them based on their hierarchies.
You can install the development version of timbr from GitHub with:
timbr provides some tidyverse methods as follows,
mutate()summarise()select() and relocate()rows_update() and rows_patch()modify()fr <- tidyr::expand_grid(key1 = letters[1:2],
key2 = letters[1:2],
key3 = letters[1:2]) %>%
mutate(value = row_number()) %>%
forest_by(key1, key2, key3)
fr
#> # A forest: 8 nodes and 1 feature
#> # Groups: key1, key2 [4]
#> # Roots: key3 [8]
#> key1 key2 node value
#> <chr> <chr> <node> <int>
#> 1 a a <key3> a 1
#> 2 a a <key3> b 2
#> 3 a b <key3> a 3
#> 4 a b <key3> b 4
#> 5 b a <key3> a 5
#> 6 b a <key3> b 6
#> 7 b b <key3> a 7
#> 8 b b <key3> b 8
fr_sum <- fr %>%
summarise(value = sum(value)) %>%
summarise(value = sum(value))
fr_sum
#> # A forest: 14 nodes and 1 feature
#> # Roots: key1 [2]
#> node value
#> <node> <int>
#> 1 <key1> a 10
#> 2 <key1> b 26
children(fr_sum)
#> # A forest: 12 nodes and 1 feature
#> # Groups: key1 [2]
#> # Roots: key2 [4]
#> key1 node value
#> <chr> <node> <int>
#> 1 a <key2> a 3
#> 2 a <key2> b 7
#> 3 b <key2> a 11
#> 4 b <key2> b 15
fr_sum %>%
climb(key3)
#> # A forest: 8 nodes and 1 feature
#> # Roots: key3 [8]
#> node value
#> <node> <int>
#> 1 <key3> a 1
#> 2 <key3> b 2
#> 3 <key3> a 3
#> 4 <key3> b 4
#> 5 <key3> a 5
#> 6 <key3> b 6
#> 7 <key3> a 7
#> 8 <key3> b 8