README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# timbr

<!-- badges: start -->
[![CRAN status](https://www.r-pkg.org/badges/version/timbr)](https://CRAN.R-project.org/package=timbr)
[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
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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](https://github.com/) with:

``` r
# 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()` and `relocate()`
- `rows_update()` and `rows_patch()`

## Examples

```{r,warning=FALSE,message=FALSE}
library(timbr)
library(dplyr)
```

```{r}
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
fr_sum
children(fr_sum)
fr_sum |> 
  climb(key3)
```

```{r}
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
fr_sum
traverse(fr_sum,
         function(x, children) {
           x$value <- prod(children$value)
           x
         })
```