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r - 向“visNetwork”添加附加信息

问题描述

使用 R，我创建了一些关于一组人及其相互关系的虚假数据：

#relationship data

Data_I_Have <- data.frame(
   
    "Node_A" = c("John", "John", "John", "Peter", "Peter", "Peter", "Tim", "Kevin", "Adam", "Adam", "Xavier"),
    "Node_B" = c("Claude", "Peter", "Tim", "Tim", "Claude", "Henry", "Kevin", "Claude", "Tim", "Henry", "Claude"),
    " Place_Where_They_Met" = c("Chicago", "Boston", "Seattle", "Boston", "Paris", "Paris", "Chicago", "London", "Chicago", "London", "Paris"),
  "Years_They_Have_Known_Each_Other" = c("10", "10", "1", "5", "2", "8", "7", "10", "3", "3", "5"),
  "What_They_Have_In_Common" = c("Sports", "Movies", "Computers", "Computers", "Video Games", "Sports", "Movies", "Computers", "Sports", "Sports", "Video Games")
)

#data about individuals

additional_data_about_people <- data.frame(
   
    "Person" = c("John", "Peter", "Tim", "Kevin", "Adam", "Xacier", "Claude", "Henry"),
   "Job" = c("Teacher", "Lawyer", "Accountant", "Engineer", "Teacher", "Lawyer", "Engineer", "Lawyer"),
"Age" = c("50", "51", "61", "56", "65", "65", "54", "50"),
"Favorite_Food" = c("pizza", "pizza", "tacos", "pizza", "ice cream", "sushi", "sushi", "pizza")
)

使用这些信息，我能够成功地制作一个表示这些人之间关系的图网络：

library(igraph)
library(dplyr)
library(visNetwork)


graph_file <- data.frame(Data_I_Have$Node_A, Data_I_Have$Node_B)


colnames(graph_file) <- c("Data_I_Have$Node_A", "Data_I_Have$Node_B")

graph <- graph.data.frame(graph_file, directed=F)
graph <- simplify(graph)

plot(graph)

nodes <- data.frame(id = V(graph)$name, title = V(graph)$name)
nodes <- nodes[order(nodes$id, decreasing = F),]
edges <- get.data.frame(graph, what="edges")[1:2]

visNetwork(nodes, edges) %>%   visIgraphLayout(layout = "layout_with_fr") %>%
    visOptions(highlightNearest = TRUE, nodesIdSelection = TRUE)

我想，如果我可以在用户单击节点时显示每个人的信息以及他们关系的详细信息（如果可能的话），那将会很有用。

我曾尝试在 R 中使用“visEvents”和“title”选项（https://datastorm-open.github.io/visNetwork/nodes.html），但我似乎无法弄清楚。有人可以告诉我怎么做吗？

谢谢

标签： rgraphnodesvisnetwork

解决方案

Data_I_Have <- data.frame(

  "Node_A" = c("John", "John", "John", "Peter", "Peter", "Peter", "Tim", "Kevin", "Adam", "Adam", "Xavier"),
  "Node_B" = c("Claude", "Peter", "Tim", "Tim", "Claude", "Henry", "Kevin", "Claude", "Tim", "Henry", "Claude"),
  "Place_Where_They_Met" = c("Chicago", "Boston", "Seattle", "Boston", "Paris", "Paris", "Chicago", "London", "Chicago", "London", "Paris"),
  "Years_They_Have_Known_Each_Other" = c("10", "10", "1", "5", "2", "8", "7", "10", "3", "3", "5"),
  "What_They_Have_In_Common" = c("Sports", "Movies", "Computers", "Computers", "Video Games", "Sports", "Movies", "Computers", "Sports", "Sports", "Video Games")
)

common_data = purrr::imap_dfc(dplyr::select(Data_I_Have, -Node_A, -Node_B), function(item, id){
  paste(id, "&colon; ", item)
})

common_strings = purrr::map_chr(seq(1, nrow(common_data)), function(in_row){
  paste(common_data[in_row, ], collapse = "<br>")
})

edge_data = dplyr::transmute(Data_I_Have, from = Node_A, to = Node_B, title = common_strings)

#data about individualsli

additional_data_about_people <- data.frame(

  "Person" = c("John", "Peter", "Tim", "Kevin", "Adam", "Xacier", "Claude", "Henry"),
  "Job" = c("Teacher", "Lawyer", "Accountant", "Engineer", "Teacher", "Lawyer", "Engineer", "Lawyer"),
  "Age" = c("50", "51", "61", "56", "65", "65", "54", "50"),
  "Favorite_Food" = c("pizza", "pizza", "tacos", "pizza", "ice cream", "sushi", "sushi", "pizza")
)


library(igraph)
library(dplyr)
library(visNetwork)


graph_file <- data.frame(Data_I_Have$Node_A, Data_I_Have$Node_B)


colnames(graph_file) <- c("Data_I_Have$Node_A", "Data_I_Have$Node_B")

graph <- graph.data.frame(graph_file, directed=F)
graph <- simplify(graph)

plot(graph)

add_field = purrr::imap_dfc(additional_data_about_people, function(item, id){
  paste0(id, "&colon; ", item)
})
additional_strings = purrr::map_chr(seq(1, nrow(add_field)), function(in_row){
  paste(add_field[in_row, ], collapse = "<br>")
})
additional_df = data.frame(id = additional_data_about_people$Person, title = additional_strings)
additional_df2 = dplyr::left_join(data.frame(id = V(graph)$name), additional_df, by = "id")


nodes <- data.frame(id = V(graph)$name, title = additional_df2$title)
nodes <- nodes[order(nodes$id, decreasing = F),]
edges <- get.data.frame(graph, what="edges")[1:2]

edges2 = dplyr::left_join(edges, edge_data, by = c("from", "to"))


visNetwork(nodes, edges2)

然后在悬停时，我会看到有关每个节点和边缘的附加信息。

这里要注意两点：

  1. visNetwork 以 html 显示，因此您必须对特殊字符使用 html 代码，例如<br>用于返回和&colon;用于“:”。
  2. 一切都可以有一个“标题”属性，显示为工具提示，因此您也可以将其添加到边缘。

请注意，我创建了 data.frame，其中添加了属性以使其看起来像带有“：”的字段，然后将它们全部粘贴在一起以显示实际标题。

希望以上是有道理的。

另外，修复你的代码，你在一个变量名前面有一个空格，它会对它做一些奇怪的事情。

至于在单击它们时显示名称，目前这超出了我的范围。

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