[英]Remove duplicated elements from a list of tidygraph objects in R?
我有一個 tidygraph 對象的列表。 在節點數據中,我有兩列,即name
和frequency
。 我想要做的是刪除任何重復多次的列表元素(即tidygraph 對象)。 希望我的例子可以解釋更多:
首先,我創建了一些節點/邊緣數據,將它們轉換為 tidygraph 對象並將它們放在一個列表中:
library(tidygraph)
library(dplyr)
library(tidyr)
library(purrr)
library(stringr)
# create some node and edge data for the tbl_graph
nodes <- data.frame(name = c("x4", NA, NA),
val = c(1, 5, 2))
nodes2 <- data.frame(name = c("x4", NA, NA),
val = c(3, 2, 2))
nodes3 <- data.frame(name = c("x4", NA, NA),
val = c(5, 6, 7))
nodes4 <- data.frame(name = c("x4", "x2", NA, NA, "x1", NA, NA),
val = c(3, 2, 2, 1, 1, 2, 7))
nodes5 <- data.frame(name= c("x1", "x2", NA),
val = c(7, 4, 2))
nodes6 <- data.frame(name = c("x1", "x2", NA),
val = c(2, 1, 3))
edges <- data.frame(from = c(1,1), to = c(2,3))
edges1 <- data.frame(from = c(1, 2, 2, 1, 5, 5),
to = c(2, 3, 4, 5, 6, 7))
# create the tbl_graphs
tg <- tbl_graph(nodes = nodes, edges = edges)
tg_1 <- tbl_graph(nodes = nodes2, edges = edges)
tg_2 <- tbl_graph(nodes = nodes2, edges = edges)
tg_3 <- tbl_graph(nodes = nodes4, edges = edges1)
tg_4 <- tbl_graph(nodes = nodes5, edges = edges)
tg_5 <- tbl_graph(nodes = nodes6, edges = edges)
# put into list
myList <- list(tg, tg_1, tg_2, tg_3, tg_4, tg_5)
然后,我有這個小 function,它根據name
列告訴我每個列表元素的頻率。 也就是說,如果列name
在多個列表元素中重復/相同,則頻率會增加。 因此,在我上面的示例中, tg
中的name
列在我的列表中出現了 3 次(在tg
、 tg_1
和tg_2
中相同)......所以它的頻率為 3。
然后,我向每個列表元素添加一個frequency
列,並更改我原來myList
object。 例如:
freqs <- lapply(myList, function(x){
x %>%
pull(name) %>%
replace_na("..") %>%
paste0(collapse = "")
}) %>%
unlist(use.names = F) %>%
as_tibble() %>%
group_by(value) %>%
mutate(val = n():1) %>%
pull(val)
newList <- purrr::imap(myList, ~.x %>%
mutate(frequency = freqs[.y]) %>%
select(name, frequency))
現在查看newList
返回:
> newList
[[1]]
# A tbl_graph: 3 nodes and 2 edges
#
# A rooted tree
#
# Node Data: 3 × 2 (active)
name frequency
<chr> <int>
1 x4 3
2 NA 3
3 NA 3
#
# Edge Data: 2 × 2
from to
<int> <int>
1 1 2
2 1 3
[[2]]
# A tbl_graph: 3 nodes and 2 edges
#
# A rooted tree
#
# Node Data: 3 × 2 (active)
name frequency
<chr> <int>
1 x4 2
2 NA 2
3 NA 2
#
# Edge Data: 2 × 2
from to
<int> <int>
1 1 2
2 1 3
[[3]]
# A tbl_graph: 3 nodes and 2 edges
#
# A rooted tree
#
# Node Data: 3 × 2 (active)
name frequency
<chr> <int>
1 x4 1
2 NA 1
3 NA 1
#
# Edge Data: 2 × 2
from to
<int> <int>
1 1 2
2 1 3
[[4]]
# A tbl_graph: 7 nodes and 6 edges
#
# A rooted tree
#
# Node Data: 7 × 2 (active)
name frequency
<chr> <int>
1 x4 1
2 x2 1
3 NA 1
4 NA 1
5 x1 1
6 NA 1
# … with 1 more row
#
# Edge Data: 6 × 2
from to
<int> <int>
1 1 2
2 2 3
3 2 4
# … with 3 more rows
[[5]]
# A tbl_graph: 3 nodes and 2 edges
#
# A rooted tree
#
# Node Data: 3 × 2 (active)
name frequency
<chr> <int>
1 x1 2
2 x2 2
3 NA 2
#
# Edge Data: 2 × 2
from to
<int> <int>
1 1 2
2 1 3
[[6]]
# A tbl_graph: 3 nodes and 2 edges
#
# A rooted tree
#
# Node Data: 3 × 2 (active)
name frequency
<chr> <int>
1 x1 1
2 x2 1
3 NA 1
#
# Edge Data: 2 × 2
from to
<int> <int>
1 1 2
2 1 3
所以我們可以看到帶有x4, NA, NA
的name
列出現了 3 次......但不是每次都添加頻率......我似乎在倒數頻率(不是故意的)......所以, x4, NA, NA
說它的頻率是 3,然后是 2,然后是 1。
我正在嘗試刪除任何重復的列表元素並僅保留頻率最高的元素。 例如,我想要的 output 看起來像:
> newList
[[1]]
# A tbl_graph: 3 nodes and 2 edges
#
# A rooted tree
#
# Node Data: 3 × 2 (active)
name frequency
<chr> <int>
1 x4 3
2 NA 3
3 NA 3
#
# Edge Data: 2 × 2
from to
<int> <int>
1 1 2
2 1 3
[[2]]
# A tbl_graph: 7 nodes and 6 edges
#
# A rooted tree
#
# Node Data: 7 × 2 (active)
name frequency
<chr> <int>
1 x4 1
2 x2 1
3 NA 1
4 NA 1
5 x1 1
6 NA 1
# … with 1 more row
#
# Edge Data: 6 × 2
from to
<int> <int>
1 1 2
2 2 3
3 2 4
# … with 3 more rows
[[3]]
# A tbl_graph: 3 nodes and 2 edges
#
# A rooted tree
#
# Node Data: 3 × 2 (active)
name frequency
<chr> <int>
1 x1 2
2 x2 2
3 NA 2
#
# Edge Data: 2 × 2
from to
<int> <int>
1 1 2
2 1 3
在這里,我們可以看到具有重復頻率的元素已被刪除......關於我如何做到這一點的任何建議?
對原始答案的評論將是改變答案的充分動力。 也就是說,通過對分組的第一個 tibble 進行slice
來稍微更新代碼,可能像這樣:
library(tidygraph) ; library(tidyverse)
freqs <- map(myList, function(x){
x %>%
pull(name) %>%
replace_na("..") %>%
paste0(collapse = "")
}) %>%
unlist(use.names = F) %>%
as_tibble() %>%
mutate(ids = 1:n()) %>%
group_by(value) %>%
mutate(val = n():1)
ids <- freqs %>% slice(1) %>% pull(ids)
freqs <- freqs %>% pull(val)
newList <- purrr::imap(myList, ~.x %>%
mutate(frequency = freqs[.y]) %>%
select(name, frequency))
newList[sort(ids)]
[[1]]
# A tbl_graph: 3 nodes and 2 edges
#
# A rooted tree
#
# Node Data: 3 x 2 (active)
name frequency
<chr> <int>
1 x4 3
2 NA 3
3 NA 3
#
# Edge Data: 2 x 2
from to
<int> <int>
1 1 2
2 1 3
[[2]]
# A tbl_graph: 7 nodes and 6 edges
#
# A rooted tree
#
# Node Data: 7 x 2 (active)
name frequency
<chr> <int>
1 x4 1
2 x2 1
3 NA 1
4 NA 1
5 x1 1
6 NA 1
# ... with 1 more row
#
# Edge Data: 6 x 2
from to
<int> <int>
1 1 2
2 2 3
3 2 4
# ... with 3 more rows
[[3]]
# A tbl_graph: 3 nodes and 2 edges
#
# A rooted tree
#
# Node Data: 3 x 2 (active)
name frequency
<chr> <int>
1 x1 2
2 x2 2
3 NA 2
#
# Edge Data: 2 x 2
from to
<int> <int>
1 1 2
2 1 3
聲明:本站的技術帖子網頁,遵循CC BY-SA 4.0協議,如果您需要轉載,請注明本站網址或者原文地址。任何問題請咨詢:yoyou2525@163.com.