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The rlist package

Description

rlist is a set of tools for working with list objects. Its goalis to make it easier to work with lists by providing a wide rangeof functions that operate on non-tabular data stored in them.

The package provides a set of functions for data manipulation withlist objects, including mapping, filtering, grouping, sorting,updating, searching, and other useful functions. Most functionsare designed to be pipeline friendly so that data processing withlists can be chained.

rlist Tutorial (https://renkun-ken.github.io/rlist-tutorial/) is a complete guide to rlist.

Convert an object to evaluating environment for list elements Users should notdirectly use this function

Description

Convert an object to evaluating environment for list elements Users should notdirectly use this function

Usage

.evalwith(x)

Arguments

Create aList environment that wraps givendata andmost list functions are defined for chainable operations.

Description

Create aList environment that wraps givendata andmost list functions are defined for chainable operations.

Usage

List(data = list())

Arguments

Details

Most list functions are defined inList environment.In addition to these functions,call(fun,...) callsexternal functionfun with additional parameters specifies in....

To extract the data from Listx, callx$data or simplyx[].

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))m <- List(x)m$filter(type=='B')$  map(score$c1) []m$group(type)$  map(g ~ List(g)$      map(score)$      call(unlist)$      call(mean) []) []# Subsetting, extracting, and assigningp <- List(list(a=1,b=2))p['a']p[['a']]p$a <- 2p['b'] <- NULLp[['a']] <- 3

create an environment for args

Description

create an environment for args

Usage

args_env(..., parent = parent.frame())

Arguments

create a list for args

Description

create a list for args

Usage

args_list(...)

Arguments

Evaluate a function with a modified default values

Description

Evaluate a function with a modified default values

Usage

callwith(fun, args, dots = list(), keep.null = FALSE, envir = parent.frame())

Arguments

Test if a vector contains certain values

Description

Test if a vector contains certain values

Usage

contains(table, x)

Arguments

Substitute ...

Description

Substitute ...

Usage

dots(...)

Arguments

Get the names of an object

Description

Get the names of an object

Usage

getnames(x, def = NULL)

Arguments

Details

This function is used in vectorization when the names of an objectis to be supplied.NULL value will break the vectorization whilesettingdef = character(1L) makes the names vectorizable.

Check if an object is empty (has length 0)

Description

Check if an object is empty (has length 0)

Usage

is.empty(x)

Arguments

Details

ANULL value, zero-length vector or list have length zero,which is called empty.

Examine if a condition is true for all elements of a list

Description

Examine if a condition is true for all elements of a list

Usage

list.all(.data, cond, na.rm = FALSE)

Arguments

Value

TRUE ifcond is evaluated to beTRUEfor all elements in.data.

See Also

list.any

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.all(x, type=='B')list.all(x, mean(unlist(score))>=6)list.all(x, score$c2 > 8 || score$c3 > 5, na.rm = TRUE)list.all(x, score$c2 > 8 || score$c3 > 5, na.rm = FALSE)

Examine if a condition is true for at least one list element

Description

Examine if a condition is true for at least one list element

Usage

list.any(.data, cond, na.rm = FALSE)

Arguments

Value

TRUE ifcond is evaluated to beTRUEfor any element in.data.

See Also

list.all

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.any(x,type=='B')list.any(x,mean(unlist(score))>=6)list.any(x, score$c2 > 8 || score$c3 > 5, na.rm = TRUE)list.any(x, score$c2 > 8 || score$c3 > 5, na.rm = FALSE)

Append elements to a list

Description

Append elements to a list

Usage

list.append(.data, ...)

Arguments

See Also

list.prepend,list.insert

Examples

## Not run: x <- list(a=1,b=2,c=3)list.append(x,d=4,e=5)list.append(x,d=4,f=c(2,3))## End(Not run)

Apply a function to each list element (lapply)

Description

Apply a function to each list element (lapply)

Usage

list.apply(.data, .fun, ...)

Arguments

Get all unique cases of a list field by expression

Description

Get all unique cases of a list field by expression

Usage

list.cases(.data, expr, simplify = TRUE, sorted = TRUE)

Arguments

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.cases(x,type)list.cases(x,mean(unlist(score)))foo <- list(x = LETTERS[1:3], y = LETTERS[3:5])list.cases(foo)

Bind all list elements by column

Description

The function binds all list elements by column. Each element of the list is expectedto be an atomic vector,data.frame, ordata.table of the same length.If list elements are also lists, the binding will flatten the lists and may produceundesired results.

Usage

list.cbind(.data)

Arguments

See Also

list.cbind,list.stack

Examples

x <- list(data.frame(i=1:5,x=rnorm(5)),   data.frame(y=rnorm(5),z=rnorm(5)))list.cbind(x)

Classify list elments into unique but non-exclusive cases

Description

In non-tabular data, a certain field may take multiple values in acollection non-exclusively. To classify these elements into differentcases, this function detects all possible cases and for each case allelements are examined whether to belong to that case.

Usage

list.class(.data, ..., sorted = TRUE)

Arguments

Value

a list of possible cases each of which contains elements belonging tothe case non-exclusively.

Examples

x <-  list(    p1=list(name='Ken',age=24,      interest=c('reading','music','movies'),      lang=list(r=2,csharp=4,python=3)),    p2=list(name='James',age=25,      interest=c('sports','music'),      lang=list(r=3,java=2,cpp=5)),    p3=list(name='Penny',age=24,      interest=c('movies','reading'),      lang=list(r=1,cpp=4,python=2)))list.class(x,interest)list.class(x,names(lang))

Clean a list by a function

Description

This function removes all elements evaluated to beTRUE by an indicator function. The removal can be recursiveso that the resulted list surely does not include such elements inany level.

Usage

list.clean(.data, fun = is.null, recursive = FALSE)

Arguments

Details

Raw data is usually not completely ready for analysis, and needs tobe cleaned up to certain standards. For example, some data operationsrequire that the input does not includeNULL values in anylevel, thereforefun = "is.null" andrecursive = TRUEcan be useful to clean out allNULL values in a list at anylevel.

Sometimes, not onlyNULL values are undesired,empty vectors or lists are also unwanted. In this case,fun = function(x) length(x) == 0L can be useful to removeall empty elements of zero length. This works becauselength(NULL) == 0L,length(list()) == 0L andlength(numeric()) == 0L are allTRUE.

Examples

x <- list(a=NULL,b=list(x=NULL,y=character()),d=1,e=2)list.clean(x)list.clean(x, recursive = TRUE)list.clean(x, function(x) length(x) == 0L, TRUE)

Get all common cases by expression for a list

Description

Get all common cases by expression for a list

Usage

list.common(.data, expr)

Arguments

Examples

x <- list(c('a','b','c'),c('a','b'),c('b','c'))list.common(x, .)x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.common(x,type)list.common(x,names(score))foo <- list(x = LETTERS[1:3], y = LETTERS[3:5])list.common(foo)

Count the number of elements that satisfy given condition

Description

Count the number of elements that satisfy given condition

Usage

list.count(.data, cond)

Arguments

Value

An integer that indicates the number of elements with whichcond is evaluatedto beTRUE.

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.count(x, type=='B')list.count(x, min(unlist(score)) >= 9)

Call a function with a list of arguments

Description

Call a function with a list of arguments

Usage

list.do(.data, fun, ...)

Arguments

Examples

x <- lapply(1:3, function(i) { c(a=i,b=i^2)})df <- lapply(1:3, function(i) { data.frame(a=i,b=i^2,c=letters[i])})list.do(x, rbind)

Exclude members of a list that meet given condition.

Description

Exclude members of a list that meet given condition.

Usage

list.exclude(.data, cond)

Arguments

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.exclude(x, type=='B')list.exclude(x, min(score$c1,score$c2) >= 8)

Create a list from all combinations of factors

Description

Create a list from all combinations of the suppliedvectors or lists, extending the functionality ofexpand.grid from data frame to list.

Usage

list.expand(...)

Arguments

Value

A list of all combinations of the supplied vectors orlists.

Examples

list.expand(x=1:10, y=c("a","b","c"))list.expand(x=list(c(1,2), c(2,3)), y = c("a","b","c"))list.expand(  a=list(list(x=1,y="a"), list(x=2, y="b")),  b=list(c("x","y"), c("y","z","w")))

Extract an element from a list or vector

Description

Extract an element from a list or vector

Usage

list.extract()

Examples

x <- list(a=1, b=2, c=3)list.extract(x, 1)list.extract(x, 'a')

Filter a list or vector by a series of conditions

Description

The function recursively filters the data by a given series ofconditions. The filter can be a single condition or multipleconditions..data will be filtered by the first condition;then the results will be filtered by the second condition, if any;then the results will be filtered by the third, if any, etc. Theresults only contain elements satisfying all conditions specifiedin....

Usage

list.filter(.data, ...)

Arguments

Value

elements in.data satisfying all conditions

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.filter(x, type=='B')list.filter(x, min(score$c1, score$c2) >= 8)list.filter(x, type=='B', score$c2 >= 8)

Find a specific number of elements in a list or vectorsatisfying a given condition

Description

Find a specific number of elements in a list or vectorsatisfying a given condition

Usage

list.find(.data, cond, n = 1L)

Arguments

Value

A list or vector of at mostn elements in.datafound to satisfycond.

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.find(x, type=='B', 1)list.find(x, min(score$c1,score$c2) >= 9)

Find the indices of a number of elements in a list or vectorsatisfying a given condition

Description

Find the indices of a number of elements in a list or vectorsatisfying a given condition

Usage

list.findi(.data, cond, n = 1L)

Arguments

Value

an integer vector consisting of the elements indices

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.findi(x, type=='B')list.findi(x, min(score$c1,score$c2) >= 8)list.findi(x, min(score$c1,score$c2) <= 8, n = 2)

Find the first element that meets a condition

Description

Find the first element that meets a condition

Usage

list.first(.data, cond)

Arguments

See Also

list.last

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.first(x, score$c1 < 10)list.first(x, score$c1 < 9 || score$c3 >= 5) # NULL for all results are NA or FALSE

Flatten a nested list to a one-level list

Description

Flatten a nested list to a one-level list

Usage

list.flatten(x, use.names = TRUE, classes = "ANY")

Arguments

Details

The function is essentially a slightly modified version offlatten2provided by Tommy atstackoverflow.com whohas full credit of the implementation of this function.

Author(s)

Tommy

Examples

p <- list(a=1,b=list(b1=2,b2=3),c=list(c1=list(c11='a',c12='x'),c2=3))list.flatten(p)p <- list(a=1,b=list(x="a",y="b",z=10))list.flatten(p, classes = "numeric")list.flatten(p, classes = "character")

Divide list/vector elements into exclusive groups

Description

Divide list/vector elements into exclusive groups

Usage

list.group(.data, ..., sorted = TRUE)

Arguments

Value

A list of group elements each contain all the elements in.databelonging to the group

See Also

list.ungroup

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.group(x, type)list.group(x, mean(unlist(score)))

Insert a series of lists at the given index

Description

Insert a series of lists at the given index

Usage

list.insert(.data, index, ...)

Arguments

See Also

list.append,list.prepend

Examples

## Not run: x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.insert(x, 2, p2.1 = list(type='B',score=list(c1=8,c2=9)))## End(Not run)

Return a logical vector that indicates if each member of a listsatisfies a given condition

Description

Return a logical vector that indicates if each member of a listsatisfies a given condition

Usage

list.is(.data, cond, use.names = TRUE)list.if(.data, cond, use.names = TRUE)

Arguments

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.is(x,type=='B')list.is(x,min(score$c1,score$c2) >= 8)

Iterate a list by evaluating an expression oneach list element

Description

Iterate a list by evaluating an expression oneach list element

Usage

list.iter(.data, expr)

Arguments

Value

invisible(.data)

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.iter(x,cat(paste(type,'\n')))list.iter(x,cat(str(.)))

Join two lists by single or multiple keys

Description

Join two lists by single or multiple keys

Usage

list.join(x, y, xkey, ykey, ..., keep.order = TRUE)

Arguments

Examples

l1 <- list(p1=list(name='Ken',age=20),       p2=list(name='James',age=21),       p3=list(name='Jenny',age=20))l2 <- list(p1=list(name='Jenny',age=20,type='A'),       p2=list(name='Ken',age=20,type='B'),       p3=list(name='James',age=22,type='A'))list.join(l1, l2, name)list.join(l1, l2, .[c('name','age')])

Find the last element that meets a condition

Description

Find the last element that meets a condition

Usage

list.last(.data, cond)

Arguments

See Also

list.first

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.last(x, score$c1 < 10)list.last(x, score$c1 < 9 || score$c3 >= 5) # NULL for all results are NA or FALSE

Load a list from file

Description

Load a list from file

Usage

list.load(  file,  type = tools::file_ext(file),  ...,  guess = c("json", "yaml", "rds", "rdata", "xml"),  action = c("none", "merge", "ungroup"),  progress = length(file) >= 5L)

Arguments

Examples

## Not run: list.load('list.rds')list.load('list.rdata')list.load('list.yaml')list.load('list.json')## End(Not run)

Map each element in a list or vector by an expression.

Description

Map each element in a list or vector by an expression.

Usage

list.map(.data, expr)

Arguments

Value

Alist in which each element is mapped byexpr in.data

See Also

list.mapv

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.map(x, type)list.map(x, min(score$c1,score$c2))

Map multiple lists with an expression

Description

Map multiple lists with an expression

Usage

list.maps(expr, ...)

Arguments

Examples

## Not run: l1 <- list(p1=list(x=1,y=2), p2=list(x=3,y=4), p3=list(x=1,y=3))l2 <- list(2,3,5)list.maps(a$x*b+a$y,a=l1,b=l2)list.maps(..1$x*..2+..1$y,l1,l2)## End(Not run)

Map each member of a list by an expression to a vector.

Description

Map each member of a list by an expression to a vector.

Usage

list.mapv(.data, expr, as, use.names = TRUE)

Arguments

Value

Avector in which each element is mapped byexpr in.data

See Also

list.map

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.mapv(x, type)list.mapv(x, min(score$c1,score$c2))

Select members of a list that match given regex pattern

Description

Select members of a list that match given regex pattern

Usage

list.match(.data, pattern, ...)

Arguments

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.match(x,'p[12]')list.match(x,'3')

Merge a number of named lists in sequential order

Description

The function merges a number of lists in sequential orderbymodifyList, that is, the later list alwaysmodifies the former list and form a merged list, and theresulted list is again being merged with the next list.The process is repeated until all lists in... orlist are exausted.

Usage

list.merge(...)

Arguments

Details

List merging is usually useful in the merging of programsettings or configuraion with multiple versions across time,or multiple administrative levels. For example, a programsettings may have an initial version in which most keys aredefined and specified. In later versions, partial modificationsare recorded. In this case, list merging can be useful to mergeall versions of settings in release order of these versions. Theresult is an fully updated settings with all later modificationsapplied.

Examples

l1 <- list(a=1,b=list(x=1,y=1))l2 <- list(a=2,b=list(z=2))l3 <- list(a=2,b=list(x=3))list.merge(l1,l2,l3)

Get or set the names of a list by expression

Description

Get or set the names of a list by expression

Usage

list.names(.data, expr)

Arguments

Examples

list.names(c(1,2,3))list.names(c(a=1,b=2,c=3))list.names(c(1,2,3),letters[.])list.names(list(list(name='A',value=10),list(name='B',value=20)), name)

Give the order of each list element by expression

Description

Give the order of each list element by expression

Usage

list.order(.data, ..., keep.names = FALSE, na.last = TRUE)

Arguments

Value

aninteger vector.

See Also

list.sort

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.order(x, type, (score$c2)) # order by type (ascending) and score$c2 (descending)list.order(x, min(score$c1,score$c2))list.order(x, min(score$c1,score$c2), keep.names=TRUE)

Convert an object to list with identical structure

Description

This function converts an object representing data tolist that represents the same data. For example, adata.frame stored tabular data column-wisely,that is, each column represents a vector of a certaintype.list.parse converts adata.frame toa list which represents the data row-wisely so that itcan be more convinient to perform other non-tabular datamanipulation methods.

Usage

list.parse(x, ...)## Default S3 method:list.parse(x, ...)## S3 method for class 'matrix'list.parse(x, ...)## S3 method for class 'data.frame'list.parse(x, ...)## S3 method for class 'character'list.parse(x, type, ...)

Arguments

Value

list object representing the data inx

Examples

x <- data.frame(a=1:3,type=c('A','C','B'))list.parse(x)x <- matrix(rnorm(1000),ncol=5)rownames(x) <- paste0('item',1:nrow(x))colnames(x) <- c('a','b','c','d','e')list.parse(x)z <- 'a:  type: x  class: A  registered: yes'list.parse(z, type='yaml')

Prepend elements to a list

Description

Prepend elements to a list

Usage

list.prepend(.data, ...)

Arguments

See Also

list.append,list.insert

Examples

x <- list(a=1,b=2,c=3)list.prepend(x, d=4, e=5)list.prepend(x, d=4, f=c(2,3))

Bind all list elements by row

Description

The function binds all list elements by row. Each element of the list is expectedto be an atomic vector,data.frame, ordata.table. If list elementsare also lists, the result can be a list-valued matrix. In this case,list.stack may produce a better result.

Usage

list.rbind(.data)

Arguments

See Also

list.cbind,list.stack

Examples

x <- lapply(1:3,function(i) { c(a=i,b=i^2)})df <- lapply(1:3,function(i) { data.frame(a=i,b=i^2,c=letters[i])})list.rbind(x)list.rbind(df)

Remove members from a list by index or name

Description

Remove members from a list by index or name

Usage

list.remove(.data, range = integer())

Arguments

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.remove(x, 'p1')list.remove(x, c(1,2))

Reverse a list

Description

Reverse a list

Usage

list.reverse(.data)

Arguments

Examples

x <- list(a=1,b=2,c=3)list.reverse(x)

Sample a list or vector

Description

Sample a list or vector

Usage

list.sample(.data, size, replace = FALSE, weight = 1, prob = NULL)

Arguments

Examples

x <- list(a = 1, b = c(1,2,3), c = c(2,3,4))list.sample(x, 2, weight = sum(.))

Save a list to a file

Description

Save a list to a file

Usage

list.save(x, file, type = tools::file_ext(file), ...)

Arguments

Value

x will be returned.

Examples

## Not run: x <- lapply(1:5,function(i) data.frame(a=i,b=i^2))list.save(x, 'list.rds')list.save(x, 'list.rdata')list.save(x, 'list.yaml')list.save(x, 'list.json')## End(Not run)

Search a list recusively by an expression

Description

Search a list recusively by an expression

Usage

list.search(.data, expr, classes = "ANY", n, unlist = FALSE)

Arguments

Details

list.search evaluates an expression (expr) recursivelyalong a list (.data).

If the expression results in a single-valued logical vector and itsvalue isTRUE, the whole vector will be collected If it resultsin multi-valued or non-logical vector, the non-NA valuesresulted from the expression will be collected.

To search whole vectors that meet certain condition, specify theexpression that returns a single logical value.

To search the specific values within the vectors, use subsetting in theexpression, that is,.[cond] or lambda expression likex -> x[cond] wherecond is a logical vector used toselect the elements in the vector.

Examples

# Exact searchx <- list(p1 = list(type='A',score=c(c1=9)),       p2 = list(type=c('A','B'),score=c(c1=8,c2=9)),       p3 = list(type=c('B','C'),score=c(c1=9,c2=7)),       p4 = list(type=c('B','C'),score=c(c1=8,c2=NA)))## Search exact valueslist.search(x, identical(., 'A'))list.search(x, identical(., c('A','B')))list.search(x, identical(., c(9,7)))list.search(x, identical(., c(c1=9,c2=7)))## Search all equal valueslist.search(x, all(. == 9))list.search(x, all(. == c(8,9)))list.search(x, all(. == c(8,9), na.rm = TRUE))## Search any equal valueslist.search(x, any(. == 9))list.search(x, any(. == c(8,9)))# Fuzzy searchdata <- list(  p1 = list(name='Ken',age=24),  p2 = list(name='Kent',age=26),  p3 = list(name='Sam',age=24),  p4 = list(name='Keynes',age=30),  p5 = list(name='Kwen',age=31))list.search(data, grepl('^K\\w+n$', .), 'character')## Not run: library(stringdist)list.search(data, stringdist(., 'Ken') <= 1, 'character')list.search(data, stringdist(., 'Man') <= 2, 'character')list.search(data, stringdist(., 'Man') > 2, 'character')## End(Not run)data <- list(  p1 = list(name=c('Ken', 'Ren'),age=24),  p2 = list(name=c('Kent', 'Potter'),age=26),  p3 = list(name=c('Sam', 'Lee'),age=24),  p4 = list(name=c('Keynes', 'Bond'),age=30),  p5 = list(name=c('Kwen', 'Hu'),age=31))list.search(data, .[grepl('e', .)], 'character')## Not run: list.search(data, all(stringdist(., 'Ken') <= 1), 'character')list.search(data, any(stringdist(., 'Ken') > 1), 'character')## End(Not run)

Select by name or expression for each member of a list

Description

Select by name or expression for each member of a list

Usage

list.select(.data, ...)

Arguments

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.select(x, type)list.select(x, tp = type)list.select(x, type, score)list.select(x, type, score.range = range(unlist(score)))

Serialize a list

Description

Serialize a list

Usage

list.serialize(x, file, type = tools::file_ext(file), ...)

Arguments

See Also

list.unserialize

Examples

## Not run: x <- list(a=1,b=2,c=3)list.serialize(x,'test.dat')list.serialize(x,'test.json')## End(Not run)

Skip a number of elements

Description

Skip the firstn elements of a list or vector andreturn the remaining elements if any.

Usage

list.skip(.data, n)

Arguments

See Also

list.skipWhile,list.take,list.takeWhile

Examples

x <- list(a=1,b=2,c=3)list.skip(x, 1)list.skip(x, 2)

Keep skipping elements while a condition holds

Description

Keep skipping elements in a list or vector while acondition holds for the element. As long as the conditionis violated, the element will be kept and all remainingelements are returned.

Usage

list.skipWhile(.data, cond)

Arguments

See Also

list.skip,list.take,list.takeWhile

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.skipWhile(x, type=='A')list.skipWhile(x, min(score$c1,score$c2) >= 8)

Sort a list by given expressions

Description

Sort a list by given expressions

Usage

list.sort(.data, ..., na.last = NA)

Arguments

See Also

list.order

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.sort(x, type, (score$c2)) # sort by score$c2 in descending orderlist.sort(x, min(score$c1,score$c2))

Stack all list elements to tabular data

Description

Stack all list elements to tabular data

Usage

list.stack(.data, ..., data.table = FALSE)

Arguments

Examples

## Not run: x <- lapply(1:3, function(i) { list(a=i,b=i^2) })list.stack(x)x <- lapply(1:3, function(i) { list(a=i,b=i^2,c=letters[i])})list.stack(x)x <- lapply(1:3, function(i) { data.frame(a=i,b=i^2,c=letters[i]) })list.stack(x)x <- lapply(1:3, function(i) { data.frame(a=c(i,i+1), b=c(i^2,i^2+1))})list.stack(x)## End(Not run)

Subset a list

Description

Subset a list

Usage

list.subset()

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.subset(x, c('p1','p2'))list.subset(x, grepl('^p', names(x)))## Not run: list.subset(x, stringdist::stringdist(names(x), 'x1') <= 1)## End(Not run)

Generate a table for a list by expression

Description

Generate a table for a list by expression

Usage

list.table(.data, ..., table.args = list(useNA = "ifany"))

Arguments

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.table(x, type)list.table(x, type, c1 = score$c1)list.table(x, type, score$c1, table.args = list(dnn=c('type','c1')))

Take a number of elements

Description

Take the firstn elements out from a list orvector.

Usage

list.take(.data, n, force = FALSE)

Arguments

See Also

list.takeWhile,list.skip,list.skipWhile

Examples

x <- list(a=1,b=2,c=3)list.take(x,1)list.take(x,10)

Keep taking elements while a condition holds

Description

Keep taking elements out from a list or vector whilea condition holds for the element. If the condition isviolated for an element, the element will not be taken andall taken elements will be returned.

Usage

list.takeWhile(.data, cond)

Arguments

See Also

list.take,list.skip,list.skipWhile

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.takeWhile(x, type=='B')list.takeWhile(x, min(score$c1,score$c2) >= 8)

Ungroup a list by taking out second-level elements

Description

This functon reverses the grouping operation by taking outsecond-level elements of a nested list and removing the labelsof the first-level elements. For example, a list may be createdfrom paged data, that is, its first-level elements only indicatethe page container. To unpage the list, the first-level elementsmust be removed and their inner elements should be taken out toto the first level.

Usage

list.ungroup(.data, level = 1L, ..., group.names = FALSE, sort.names = FALSE)

Arguments

See Also

list.group

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))xg <- list.group(x, type)list.ungroup(xg)x <- list(a = list(a1 = list(x=list(x1=2,x2=3),y=list(y1=1,y2=3))),       b = list(b1 = list(x=list(x1=2,x2=6),y=list(y1=3,y2=2))))list.ungroup(x, level = 1)list.ungroup(x, level = 2)list.ungroup(x, level = 2, group.names = TRUE)

Unserialize a file

Description

Unserialize a file

Usage

list.unserialize(file, type = tolower(tools::file_ext(file)), ...)

Arguments

See Also

list.serialize

Examples

## Not run: list.unserialize('test.dat')list.unserialize('test.json')## End(Not run)

Transform a list of elements with similar structure into a list of decoupled fields

Description

Transform a list of elements with similar structure into a list of decoupled fields

Usage

list.unzip(  .data,  .fields = c("intersect", "union"),  ...,  .aggregate = "simplify2array",  .missing = NA)

Arguments

See Also

list.zip

Examples

list.unzip(list(p1 = list(a = 1, b = 2), p2 = list(a = 2, b = 3)))list.unzip(list(p1 = list(a = 1, b = 2), p2 = list(a = 2, b = 3, c = 4)))list.unzip(list(p1 = list(a = 1, b = 2), p2 = list(a = 2, b = 3, c = 4)), 'union')list.unzip(list(p1 = list(a = 1, b = 2), p2 = list(a = 2, b = 3, c = 4)), 'union', a = 'identity')list.unzip(list(p1 = list(a = 1, b = 2), p2 = list(a = 2, b = 3, c = 4)), 'intersect', a = NULL)x <- list(april = list(n_days = 30,   holidays = list(list('2015-04-01', 'april fools'), list('2015-04-05', 'easter')),   month_info = c(number = '4', season = 'spring')),     july = list(n_days = 31, holidays = list(list('2014-07-04', 'july 4th')),   month_info = c(number = '7', season = 'summer')))list.unzip(x, holidays = c('list.ungroup', 'unname', 'list.stack',  function(df) setNames(df, c("date", "name"))))

Update a list by appending or modifying its elements.

Description

The function updates each element of a list by evaluatinga group of expressions in the scope of the element. If thename of an expression alreadys exists in an list element,then the field with the name will be updated. Otherwise,the value with the name will be appended to the listelement. The functionality is essentially done bymodifyList.

Usage

list.update(.data, ..., keep.null = FALSE)

Arguments

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.update(x, high=max(score$c1,score$c2), low=min(score$c1,score$c2))list.update(x, exams=length(score))list.update(x, grade=ifelse(type=='A', score$c1, score$c2))list.update(x, score=list(min=0, max=10))

Give the indices of list elements satisfyinga given condition

Description

Give the indices of list elements satisfyinga given condition

Usage

list.which(.data, cond)

Arguments

Value

aninteger vector

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))list.which(x, type == 'B')list.which(x, min(score$c1,score$c2) >= 8)

Combine multiple lists element-wisely.

Description

Combine multiple lists element-wisely.

Usage

list.zip(..., use.argnames = TRUE, use.names = TRUE)

Arguments

See Also

list.unzip

Examples

x <- list(1,2,3)y <- list('x','y','z')list.zip(num=x,sym=y)

New York hourly weather data

Description

A non-tabular data of the hourly weather conditions of the New York Cityfrom 2013-01-01 to 2013-03-01.

Usage

nyweather

Format

Seehttps://openweathermap.org/weather-data

Details

Fetch date: 2014-11-23.

Processed by rlist.

To retrieve the data, please visithttps://openweathermap.org/api forAPI usage.

Make names for unnamed symbol arguments

Description

Make names for unnamed symbol arguments

Usage

set_argnames(args, data = args)

Arguments

Details

The elements of an unevaluated list of arguments may or may nothave names as given by user. For example,list.select requires userto specify the fields to select. These fields are unevaluated arguments,some of which are symbols and others are calls. For the symbols, it is naturalto make the resulted lists to have the same name for the particular arguments.

Subset a list by a logical condition

Description

Subset a list by a logical condition

Usage

## S3 method for class 'list'subset(x, subset, select, ...)

Arguments

Examples

x <- list(p1 = list(type='A',score=list(c1=10,c2=8)),       p2 = list(type='B',score=list(c1=9,c2=9)),       p3 = list(type='B',score=list(c1=9,c2=7)))subset(x, type == 'B')subset(x, select = score)subset(x, min(score$c1, score$c2) >= 8, data.frame(score))subset(x, type == 'B', score$c1)do.call(rbind,   subset(x, min(score$c1, score$c2) >= 8, data.frame(score)))

Try to evaluate an expression and return a default value ifan error occurs or otherwise return its value.

Description

Try to evaluate an expression and return a default value ifan error occurs or otherwise return its value.

Usage

tryEval(expr, def = NULL)

Arguments

Examples

x <- list(a=c(x=1,y=2),b=c(x=2,p=3))list.map(x, tryEval(x+y, NA))

Try to get the value of a symbol if exists or return a default value

Description

Try to get the value of a symbol if exists or return a default value

Usage

tryGet(symbol, def = NULL, ..., envir = parent.frame())

Arguments

Details

By default, the symbol is examined inenvir without inheritance,that is, if the symbol does not exist inenvir the default valuedef will be returned.

Examples

x <- list(a=c(x=1,y=2),b=c(x=2,p=3))list.map(x, tryGet(y,0))