I want to represent subclusters within clusters on variables using line graphs. I am using R.

I have two categorical variables (clusters; denoted below as a,b,c) which are nested such that each cluster has multiple subclusters (a1, a2, a3, b1, b2 and so on) within it.

I also have multiple numeric variables which I want to display by cluster and subcluster. I would like to use line graphs to display the means of the numeric variables. I have succeeded in displaying the means using summarize(),melt(), and ggplot with facet_wrap to separate the clusters. However, I don't know how I could display the subclusters.

I want to display the cluster means in with a thick black line, while displaying the subcluster means on the same graph, but "greyed out" and thinner to de-emphasize them. I have successfully used facet_wrap to separate the clusters, but I cannot think of how to get the subcluster means on the same graph.

I generated this dataset to illustrate the issue:

library(reshape)
library(tidyverse)

library(reshape)
library(tidyverse)

cases <- c(1:27)
cluster1 <- c(
"a","a","a","a","a","a","a","a","a",
"b","b","b","b","b","b","b","b","b",
"c","c","c","c","c","c","c","c","c")

cluster2 <- c(
"a1","a1","a1",
"a2","a2","a2",
"a3","a3","a3",
"b1","b1","b1",
"b2","b2","b2",
"b3","b3","b3",
"c1","c1","c1",
"c2","c2","c2",
"c3","c3","c3")

v1 <- runif(27,min = -2, max = 2)
v2 <- runif(27,min = -3, max = 1)
v3 <- runif(27,min = -4, max = 0)

df <- data.frame(cases,cluster1,cluster2,v1,v2,v3)

means.df <- subset(df) %>%
   group_by(cluster1)%>%
   summarise_at(vars(c(3:5)),mean)
means.df <- as.data.frame(means.df)

melt.df <- melt(means.df,id ="cluster1")

ggplot(data = melt.df,aes(x = variable, y = value, group = cluster1)) 
  geom_line() 
  geom_point() 
  ylab("Mean") 
  theme(axis.text.x = element_text(angle = 90,hjust = 1,vjust=0.3)) 
  facet_wrap(facets="cluster1")

Thank you in advance. Please let me know if I can provide more details.

CodePudding user response：

You could achieve your desired result by

1. Creating a dataframe with the means by cluster1 and cluster2
2. Passing this dataframe to the data argument of a second geom_line

library(reshape)
library(tidyverse)

set.seed(123)

means.df <- df %>%
  group_by(cluster1) %>%
  summarise(across(starts_with("v"), mean)) %>% 
  as.data.frame()

melt.df <- melt(means.df, "cluster1")

means.df2 <- df %>%
  group_by(cluster1, cluster2) %>%
  summarise(across(starts_with("v"), mean))%>% 
  as.data.frame()

melt.df2 <- melt(means.df2, c("cluster1", "cluster2"))

ggplot(data = melt.df, mapping = aes(x = variable, y = value, group = cluster1))  
  geom_line(data = melt.df2, aes(group = cluster2), color = "grey", alpha = .6)  
  geom_line(color = "black")  
  geom_point()  
  ylab("Mean")  
  theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.3))  
  facet_wrap(facets = "cluster1")

CodePudding user response：

You can use a different data origin to plot different layers of data as in geom_line(data = plotU, ...)

df <- data.frame(cases,cluster1,cluster2,v1,v2,v3) |>
  pivot_longer(cols = starts_with("v"), names_to = "variable")

plotD <- df |>
  group_by(variable, cluster1, cluster2) |>
  summarize(value = mean(value), .groups = "drop")

plotU <- df |>
  group_by(variable, cluster1) |>
  summarize(value = mean(value), .groups= "drop")

ggplot(plotD, aes(x = variable, y = value))  
  geom_line(aes(group = cluster2), alpha = 0.5, lty = 2)  
  geom_line(data = plotU, color = "black", group = "cluster1", size = 1.4)  
  ylab("Mean") 
  theme(axis.text.x = element_text(angle = 90,hjust = 1,vjust=0.3)) 
  facet_wrap(facets="cluster1")