R语言实现两个数值向量的相邻并排式分组直方图绘制

步骤1：加载依赖包 #

• 若未安装依赖包，先执行安装代码：install.packages(c("reshape2", "ggplot2"))
• 加载包：

library(reshape2)
library(ggplot2)

步骤2：处理原始labelled类向量 #

注意：labelled类数值向量需先转换为普通numeric类型，避免ggplot绘图识别异常

# 转换labelled类为普通数值
A_num <- as.numeric(A)
B_num <- as.numeric(B)

# 合并为宽格式数据框，列名对应图例分组
raw_df <- data.frame(
  tax = A_num,
  truth = B_num
)

步骤3：长宽格式转换（匹配参考方案逻辑） #

使用reshape2包的melt函数将宽格式转为长格式，适配ggplot映射规则：

melt_df <- melt(raw_df, 
                variable.name = "group",  # 分组列对应tax/truth类别
                value.name = "personal_norm") # 数值列对应x轴取值

步骤4：绘制并排分组直方图 #

核心通过geom_bar(position = "dodge")实现相邻分离的条形效果，参数完全匹配你原有基础直方图的样式：

ggplot(melt_df, aes(x = as.factor(personal_norm), fill = group)) +
  # 核心参数position = "dodge"实现条形并排排列
  geom_bar(stat = "count", position = "dodge", color = "white") +
  # 匹配原有基础直方图的配色：tax为蓝色、truth为红色
  scale_fill_manual(values = c("tax" = rgb(0,0,1,0.7), "truth" = rgb(1,0,0,0.7)),
                    labels = c("tax", "truth")) +
  # 统一x轴范围和标签，和原有hist效果一致
  scale_x_discrete(name = "Personal Norm", limits = as.character(1:9)) +
  labs(title = "Distribution of the Personal Norm") +
  # 优化主题样式
  theme_bw()

可选调整：连续分箱模式 #

若需要完全匹配基础hist(breaks=9)的连续型分箱逻辑，而非整数分类刻度，可将绘图代码替换为：

ggplot(melt_df, aes(x = personal_norm, fill = group)) +
  geom_histogram(position = "dodge", bins = 9, color = "white") +
  scale_fill_manual(values = c("tax" = rgb(0,0,1,0.7), "truth" = rgb(1,0,0,0.7)),
                    labels = c("tax", "truth")) +
  scale_x_continuous(name = "Personal Norm", limits = c(1,9)) +
  labs(title = "Distribution of the Personal Norm") +
  theme_bw()

内容的提问来源于stack exchange，提问作者Tom。