What is the best way to list the neighbors of selected nodes in an undirected graph?

Usage
1

I have an undirected graph and could categorise them into three categories (Gg, Sg, Eg). I want to list the neighbours of all the nodes from Eg category to Gg&Sg categories. What is the best way to do it?

I tried to approach it like below:

set.seed(123)

# Generate graph and node attribute
g <- sample_gnp(25, 2/10)
V(g)$name <- LETTERS[seq_len(gorder(g))]
V(g)$nCat <- sample(c("Gg", "Sg", "Eg"), 25, replace = TRUE)

vertex.attributes(g) %>% as_tibble() %>% filter(nCat == "Eg")
# # A tibble: 10 x 2
#    name  nCat 
#    <chr> <chr>
#  1 B     Eg   
#  2 C     Eg   
#  3 F     Eg   
#  4 H     Eg   
#  5 L     Eg   
#  6 O     Eg   
#  7 P     Eg   
#  8 Q     Eg   
#  9 W     Eg   
# 10 X     Eg  

# Fetch the adjacency list
get.adjlist(g) %>% head(3)
# $A
# + 4/25 vertices, named, from 9d72dda:
#   [1] L R W Y
# 
# $B
# + 4/25 vertices, named, from 9d72dda:
#   [1] G K P T
# 
# $C
# + 3/25 vertices, named, from 9d72dda:
#   [1] D G N
# ...

Expected output (dataframe):

# col1  col2  
# B     G
# B     K
# B     P
# B     T
# C     D
# C     G
# C     N
# ...

Are there any better approaches?

Maybe like this?

get.edgelist(g) %>% as_tibble() %>% filter(V1 %in% c("B", "C"))
# A tibble: 7 x 2
#   V1    V2   
#   <chr> <chr>
# 1 C     D    
# 2 B     G    
# 3 C     G    
# 4 B     K    
# 5 C     N    
# 6 B     P    
# 7 B     T

For these two nodes, it is fine. But when I looked for more nodes, I found that this might not be the right approach as the order of the nodes for an edge does not matter (i.e., A-B and B-A are the same).

get.edgelist(g) %>% as_tibble() %>% group_by(V1) %>% add_count() %>% distinct(V1, n) %>% arrange(V1)
# A tibble: 22 x 2
# Groups:   V1 [22]
#    V1        n
#    <chr> <int>
#  1 A         4
#  2 B         4
#  3 C         3
#  4 D         4
#  5 E         4
#  6 F         1
#  7 G         3
#  8 H         7
#  9 I         2
# 10 J         3
# # ... with 12 more rows

get.adjlist(g)
# $A
# + 4/25 vertices, named, from 9d72dda:
#   [1] L R W Y
# 
# $B
# + 4/25 vertices, named, from 9d72dda:
#   [1] G K P T
# 
# $C
# + 3/25 vertices, named, from 9d72dda:
#   [1] D G N
# 
# $D
# + 5/25 vertices, named, from 9d72dda:
#   [1] C O R S T
# 
# $O
# + 4/25 vertices, named, from 9d72dda:
#   [1] D F J T
# 
# 
# $R
# + 7/25 vertices, named, from 9d72dda:
#   [1] A D G H M P S
# 
# $S
# + 4/25 vertices, named, from 9d72dda:
#   [1] D M R Y
# 
# $T
# + 5/25 vertices, named, from 9d72dda:
#   [1] B D O X Y


get.edgelist(g) %>% as_tibble() %>% group_by(V1) %>% add_count() %>% distinct(V1, n) %>% 
  filter(V1 %in% c("A", "B", "C", "D", "O", "R", "S", "T")) %>% arrange(V1)
# A tibble: 8 x 2
# Groups:   V1 [8]
#   V1        n
#   <chr> <int>
# 1 A         4
# 2 B         4
# 3 C         3
# 4 D         4
# 5 O         1
# 6 R         1
# 7 S         1
# 8 T         2

Thanks for looking into this request.