我正在执行一个实体消歧项目,我有一个同名作者的数据,并有以下列:author ID和coauthor names。
我需要找到由作者ID标识的作者与他/她曾经合作过的所有合作者之间的数字协作。
下面是数据文件的一个示例:
author.ID coauthor.names
1 J Smith, A Greer
1 J Adams, J Smith
2 D Richardson, J Smith我想要的输出是:
author.ID coauthor.name collaboration.times
1 J Smith 2
1 J Adams 1
1 A Greer 1
2 D Richardson 1
2 J Smith 1我尝试过将所有的合著者(用逗号分隔)和一个特定的author ID组合成一个大字符串,我将在这个巨大的字符串上使用来自stringr包的stringr包,但是我不知道我是否在解决这个问题的正确道路上。
是否有更有效或更优雅的方法来解决这个问题?
谢谢。
发布于 2017-04-07 04:17:57
假设你在处理这样的数据:
mydf <- structure(list(author.ID = c(1L, 1L, 2L), coauthor.names = c("J Smith, A Greer",
"J Adams, J Smith", "D Richardson, J Smith")), .Names = c("author.ID",
"coauthor.names"), row.names = c(NA, 3L), class = "data.frame")
mydf
## author.ID coauthor.names
## 1 1 J Smith, A Greer
## 2 1 J Adams, J Smith
## 3 2 D Richardson, J Smith..。您可以从我的"splitstackshape“包中尝试cSplit,然后使用”data.table“中的.N进行聚合:
library(splitstackshape)
cSplit(mydf, "coauthor.names", ",", "long")[
, list(collaboaration.times = .N), .(author.ID, coauthor.names)][]
# author.ID coauthor.names collaboaration.times
# 1: 1 J Smith 2
# 2: 1 A Greer 1
# 3: 1 J Adams 1
# 4: 2 D Richardson 1
# 5: 2 J Smith 1假设你在处理这样的数据:
mydf2 <- structure(list(author.ID = c(1L, 1L, 2L), coauthor.names = structure(list(
c("J Smith", "A Greer"), c("J Adams", "J Smith"), c("D Richardson",
"J Smith")), class = "AsIs")), .Names = c("author.ID", "coauthor.names"
), row.names = c(NA, 3L), class = "data.frame")
mydf2
## author.ID coauthor.names
## 1 1 J Smith,....
## 2 1 J Adams,....
## 3 2 D Richar......。您可以从listCol_l开始(同样从“splitstackshape”开始),然后以相同的方式计数。
listCol_l(mydf2, "coauthor.names")[
, list(collaboration.times = .N), .(author.ID, coauthor.names_ul)]
# author.ID coauthor.names_ul collaboration.times
# 1: 1 J Smith 2
# 2: 1 A Greer 1
# 3: 1 J Adams 1
# 4: 2 D Richardson 1
# 5: 2 J Smith 1"tidyverse“等价物可能如下所示:
library(tidyverse)
# For a single character string as "coauthor.names"
mydf %>%
mutate(coauthor.names = lapply(strsplit(coauthor.names, ","), trimws)) %>%
unnest() %>%
group_by(author.ID, coauthor.names) %>%
summarise(collaboration.times = n())
# If "coauthor.names" is already a `list`.
mydf2 %>%
unnest() %>%
group_by(author.ID, coauthor.names) %>%
summarise(collaboration.times = n())https://stackoverflow.com/questions/43268482
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