我使用带有 R 的包进行了 k-medoid 聚类分析CRAN cluster。数据位于一个data.frame名为 df4 的 13111 obs 上。11 个二进制和序数值。聚类后，我将聚类结果应用于原始data.frame显示相应的聚类编号到用户 ID。
如何根据集群聚合二元和序数选择？
例如，Gender变量具有男性/女性值，Age范围为“18-20”、“21-24”、“25-34”、“35-44”、“45-54”、“55-64”和“ 65+”。我想要变量Gender和类别中每个集群的男性和女性值的总和Age。
这是我的带有集群标签列的 data.frame 的头部：
#12 variables because I added the clustering object to the data.frame
#I only included two variables from the R output
> str(df4)
'data.frame': 13111 obs. of 12 variables:
$ Age : Factor w/ 7 levels "18-20","21-24",..: 6 6 6 6 7 6 5 7 6 3 ...
$ Gender : Factor w/ 2 levels "Female","Male": 1 1 2 2 2 1 2 1 2 2 …
#I only included three variables from the R output
> head(df4)
Age Gender
1 55-64 Female
2 55-64 Female
3 55-64 Male
4 55-64 Male
5 65+ Male
6 55-64 Female
这是一个类似于我的数据集的可重现示例：
age <- c("18-20", "21-24", "25-34", "35-44", "45-54", "55-64", "65+")
gender <- c("Female", "Female", "Male", "Male", "Male", "Male", "Female")
smalldf <- data.frame(age, gender)
#Import cluster package
library(cluster)
#Create dissimilarity matrix
#Gower coefficient for finding distance between mixed variable
smalldaisy4 <- daisy(smalldf, metric = "gower",
type = list(symm = c(2), ordratio = c(1)))
#Set randomization seed
set.seed(1)
#Pam algorithm with 3 clusters
smallk4answers <- pam(smalldaisy4, 3, diss = TRUE)
#Apply cluster IDs to original data frame
smalldf$cluster <- smallk4answers$cluster
期望的输出结果（假设）：
cluster female male 18-20 21-24 25-34 35-44 45-54 55-64 65+
1 1 1 1 1 2 1 0 3 1 0
2 2 2 1 1 1 0 1 2 0 0
3 3 0 1 1 1 1 1 0 2 3
让我知道我是否可以提供更多信息。