R语言：如何为DataFrame添加同名出现次数列及车辆列表列？

你的代码问题在于：df2$Name==df1$Name会触发R的向量循环回收机制，最终length(which(...))计算的是df2中与df1所有姓名匹配的总次数，不是每行姓名单独的出现次数，所以整列会被赋值为同一个数，不符合需求。下面是两种场景的正确实现：

需求1：新增列记录姓名在df2中的出现次数 #

方法1：基础R实现 #

df1 <- data.frame(Name=c('Nick', 'Mary', 'Linus', 'Eva', 'Michael','John'))
df2 <- data.frame(Name=c('Nick', 'John', 'Mary', 'John', 'Paul', 'John'),
                  Car=c('VW', 'Volvo', 'Toyota', 'Opel', 'Opel', 'VW'))

# 统计df2中各姓名的出现频次
name_counts <- table(df2$Name)
# 匹配df1的姓名，转换为整数类型
df1$Occurrences_in_df2 <- as.integer(name_counts[df1$Name])
# 把在df2中不存在的姓名的次数设为0
df1$Occurrences_in_df2[is.na(df1$Occurrences_in_df2)] <- 0

方法2：dplyr（tidyverse）实现 #

如果习惯使用tidyverse工具链，代码更简洁直观：

library(dplyr)

df1 <- df1 %>%
  # 先统计df2的姓名频次，再左连接到df1
  left_join(count(df2, Name, name = "Occurrences_in_df2"), by = "Name") %>%
  # 把缺失值替换为0
  mutate(Occurrences_in_df2 = replace_na(Occurrences_in_df2, 0))

需求2：新增列列出每个人员的所有车辆 #

方法1：基础R实现 #

# 按姓名分组，把车辆用逗号拼接成字符串
car_list <- aggregate(Car ~ Name, data = df2, FUN = function(x) paste(x, collapse = ", "))
# 左连接到df1，保留所有df1的姓名
df1 <- merge(df1, car_list, by = "Name", all.x = TRUE)
# 把无车辆的记录替换为提示文本
df1$Car[is.na(df1$Car)] <- "无车辆"

方法2：dplyr+tidyr实现 #

library(dplyr)
library(tidyr)

df1 <- df1 %>%
  left_join(
    df2 %>% 
      group_by(Name) %>% 
      summarise(Car = str_c(Car, collapse = ", ")), 
    by = "Name"
  ) %>%
  mutate(Car = replace_na(Car, "无车辆"))

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