我有一个SQL表,可以映射作者和书籍。我想将链接的作者和书籍(由同一作者撰写的书籍和共同撰写一本书的作者)组合在一起,并确定这些群体的大小。例如,如果J.K. Rowling与Junot Diaz合作,而Junot Diaz与Zadie Smith共同撰写了一本书,然后我希望所有三位作者都在同一组中。
这是一个玩具数据集(h / t Matthew Dowle),其中包含我正在讨论的一些关系:
set.seed(1)
authors <- replicate(100,sample(1:3,1))
book_id <- rep(1:100,times=authors)
author_id <- c(lapply(authors,sample,x=1:100,replace=FALSE),recursive=TRUE)
aubk <- data.table(author_id = author_id,book_id = book_id)
aubk[order(book_id,author_id),]
这里有人看到作者27和36共同编写了第2册,所以他们应该在同一个小组中。作者63和100同样为3;和D,F和L为4.依此类推。
除了for循环之外,我想不出一个好的方法,这个(你可以猜到)很慢。我试了一下data.table
以避免不必要的复制。有没有更好的方法呢?
aubk$group <- integer(dim(aubk)[1])
library(data.table)
aubk <- data.table(aubk)
#system.time({
for (x in 1:dim(aubk)[1]) {
if(identical(x,1)) {
value <- 1L
} else {
sb <- aubk[1:(x-1),]
index <- match(aubk[x,author_id],sb[,author_id])
if (identical(index,NA_integer_)) {
index <- match(aubk[x,book_id],sb[,book_id])
if (identical(index,NA_integer_)) {
value <- x
} else {
value <- aubk[index,group]
}
} else {
value <- aubk[index,group]
}
}
aubk[x,group:=value]
}
#})
编辑:正如@Josh O'Brien和@thelatemail所提到的,我的问题也可以说是从两列列表中查找图表的连通组件,其中每个边缘都是行,两列是连接的节点。
答案 0 :(得分:3)
将500K节点转换为邻接矩阵对我的计算机内存来说太多了,所以我无法使用igraph
。对于R版本2.15.1,RBGL
包不会更新,因此也没有更新。
在编写了许多似乎不起作用的愚蠢代码之后,我认为以下内容可以帮助我找到正确的答案。
aubk[,grp := author_id]
num.grp.old <- aubk[,length(unique(grp))]
iterations <- 0
repeat {
aubk[,grp := min(grp),by=author_id]
aubk[,grp := min(grp), by=book_id]
num.grp.new <- aubk[,length(unique(grp))]
if(num.grp.new == num.grp.old) {break}
num.grp.old <- num.grp.new
iterations <- iterations + 1
}
答案 1 :(得分:1)
以下是我对Josh O'Brien在评论(identify groups of linked episodes which chain together)中所链接的旧问题的回答。这个答案使用igraph
库。
# Dummy data that might be easier to interpret to show it worked
# Authors 1,2 and 3,4 should group. author 5 is a group to themselves
aubk <- data.frame(author_id=c(1,2,3,4,5),book_id=c(1,1,2,2,5))
# identify authors with a bit of leading text to prevent clashes
# with the book ids
aubk$author_id2 <- paste0("au",aubk$author_id)
library(igraph)
#create a graph - this needs to be matrix input
au_graph <- graph.edgelist(as.matrix(aubk[c("author_id2","book_id")]))
# get the ids of the authors
result <- data.frame(author_id=names(au_graph[1]),stringsAsFactors=FALSE)
# get the corresponding group membership of the authors
result$group <- clusters(au_graph)$membership
# subset to only the authors data
result <- result[substr(result$author_id,1,2)=="au",]
# make the author_id variable numeric again
result$author_id <- as.numeric(substr(result$author_id,3,nchar(result$author_id)))
> result
author_id group
1 1 1
3 2 1
4 3 2
6 4 2
7 5 3
答案 2 :(得分:0)
一些建议
aubk[,list(author_list = list(sort(author_id))), by = book_id]
将提供作者组列表
以下内容将为每组作者创建唯一标识符,然后返回带有
的列表
aubk[, list(author_list = list(sort(author_id)),
group_id = paste0(sort(author_id), collapse=','),
n_authors = .N),by = book_id][,
list(n_books = .N,
n_authors = unique(n_authors),
book_list = list(book_id),
book_ids = paste0(book_id, collapse = ', ')) ,by = group_id]
如果作者订单很重要,只需删除sort
并定义author_list
和group_id
注意到上述内容,虽然有用但没有做适当的分组
也许以下
# the unique groups of authors by book
unique_authors <- aubk[, list(sort(author_id)), by = book_id]
# some helper functions
# a filter function that allows arguments to be passed
.Filter <- function (f, x,...)
{
ind <- as.logical(sapply(x, f,...))
x[!is.na(ind) & ind]
}
# any(x in y)?
`%%in%%` <- function(x,table){any(unlist(x) %in% table)}
# function to filter a list and return the unique elements from
# flattened values
FilterList <- function(.list, table) {
unique(unlist(.Filter(`%%in%%`, .list, table =table)))
}
# all the authors
all_authors <- unique(unlist(unique_authors))
# with names!
setattr(all_authors, 'names', all_authors)
# get for each author, the authors with whom they have
# collaborated in at least 1 book
lapply(all_authors, FilterList, .list = unique_authors)