本文介绍了在边列表R上匹配顶点属性的处理方法，对大家解决问题具有一定的参考价值
问题描述
我有一个定向网络列表
list(structure(list(nominator1 = structure(c(3L, 4L, 1L, 2L), .Label = c("Angela",
"Jeff", "Jim", "Pam"), class = "factor"), nominee1 = structure(c(1L,
2L, 3L, 2L), .Label = c("Andy", "Angela", "Jeff"), class = "factor")), class = "data.frame", row.names = c(NA,
-4L)), structure(list(nominator2 = structure(c(4L, 1L, 2L, 3L
), .Label = c("Eric", "Jamie", "Oscar", "Tim"), class = "factor"),
nominee2 = structure(c(1L, 3L, 2L, 3L), .Label = c("Eric",
"Oscar", "Tim"), class = "factor")), class = "data.frame", row.names = c(NA,
-4L)))
我有不同网络中人的顶点属性的数据帧
structure(list(names = structure(c(6L, 7L, 5L, 2L, 1L, 8L, 3L,
4L), .Label = c("Andy", "Angela", "Eric", "Jamie", "Jeff", "Jim",
"Pam", "Tim"), class = "factor"), gender = structure(c(3L, 2L,
3L, 2L, 3L, 1L, 1L, 2L), .Label = c("", "F", "M"), class = "factor"),
happiness = c(8, 9, 4.5, 5.7, 5, 6, 7, 8)), class = "data.frame", row.names = c(NA,
-8L))
我想找到一种方法，将正确的顶点属性匹配并添加到网络中每个人的图形对象中，以便我可以基于这些顶点属性执行分析。
如何在igraph图形对象内的边列表中匹配顶点属性？
要将边列表转换为图形对象，请使用
if(!require(igraph)) install.packages("igraph"); require(igraph)
graphs_list<-lapply(name_of_edgelist_list, graph_from_data_frame)
推荐答案
不是一个完美的答案，但这只适用于For循环方式的一个属性
for(i in 1:length(graph_list)){
graph_list[[i]]=set_vertex_attr(graph_list[[i]],"gender", value=attribute_df$gender[match(V(graph_list[[i]])$name, attribute_df$names)])
}
，graph_list表示图形对象列表，attribute_df是您拥有的属性的数据帧，
structure(list(names = structure(c(6L, 7L, 5L, 2L, 1L, 8L, 3L,
4L), .Label = c("Andy", "Angela", "Eric", "Jamie", "Jeff", "Jim",
"Pam", "Tim"), class = "factor"), gender = structure(c(3L, 2L,
3L, 2L, 3L, 1L, 1L, 2L), .Label = c("", "F", "M"), class = "factor"),
happiness = c(8, 9, 4.5, 5.7, 5, 6, 7, 8)), class = "data.frame", row.names = c(NA,
-8L))
然后，您只需更改循环(就像执行attribute_df$happiness以获取Happy属性)，即可获得每个属性。不过，采用矢量化的方式会更好
这篇关于在边列表R上匹配顶点属性的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，WP2