如何在R语言中筛选model、country、year相同但factor不同的数据行？

我们需要从给定的R语言DataFrame中，筛选出model、country、year取值完全一致，但factor取值不同的数据行。

原始数据与代码 #

model <- c("A","B","C","A","A","C","B","A")
country <- c("Italy","Germany","Norway","Italy","France","Germany","Norway","Italy")
year <- c(2016,2016,2016,2016,2015,2015,2015,2015)
value <-  c(14,24,11,34,73,11,33,22)
factor <- c("NEW","OLD","OLD","OLD","OLD","OLD","NEW","NEW")

df <- data.frame(model,country,year,value, factor)

生成的原始DataFrame：

model country year value factor
1     A   Italy 2016    14    NEW
2     B Germany 2016    24    OLD
3     C  Norway 2016    11    OLD
4     A   Italy 2016    34    OLD
5     A  France 2015    73    OLD
6     C Germany 2015    11    OLD
7     B  Norway 2015    33    NEW
8     A   Italy 2015    22    NEW

解决方案 #

方法1：使用dplyr包 #

通过分组后筛选出组内factor存在多种取值的行：

library(dplyr)

result <- df %>%
  group_by(model, country, year) %>%
  filter(n_distinct(factor) > 1) %>%
  ungroup()

print(result)

方法2：Base R实现 #

通过构造分组键，统计每组的factor唯一值数量，再筛选目标组：

# 构造分组键
group_key <- with(df, paste(model, country, year, sep = "_"))
# 统计每组factor的唯一值数量
factor_unique_counts <- tapply(df$factor, group_key, function(x) length(unique(x)))
# 筛选出factor有多种取值的组
target_groups <- names(factor_unique_counts[factor_unique_counts > 1])

# 提取目标行
result <- df[group_key %in% target_groups, ]
print(result)

输出结果 #

model country year value factor
1     A   Italy 2016    14    NEW
4     A   Italy 2016    34    OLD

注：你提供的期望输出中value为22的行（原始数据第8行）对应的year是2015年，与另一行的2016年不一致，不符合筛选条件，正确符合要求的结果如上。

内容的提问来源于stack exchange，提问作者user18937485