英文:
Create a dendrogram
问题
我有这样的数据集| SELF | OTHER || -------- | -------- || 1 | 3 || 1 | 4 || 1 | 5 || 2 | 6 || 2 | 1 || 2 | 5 || 3 | 5 || 3 | 4 || 3 | 2 || 4 | 8 || 4 | 7 || 4 | 5 || 5 | 1 || 5 | 2 || 5 | 3 || 6 | 7 || 6 | 8 || 6 | 5 || 7 | 5 || 7 | 2 || 7 | 3 || 8 | 6 || 8 | 6 || 8 | 6 |自我代表8名足球运动员，其他代表这8名足球运动员中的一个与哪些人交友。我想评估两名足球运动员的友谊圈有多相似，以及共同的朋友。然后我想做一个聚类。到目前为止我做了这些，但是出现了错误消息
footballplayers <- read.csv("footballplayer.csv", header = TRUE)
footballplayers_e <- graph_from_edgelist(as.matrix(footballplayers),directed = TRUE)
similarities <- as.dist(1 - cor(footballplayers_e), upper = TRUE)
footballplayersdend<-hclust(similarities)
plot(footballplayersdend)
但是它不起作用。Error in FUN(X[[i]], ...) : as.sociomatrix.sna input must be an adjacency matrix/array, network, or list.
英文:
I have a dataset like this
| SELF | OTHER |
|---|---|
| 1 | 3 |
| 1 | 4 |
| 1 | 5 |
| 2 | 6 |
| 2 | 1 |
| 2 | 5 |
| 3 | 5 |
| 3 | 4 |
| 3 | 2 |
| 4 | 8 |
| 4 | 7 |
| 4 | 5 |
| 5 | 1 |
| 5 | 2 |
| 5 | 3 |
| 6 | 7 |
| 6 | 8 |
| 6 | 5 |
| 7 | 5 |
| 7 | 2 |
| 7 | 3 |
| 8 | 6 |
| 8 | 6 |
| 8 | 6 |
The self represent the 8 football players and the other represents with which of this 8 football players one is befriended. I one to evaluate how similar two football players have a friendship circle, also share same people as friends. And then I would like to do a clustering
This is what I did so far, but got error message
footballplayers <- read.csv("footballplayer.csv", header = TRUE)footballplayers_e <- graph_from_edgelist(as.matrix(footballplayers),directed = TRUE)similarities <- as.dist(1 - cor(footballplayers_e), upper = TRUE)footballplayersdend<-hclust(similarities)plot(footballplayersdend)
But it doesn't work.
Error in FUN(X[[i]], ...) : as.sociomatrix.sna input must be an adjacency matrix/array, network, or list.
答案1
得分: 0
从边缘列表获取邻接矩阵的简单方法是使用Matrix::sparseMatrix函数。
library(tibble)df <- tribble(~SELF, ~OTHER,1, 3,1, 4,1, 5,2, 6,2, 1,2, 5,3, 5,3, 4,3, 2,4, 8,4, 7,4, 5,5, 1,5, 2,5, 3,6, 7,6, 8,6, 5,7, 5,7, 2,7, 3,8, 6,8, 6,8, 6)with(df, Matrix::sparseMatrix(SELF, OTHER, symmetric = TRUE))##> 8 x 8 sparse Matrix of class "ngCMatrix"##>##> [1,] . . | | | . . .##> [2,] . . . . | | . .##> [3,] | . . | | . . .##> [4,] | . | . | . | |##> [5,] | | | | . . . .##> [6,] . | . . . . | |##> [7,] . . . | . | . .##> [8,] . . . | . | . .
然后我们可以应用 dist 和 hclust，例如：
with(df, Matrix::sparseMatrix(SELF, OTHER, symmetric = TRUE)) |>dist("binary") |>hclust() |>plot()
英文:
An easy way to get an adjacency matrix from an edge list is by using Matrix::sparseMatrix
library(tibble)df <- tribble(~SELF, ~OTHER,1, 3,1, 4,1, 5,2, 6,2, 1,2, 5,3, 5,3, 4,3, 2,4, 8,4, 7,4, 5,5, 1,5, 2,5, 3,6, 7,6, 8,6, 5,7, 5,7, 2,7, 3,8, 6,8, 6,8, 6)with(df, Matrix::sparseMatrix(SELF, OTHER, symmetric = TRUE))##> 8 x 8 sparse Matrix of class "ngCMatrix"##>##> [1,] . . | | | . . .##> [2,] . . . . | | . .##> [3,] | . . | | . . .##> [4,] | . | . | . | |##> [5,] | | | | . . . .##> [6,] . | . . . . | |##> [7,] . . . | . | . .##> [8,] . . . | . | . .
Then we can apply dist and hclust e.g.:
with(df, Matrix::sparseMatrix(SELF, OTHER, symmetric = TRUE)) |>dist("binary") |>hclust() |>plot()
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