使用 igraph 包，将其转换为图形对象：

library(dplyr)
library(tidyr)
library(igraph)

g <- separate_rows(x, Neighbour_ID, convert = TRUE) %>% 
  select(from = ID, to = Neighbour_ID) %>% 
  filter(!is.na(to) & from != to) %>% 
  graph_from_data_frame(directed = FALSE)

g
# IGRAPH 1eeedee UN-- 5 5 -- 
# + attr: name (v/c)
# + edges from 1eeedee (vertex names):
#   [1] 1--2 1--3 2--4 1--3 4--5
plot(g)

我会在这里停止，因为我们的数据是 graph 格式的。但是如果你需要你的输出是 * data.frame *，那么就得到 edgelists 并合并回原始数据。

gEdge <- get.edgelist(g)
left_join(x %>% select(Name, ID),
          data.frame(unique(rbind(gEdge[, 1:2], gEdge[, 2:1]))) %>%
            mutate(X1 = as.integer(X1), X2 = as.integer(X2)) %>% 
            summarise(Neighbour_ID = paste(sort(X2), collapse = ","), .by = X1),
          by = c("ID" = "X1"))

#     Name ID Neighbour_ID
# 1   Josh  1          2,3
# 2   Emma  2          1,4
# 3   Nick  3            1
# 4   Mark  4          2,5
# 5 Claire  5            4

x %>%
  separate_rows(Neighbour_ID, convert = TRUE) %>% 
  select(-Name) %>%
  rbind(setNames(rev(.), names(.))) %>%
  filter(ID != Neighbour_ID) %>%
  distinct()%>%
  left_join(select(x, -Neighbour_ID), c(ID = 'ID')) %>%
  summarise(Neighbour_ID = toString(sort(Neighbour_ID)), .by = c(Name, ID))

  # A tibble: 5 × 3
  Name      ID Neighbour_ID
  <chr>  <int> <chr>       
1 Josh       1 2, 3        
2 Emma       2 1, 4        
3 Nick       3 1           
4 Mark       4 2, 5        
5 Claire     5 4