如何修复R代码创建分类雇佣比例表格时的‘private未找到’错误？

原代码出现Error in private : object 'private' not found的核心原因是循环内的变量引用语法错误，同时存在多处数据框索引、变量范围的问题：

• 循环中错误使用row.table$private，正确的行索引写法应为table$private[row]或table[row, "private"]
• 直接引用employed未指定所属数据框，需明确为table$employed[row]
• 判断政府/自雇类别的时候误用了原始data对象，而非过滤后的table，且未按行索引
• 初始过滤逻辑employed != 0 & unemployed != 0需确认合理性（同一对象通常不会同时处于雇佣和失业状态）

修复后的循环版本代码 #

# 加载dplyr包（使用filter函数必需）
library(dplyr)

# 过滤数据（保留原逻辑，若需调整可修改条件）
data1 <- filter(data, employed != 0 & unemployed != 0)
table_df <- data.frame(data1) # 避免用table作为变量名，与内置函数冲突

privateSum <- 0
privateEmployed <- 0
governmentSum <- 0
governmentEmployed <- 0
selfSum <- 0
selfEmployed <- 0

for(row in 1:nrow(table_df)) {
  # 处理private分类
  if(table_df$private[row] == 1) {
    privateSum <- privateSum + 1
    if(table_df$employed[row] == 1) {
      privateEmployed <- privateEmployed + 1
    }
  }
  # 处理government分类
  if(table_df$government[row] == 1) {
    governmentSum <- governmentSum + 1
    if(table_df$employed[row] == 1) {
      governmentEmployed <- governmentEmployed + 1
    }
  }
  # 处理self分类
  if(table_df$self[row] == 1) {
    selfSum <- selfSum + 1
    if(table_df$employed[row] == 1) {
      selfEmployed <- selfEmployed + 1
    }
  }
}

# 构建结果表格
tab <- matrix(
  c(privateEmployed / privateSum, governmentEmployed / governmentSum, selfEmployed / selfSum),
  ncol = 3, byrow = TRUE
)
colnames(tab) <- c('Private','Government','Self')
rownames(tab) <- c('Proportion Employed')
tab <- as.table(tab)

print(tab)

更高效的R风格实现（推荐） #

R中不推荐用循环处理这类聚合统计，用dplyr的向量操作更简洁高效：

library(dplyr)

# 过滤数据（保留原逻辑）
data1 <- filter(data, employed != 0 & unemployed != 0)

# 计算各分类的雇佣比例
result <- data1 %>%
  summarise(
    Private = sum(private == 1 & employed == 1) / sum(private == 1),
    Government = sum(government == 1 & employed == 1) / sum(government == 1),
    Self = sum(self == 1 & employed == 1) / sum(self == 1)
  ) %>%
  t() %>% # 转置为表格格式
  as.table()

rownames(result) <- c('Private','Government','Self')
colnames(result) <- c('Proportion Employed')

print(result)

内容的提问来源于stack exchange，提问作者user20544203