as.data.frame.Node {data.tree}

Convert a data.tree structure to a data.frame

Description

If a node field contains data of length > 1, then that is converted into a string in the data.frame.

Usage

## S3 method for class 'Node'
as.data.frame(
  x,
  row.names = NULL,
  optional = FALSE,
  ...,
  traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"),
  pruneFun = NULL,
  filterFun = NULL,
  format = FALSE,
  inheritFromAncestors = FALSE
)

ToDataFrameTree(x, ..., pruneFun = NULL)

ToDataFrameTable(x, ..., pruneFun = NULL)

ToDataFrameNetwork(
  x,
  ...,
  direction = c("climb", "descend"),
  pruneFun = NULL,
  format = FALSE,
  inheritFromAncestors = FALSE
)

ToDataFrameTypeCol(x, ..., type = "level", prefix = type, pruneFun = NULL)

Arguments

x

The root Node of the tree or sub-tree to be convert to a data.frame

row.names

NULL or a character vector giving the row names for the data frame. Missing values are not allowed.

optional

logical. If TRUE, setting row names and converting column names (to syntactic names: see make.names) is optional.

...

the attributes to be added as columns of the data.frame. See Get for details. If a specific Node does not contain the attribute, NA is added to the data.frame.

traversal

any of 'pre-order' (the default), 'post-order', 'in-order', 'level', or 'ancestor'. See Traverse for details.

pruneFun

allows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.

filterFun

a function taking a Node as an argument. See Traverse for details.

format

if FALSE (the default), then no formatting will be applied. If TRUE, then the first formatter (if any) along the ancestor path is used for formatting.

inheritFromAncestors

if FALSE, and if the attribute is a field or a method, then only a Node itself is searched for the field/method. If TRUE, and if the Node does not contain the attribute, then ancestors are also searched.

direction

when converting to a network, should the edges point from root to children ("climb") or from child to parent ("descend")?

type

when converting type columns, the type is the discriminator, i.e. an attribute (e.g. field name) of each node

prefix

when converting type columns, the prefix used for the column names. Can be NULL to omit prefixes.

Value

ToDataFrameTree: a data.frame, where each row represents a Node in the tree or sub-tree spanned by x, possibly pruned according to pruneFun.

ToDataFrameTable: a data.frame, where each row represents a leaf Node in the tree or sub-tree spanned by x, possibly pruned according to pruneFun.

ToDataFrameNetwork: a data.frame, where each row represents a Node in the tree or sub-tree spanned by x, possibly pruned according to pruneFun. The first column is called 'from', while the second is called 'to', describing the parent to child edge (for direction "climb") or the child to parent edge (for direction "descend"). If AreNamesUnique is TRUE, then the Network is based on the Node$name, otherwise on the Node$pathString

ToDataFrameTypeCol: a data.frame in table format (i.e. where each row represents a leaf in the tree or sub-tree spanned by x), possibly pruned according to pruneFun. In addition to ..., each distinct type is output to a column.

Examples

data(acme)
acme$attributesAll
as.data.frame(acme, row.names = NULL, optional = FALSE, "cost", "p")

ToDataFrameTree(acme, "cost", "p")
ToDataFrameNetwork(acme, "cost", "p", direction = "climb")
ToDataFrameTable(acme, "cost", "p")
ToDataFrameTypeCol(acme)

#use the pruneFun:
acme$Do(function(x) x$totalCost <- Aggregate(x, "cost", sum), traversal = "post-order")
ToDataFrameTree(acme, "totalCost", pruneFun = function(x) x$totalCost > 300000)

#inherit
acme$Set(floor = c(1, 2, 3), filterFun = function(x) x$level == 2)
as.data.frame(acme, row.names = NULL, optional = FALSE, "floor", inheritFromAncestors = FALSE)
as.data.frame(acme, row.names = NULL, optional = FALSE, "floor", inheritFromAncestors = TRUE)

#using a function as an attribute:
acme$Accounting$Head <- "Mrs. Numright"
acme$Research$Head <- "Mr. Stein"
acme$IT$Head <- "Mr. Squarehead"
ToDataFrameTable(acme, department = function(x) x$parent$name, "name", "Head", "cost")

#complex TypeCol
acme$IT$Outsource$AddChild("India")
acme$IT$Outsource$AddChild("Poland")
acme$Set(type = c('company', 'department', 'project', 'project', 'department',
                  'project', 'project', 'department', 'program', 'project',
                  'project', 'project', 'project'
                  )
        )
print(acme, 'type')
ToDataFrameTypeCol(acme, type = 'type')