list-processing: List Processing

In collapse: Advanced and Fast Data Transformation

List Processing

Description

collapse provides the following set of functions to efficiently work with lists of R objects:

• Search and Identification

  • is_unlistable checks whether a (nested) list is composed of atomic objects in all final nodes, and thus unlistable to an atomic vector using unlist.

  • ldepth determines the level of nesting of the list (i.e. the maximum number of nodes of the list-tree).

  • has_elem searches elements in a list using element names, regular expressions applied to element names, or a function applied to the elements, and returns TRUE if any matches were found.

• Subsetting

  • atomic_elem examines the top-level of a list and returns a sublist with the atomic elements. Conversely list_elem returns the sublist of elements which are themselves lists or list-like objects.

  • reg_elem and irreg_elem are recursive versions of the former. reg_elem extracts the 'regular' part of the list-tree leading to atomic elements in the final nodes, while irreg_elem extracts the 'irregular' part of the list tree leading to non-atomic elements in the final nodes. (Tip: try calling both on an lm object). Naturally for all lists l, is_unlistable(reg_elem(l)) evaluates to TRUE.

  • get_elem extracts elements from a list using element names, regular expressions applied to element names, a function applied to the elements, or element-indices used to subset the lowest-level sub-lists. by default the result is presented as a simplified list containing all matching elements. With the keep.tree option however get_elem can also be used to subset lists i.e. maintain the full tree but cut off non-matching branches.

• Splitting and Transposition

  • rsplit recursively splits a vector or data frame into subsets according to combinations of (multiple) vectors / factors - by default returning a (nested) list. If flatten = TRUE, the list is flattened yielding the same result as split. rsplit is also faster than split, particularly for data frames.

  • t_list efficiently transposes nested lists of lists, such as those obtained from splitting a data frame by multiple variables using rsplit.

• Apply Functions

  • rapply2d is a recursive version of lapply with two key differences to rapply to apply a function to nested lists of data frames or other list-based objects.

• Unlisting / Row-Binding

  • unlist2d efficiently unlists unlistable lists in 2-dimensions and creates a data frame (or data.table) representation of the list. This is done by recursively flattening and row-binding R objects in the list while creating identifier columns for each level of the list-tree and (optionally) saving the row-names of the objects in a separate column. unlist2d can thus also be understood as a recursive generalization of do.call(rbind, l), for lists of vectors, data frames, arrays or heterogeneous objects. A simpler version for non-recursive row-binding lists of lists / data.frames, is also available by rowbind.

Table of Functions

Function		Description
is_unlistable		Checks if list is unlistable
ldepth		Level of nesting / maximum depth of list-tree
has_elem		Checks if list contains a certain element
get_elem		Subset list / extract certain elements
atomic_elem		Top-level subset atomic elements
list_elem		Top-level subset list/list-like elements
reg_elem		Recursive version of atomic_elem: Subset / extract 'regular' part of list
irreg_elem		Subset / extract non-regular part of list
rsplit		Recursively split vectors or data frames / lists
t_list		Transpose lists of lists
rapply2d		Recursively apply functions to lists of data objects
unlist2d		Recursively unlist/row-bind lists of data objects in 2D, to data frame or data.table
rowbind		Non-recursive binding of lists of lists / data.frames.

See Also

Collapse Overview

collapse documentation built on Nov. 3, 2024, 9:08 a.m.