timbr
Forest/Tree Data Frames
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.
timbr
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.
Installation
You can install the development version of timbr from GitHub with:
# the released version from CRAN:
install.packages("timbr")
# the development version from GitHub:
# install.packages("devtools")
devtools::install_github("UchidaMizuki/timbr")
Main Functions
The main functions provided by timbr are as follows,
children()climb()leaves()traverse()rbind()
tidyverse methods
timbr provides some tidyverse methods as follows,
mutate()summarise()select()andrelocate()rows_update()androws_patch()
Examples
library(timbr)
library(dplyr)
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_sum <- fr |>
summarise(value = sum(value)) |>
summarise(value = sum(value))
fr
#> # A forest: 8 nodes and 1 feature
#> # Groups: key1, key2 [4]
#> # Trees:
#> # key3 [8]
#> key1 key2 . 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
#> # A forest: 14 nodes and 1 feature
#> # Trees:
#> # key1 [2]
#> # └─key2 [4]
#> # └─key3 [8]
#> . value
#> <node> <int>
#> 1 <key1> a 10
#> 2 <key1> b 26
children(fr_sum)
#> # A forest: 12 nodes and 1 feature
#> # Groups: key1 [2]
#> # Trees:
#> # key2 [4]
#> # └─key3 [8]
#> key1 . 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
#> # Trees:
#> # key3 [8]
#> . 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
fr1 <- tidyr::expand_grid(
key1 = letters[1:2],
key2_1 = letters[1:2],
key3_1 = letters[1:2]
) |>
mutate(value = row_number()) |>
forest_by(key1, key2_1, key3_1) |>
summarise(value = sum(value))
fr2 <- tidyr::expand_grid(
key1 = letters[1:2],
key2_2 = letters[1:2],
key3_2 = letters[1:2]
) |>
mutate(value = row_number()) |>
forest_by(key1, key2_2, key3_2) |>
summarise(value = sum(value))
fr <- rbind(fr1, fr2)
fr_sum <- fr |>
summarise(value = sum(value))
fr
#> # A forest: 24 nodes and 1 feature
#> # Groups: key1 [2]
#> # Trees:
#> # key2_1 [4]
#> # └─key3_1 [8]
#> # key2_2 [4]
#> # └─key3_2 [8]
#> key1 . value
#> <chr> <node> <int>
#> 1 a <key2_1> a 3
#> 2 a <key2_1> b 7
#> 3 b <key2_1> a 11
#> 4 b <key2_1> b 15
#> 5 a <key2_2> a 3
#> 6 a <key2_2> b 7
#> 7 b <key2_2> a 11
#> 8 b <key2_2> b 15
fr_sum
#> # A forest: 26 nodes and 1 feature
#> # Trees:
#> # key1 [2]
#> # ├─key2_1 [4]
#> # │ └─key3_1 [8]
#> # └─key2_2 [4]
#> # └─key3_2 [8]
#> . value
#> <node> <int>
#> 1 <key1> a 20
#> 2 <key1> b 52
traverse(fr_sum, function(x, children) {
x$value <- prod(children$value)
x
})
#> # A forest: 26 nodes and 1 feature
#> # Trees:
#> # key1 [2]
#> # ├─key2_1 [4]
#> # │ └─key3_1 [8]
#> # └─key2_2 [4]
#> # └─key3_2 [8]
#> . value
#> <node> <int>
#> 1 <key1> a 576
#> 2 <key1> b 2822400